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Tag Archives: trends

IBM’s Rob Thomas details key AI trends in shift to hybrid cloud

March 19, 2021   Big Data

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The last year has seen a major spike in the adoption of AI models in production environments, in part driven by the need to drive digital business transformation initiatives. While it’s still early days as far as AI is concerned, it’s also clear AI in the enterprise is entering a new phase.

Rob Thomas, senior vice president for software, cloud, and data platform at IBM, explains to VentureBeat how this next era of AI will evolve as hybrid cloud computing becomes the new norm in the enterprise.

As part of that effort, Thomas reveals IBM has formed a software-defined networking group to extend AI all the way out to edge computing platforms.

This interview has been edited for brevity and clarity.

VentureBeat: Before the COVID-19 pandemic hit, there was a concern AI adoption was occurring slowly. How much has that changed in the past year?

Rob Thomas: We’ve certainly got massive acceleration for things like Watson Assistant for customer service. That absolutely exploded. We had nearly 100 customers that started and then went live in the first 90 days after COVID hit. When you broaden it out, there are five big use cases that have come up over the last year. One is customer service. Second is around financial planning and budgeting. Thirdly are things such as data science. There’s such a shortage of data science skills, but that is slowly changing. Fourth is around compliance. Regulatory compliance is only increasing, not decreasing. And then fifth is AI Ops. We launched our first AI ops product last June and that’s exploded as well, which is related to COVID in that everybody was forced remote. How do we better manage our IT systems? It can’t be all through humans because we’re not on site. We’ve got to use software to do that. I think that was 18 months ago, I wouldn’t have given you those five. I would have said “There’s a bunch of experimentations.” Now we see pretty clearly there are five things people are doing that represent 80% of the activity.

VentureBeat: Should organizations be in the business of building AI or should they buy it in one form or another?

Thomas: I hate to be too dramatic, but we’re probably in a permanent and a secular change where people want to build. Trying to fight that is a tough discussion because people really want to build. When we first started with Watson, the idea was this is a big platform. It does everything you need. I think what we’ve discovered along the way is if you componentize to focus where we think we’re really good, people will pick up those pieces and use them. We focused on three areas for AI. One is natural language processing (NLP). I think if you look at things like external benchmarks, we had the best NLP from a business context. In terms of document understanding, semantic parsing of text, we do that really well. The second is automation. We’ve got really good models for how you automate business processes. Third is trust. I don’t really think anybody is going to invest to build a data lineage model, explainability model, or bias detection. Why would a company build that? That’s a component we can provide. If you want them to be regulatory compliant, you want them to have explainability, then we provide a good answer for that.

VentureBeat: Do you think people understand explainability and the importance of the provenance of AI models and the importance of that yet? Are they just kind of blowing by that issue in the wake of the pandemic?

Thomas: We launched the first version of what we built to address that around that two years ago. I would say that for the first year we got a lot of social credit. This changed dramatically in the second half of last year. We won some significant deals that were specifically for model management explainability and lifecycle management of AI because companies have grown to the point where they have thousands of AI models. It’s pretty clear, once you get to that scale, you have no choice but to do this, so I actually think this is about to explode. I think the tipping point is once you get north of a thousandish models in production. At that point, it’s kind of like nobody’s minding the store. Somebody has to be in charge when you have that much machine learning making decisions. I think the second half of last year will prove to be a tipping point.

Above: IBM senior VP of software, cloud, and data Rob Thomas

VentureBeat: Historically, AI models have been trained mainly in the cloud, and then inference engines are employed to push AI out to where it’d be consumed. As edge computing evolves, there will be a need to push the training of AI models out to the edge where data is being analyzed at the point of creation and consumption. Is that the next AI frontier?

Thomas: I think it’s inevitable AI is gonna happen where the data is because it’s not economical to do the opposite, which is to start everything with a Big Data movement. Now, we haven’t really launched this formally, but two months ago I started a unit in IBM software focused on software-defined networking (SDN) and the edge. I think it’s going to be a long-term trend where we need to be able to do analytics, AI, and machine learning (ML) at the edge. We’ve actually created a unit to go after that specifically.

VentureBeat: Didn’t IBM sell an SDN group to Cisco a long time ago now?

Thomas: Everything that we sold in the ’90s was hardware-based networking. My view is everything that’s done in hardware from a networking at the edge perspective is going to be done in software in the next five to seven years. That’s what’s different now.

VentureBeat: What differentiates IBM when it comes to AI most these days?

Thomas: There are three major trends that we see happening in the market. One is around decentralization of IT. We went from mainframes that are centralized to client/server and mobile. The initial chapter of public cloud was very much a return to a centralized architecture that brings everything to one place. We are now riding the trend that says that we will decentralize again in the world that will become much more about multicloud and hybrid cloud.

The second is around automation. How do you automate feature engineering and data science? We’ve done a lot in the realm of automation. The third is just around getting more value out of data. There was this IDC study last year that 90% of the data in businesses is still unutilized or underutilized. Let’s be honest. We haven’t really cracked that problem yet. I’d say those are the three megatrends that we’re investing against. How does that manifest in the IBM strategy? In three ways. One is we are building all of our software on open source. That was not the case two years ago. Now, in conjunction with the Red Hat acquisition, we think there’s room in the market for innovation in and around open source. You see the cloud providers trying to effectively pirate open source rather than contribute. Everything we’re doing from a software perspective is now either open source itself or it’s built on open source.

The second is around ecosystem. For many years we thought we could do it ourselves. One of the biggest changes we’ve made in conjunction with the move to open source is we’re going to do half of our business by making partners successful. That’s a big change. That why you see things like the announcement with Palantir. I think most people were surprised. That’s probably not something we would have done two years ago. It’s kind of an acknowledgment that all the best innovation doesn’t have to come from IBM. If we can work with partners that have a similar philosophy in terms of open source, that’s what we’re doing.

The third is a little bit more tactical. We announced earlier this year that we’ve completely changed our go-to-market strategy, which is to be much more technical. That’s what we’ve heard customers want. They don’t want a salesperson to come in and read them the website. They want somebody to roll up their sleeves and actually build something and co-create.

VentureBeat: How do you size up the competitive landscape?

Thomas: Watson components can run anywhere. The real question is why is nobody else enabling their AI to run anywhere? IBM is the only company doing that. My thesis is that most of the other big AI players have a strategy tax. If your whole strategy is to bring everything to our cloud, the last thing you want to do is enable your AI to run other places because then you’re acknowledging that other places exist. That’s a strategy advantage for us. We’re the only ones that can truly say you can bring the AI to where the data is. I think that’s going to give us a lot of momentum. We don’t have to be the biggest compute provider, but we do have to make it incredibly easy for companies to work across cloud environments. I think that’s a pretty good bet.

VentureBeat. Today there is a lot of talk about MLOps, and we already have DevOps and traditional IT operations. Will all that converge one day or will we continue to need a small army of specialists?

Thomas: That’s a little tough to predict. I think the reason we’ve gotten a lot of momentum with AI Ops is because we took the stuff that was really hard in terms of data virtualization, model management, model creation, and automated 60-70% of that. That’s hard. I think it’s going to be harder than ever to automate 100%. I do think people will get a lot more efficient as they get more models in production. You need to manage those in an automated fashion versus a manual fashion, but I think it’s a little tough to predict that at this stage.

VentureBeat: There’re a lot of different AI engines. IBM has partnered with Salesforce. Will we see more of that type of collaboration? Will the AI experience become more federated?

Thomas: I think that’s right. Let’s look at what we did with Palantir. Most people thought of Palantir as an AI company. Obviously, they associate Watson with AI. Palantir does something really good, which is a low-code, no-code environment so that the data science team doesn’t have to be an expert. What they don’t have is an environment for the data scientist that does want to go build models. They don’t have a data catalog. If you put those two together, suddenly you’ve got an AI system that’s really designed for a business. It’s got low code, no code, it’s got Python, it’s got data virtualization, a data catalog. Customers can use that joint stack from us and will be better off than had they chosen one or the other and then tried to fix the things themselves. I think you’ll probably see more partnerships over time. We’re really looking for partnerships that are complementary to what we’re doing.

VentureBeat: If organizations are each building AI models to optimize specific processes in their favor, will this devolve into competing AI models simply warring with one another?

Thomas: I don’t know if it’ll be that straightforward. Two companies are typically using very different datasets. Now maybe they’re both joining with an external dataset that’s common, but whatever they have is first-party data or third-party data that is probably unique to them. I think you get different flavors, as opposed to two things that are conflicting or head to head. I think there’s a little bit more nuance there.

VentureBeat: Do you think we’ll keep calling it AI? Or will we get to a point where we just kind of realize that it’s a combination of algorithms and statistics and math [but we] don’t have to necessarily call it AI?

Thomas: I think the term will continue for a while because there is a difference between a rules-based system and a true learning machine that gets better over time as you feed it more data. There is a real distinction.

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New Customer Experience Needs and Commerce Trends for 2021

February 24, 2021   CRM News and Info

By Jack M. Germain

Feb 24, 2021 5:08 AM PT

As consumers get comfortable with their newfound digital wallets and gift cards, marketers must continue to adapt their strategies to changes in shopping behavior to better finesse the customer experience.

Both consumers and vendors have had non-stop adjustments. Lockdowns and social distancing requirements accelerated the adoption of new technologies. Commerce trends that were on the horizon pre-COVID-19 were suddenly adopted at a brisk pace. Online food ordering, curbside pickup, and BOPIS (buy online, pick up in store) are presenting new challenges to store owners and brand marketers.

Commerce analysts do not see consumers shedding their newfound buying options in the wake of a post-pandemic marketplace. Concerns for health safety, social distancing, and remote working will remain as the center stage in the daily lives of millions of shoppers.

So brands must continue to assess how they can best meet the dramatically changing landscape of commerce. How brands deliver customer experience (CX) will determine where and how consumers continue to shop.

Four trends about customer experience and the new commerce will define 2021 and beyond, according to Jennifer Conklin, sector lead of unified commerce at Capgemini North America. Contactless customer experience, omnichannel shopping, personalization and changing customer journeys, and voice commerce will power the customer experience engine going forward.

“Consumer shopping and spending behavior have significantly shifted since the pandemic began in March 2020. Recent Capgemini research showed that 48 percent of holiday season purchases were for essential items, with consumers prioritizing clothing (36 percent), beauty/personal care products (21 percent), and electrical items (21 percent),” Conklin told CRM Buyer.

As for luxury products, Capgemini research showed that 47 percent of consumers expected a decrease in spend over the holidays while 29 percent predicted an increase in luxury purchases, she noted.

New Normal Sales Tools

Not all analysts are confident that consumers will ever return to brick-and-mortar stores as their primary shopping suppliers. Conklin is sure the four commerce drivers she identified have staying power. Her reasons make sense.

A contactless customer experience is one of the main demands indicated by consumers. Retailers that rolled out simple curbside options during the pandemic will put high-tech BOPIS and curbside offerings in place. Many shoppers still do not want to linger and browse in-store.

Omnichannel shopping has proven its value to shoppers looking for reliable delivery and better pricing options. Merchants who demonstrate that they are able to quickly get products to consumers, resolve issues with customer service, and provide fast delivery and returns will be the ones that thrive.

Personalization and changing customer journeys are the new sales tools. As brands look to understand new customer journeys, they must get creative online to improve engagement and increase customer loyalty, Conklin suggested.

Voice Commerce is the shopping tool just as voice commands are finding new uses in smart homes and electronic gadgets. Retailers will try to figure out how they can use voice to make the customer experience even more engaging.

Safety is still at the forefront of consumer concerns, noted Conklin. Last year, Capgemini research revealed that 77 percent of consumers expect to increase their use of touchless technologies to avoid interactions that require physical contact.

Her company’s research found that 59 percent of consumers prefer to use voice interfaces in public places during the pandemic. Researchers do not expect that percentage to shrink in a post-pandemic era.

“If this is not on merchants’ 2021 digital road maps, it needs to be added,” she urged.

The Journey Counts

To better understand the changing directions of shopping journeys, merchants should inject more effort by adding a personalization element, according to Conklin. This helps the customer feel known and valued as they make their purchasing decisions.

“While there are several degrees of personalization capabilities, merchants can start small by incentivizing customers to create account profiles and fine-tune their segmentation efforts so the organization can reach out to the customer with the right message at the right time,” she offered.

Data also plays an integral role when it comes to the success of personalization and omnichannel efforts. Companies need to ensure they are working with one central view of their customer across the organization from sales, service, marketing, and commerce, Conklin said.

“No matter who in the company is communicating with the customer, they need to have the relevant data at their fingertips to be successful in their role. This is also critical in order to deliver a consistent, seamless experience to the customer across every touchpoint in the customer journey,” she explained.

This data and direct customer feedback can influence product sets as well. That enables retailers to further refine their inventory strategies cross-channel/cross-market, she added.

What’s Ahead

Consumers’ modes of interaction and habits have changed and are continuing to do so as we adapt to the “new normal,” according to Durk Stelter, CRO of Linc, a CX automation platform provider in Sunnyvale, Calif. This year will bring further transition and change to retail. Shoppers’ expectations continue to rise for anywhere, anytime interactions with brands.

“As the fixed boundary between workplace and home has eroded, so has the divide between daytime computer use and leisure time on mobile. Amidst overlapping worlds, digital shopping has become omnipresent and around the clock — shifting among devices and following shoppers around their homes, into their cars, and on their cautious forays into the outside world,” Stelter told CRM Buyer.

These trends will stick for now. However, as stores reopen, the trends will likely evolve, creating more cohesion between the online and in-store experience, suggested Shelly Socol, co-founder of 1R, a digital commerce and retail strategy agency in New York City. The online buying experience will continue to evolve and grow so it is inevitable that the trends will morph.

“However, the trends we are seeing today are ahead of their time due to the pandemic. Both merchants and consumers have progressed by leaps and bounds over the past year, Socol told CRM Buyer.

Merchants have been forced to build more robust shopping experiences and offer high-touch customer service. Consumers, on the other hand, have had to get used to shopping online more often, she described.

“What might have been once foreign and uncomfortable for them has become a standard, and it is likely consumers will not revert back to shopping only in-store even when they are fully open,” predicted the 1R co-founder.

Differing CX Realities

Managing CX is becoming different now for in-store commerce versus e-commerce, according to Capgemini’s Conklin. In-store traffic remains at an all-time low. But e-commerce channels have invested heavily in robust customer experience capabilities.

“Since customers do not want to browse and shop in-store, the online digital experience needs to mimic the in-store experience. This means intuitive navigation, detailed product pages with full imagery, and personalized technology to foster loyalty,” advised Conklin.

Brands and retailers will also start to invest more in immersive technologies to bring products to life and embed this functionality into their sites, she noted. This will enable customers to configure products using a 3D configurator, augmented reality, or virtual photography.

“Once the pandemic subsides, the in-store shopping experience will return and likely be more immersive than ever before. Stores will likely carry less inventory and allocate space to be utilized for unique and engaging experiences such as product demonstrations, classes, spa treatments, cafes, and so much more where customers can spend time in-store,” she predicted.

CX in general has dramatically changed since the pandemic started. Customers expect 24/7 individualized personalization support on everything from pre-purchase information, to order support, returns, and loyalty and membership information, observed Linc’s Stelter.

“The rising degree of difficulty for customer service interactions requires organization-wide responsiveness and flexibility. As brands increasingly turn to automated solutions to help manage the volume of inquiries, the quality of digital-human interactions is crucial,” he said.

Create Seamless Shopping Experiences

A primary consideration is changing how marketers use chatbots, as Stelter sees it. To meet the challenges of 2021, digital interactions must be adaptive and empower the consumer to drive the conversation.

In order to improve their customer experience, merchants need to focus on accessibility, noted Meghan Brophy, retail and e-commerce analyst at Fit Small Business. That is one aspect of online shopping that has been neglected for too long.

“To truly offer a great customer experience, merchants need to make online shopping accessible to all. Simple changes like labeling form fields, adding alt text to images, and not using strikethroughs to show sale prices can make a big difference,” she told CRM Buyer.

More important than ever is for consumers to have a seamless shopping experience. Shoppers are starting and completing buying journeys using a mix of channels, and they all need to work together smoothly, explained Brophy.

For example, a customer might start on a brand’s Instagram page and add items to the cart. Then the customer visits the website later to complete the purchase and picks up the order in-store.

Many options exist for brands to maximize the online customer experience. Helpful and fast customer service is key, in addition to free shipping and easy returns. SMS is also a rising form of communication with consumers and is becoming a must, offered 1R’s Socol.

Brands should also build and utilize flexible landing pages populated with both content and products. These pages can form the foundation for marketing purposes to drive traffic. Brands can create storytelling experiences that complement the website and allow the brand to produce unique content for different target audiences.
end enn New Customer Experience Needs and Commerce Trends for 2021


Jack%20M.%20Germain New Customer Experience Needs and Commerce Trends for 2021
Jack M. Germain has been an ECT News Network reporter since 2003. His main areas of focus are enterprise IT, Linux and open-source technologies. He is an esteemed reviewer of Linux distros and other open-source software. In addition, Jack extensively covers business technology and privacy issues, as well as developments in e-commerce and consumer electronics. Email Jack.

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Conversational Platform Trends for 2021

January 21, 2021   CRM News and Info

Live chat and conversational platform technologies have made significant advancements in the past few years. Thanks to AI and machine learning, these implementations have gone beyond just being a customer support tool, to a crucial component of an e-commerce website’s revenue engine.

With the pandemic ongoing, e-commerce is booming right now at the expense of brick-and-mortar. But with Amazon still accounting for 44 percent of all online transactions, e-commerce business owners must constantly search for ways to keep customers on their site and returning for future business.

Live chat is one of the most important tools that retailers can have on their website so that when a customer has any questions or concerns about a product or service, they can get instant customer support. This is particularly important to service consumers with a high-level of intent to purchase, so they don’t bounce to a competitor to get their questions answers and make the buy.

However, a live chat tool is only as good as the team and technology behind it — and live chat experiences can vary dramatically from retailer to retailer. There are essential factors that every online seller who is serious about conversions needs to consider.

Here’s what retailers need to know to get maximum conversions and satisfied customers from live chat tools in 2021 and beyond.

So Many Channels, So Little Time

When today’s consumers have a question for a retailer, there are a growing number of communications channels they might try to send a message through: the website, email, Facebook, Twitter, Instagram, etc. The longer a customer is left waiting for a response, the more likely a serious shopper will have searched elsewhere for what they were looking for.

But now, live chat technology can integrate into all the various communication channels. Customer messages that arrive via channel can be sent to an app on the smartphones of the retailer’s support staff, so they can instantly respond to any customer messages that come through any channel, at any time of day.

AI, Machine Learning

Very few technologies haven’t benefited from AI and machine learning — and live chat is no exception. There is a fine balance between technology and human experience when it comes to customer satisfaction. At the end of the day, the advantage of automation is that it saves businesses time and money. The downside is that sometimes your customers just want to speak with a human and get frustrated dealing with bots.

Hiring humans to answer the same questions over and over makes little sense. This is why many retailers offer a chatbot to respond to common questions, but these can often be a lackluster or frustrating experience from the customer’s perspective.

A live chat system with good AI will monitor hundreds of thousands or millions of live chat conversations between customers and sales associates to identify common customer problems and determine which questions can be automated verses requiring human interaction.

AI can now analyze all your customers’ live chat sessions to understand the most common questions, integrate these answers into a bot, and redirect customers who want to speak to a human instantly with the right person.

AI and Customer Intent

One of the hottest topics recently for retailers has been customer intent. Only 17 percent of customers who visit a website have a serious intention to buy. In turn, this means that 83 percent of people visiting a website have no intent of actually buying anything.

Thanks to AI, state-of-the-art live chat systems can help identify which shoppers on a website have a serious intent to purchase. This gives the retailer a chance to open up a live chat portal and offer these customers the chance to speak to a sales associate. Very much like the in-store experience, these sales associates can help answer any questions, maximize the chance of converting these customers, upsell more products, and offer the best customer experience.

Integrating Freelance Product Experts

One of the primary reasons that retailers don’t have a 24/7 team of people on standby to live chat with their online customers is expense.

However, another key trend that has unfolded recently is integrating independent product experts and sales associates who work on a freelance model (similar to Uber), in the e-commerce live chat system.

Instead of paying full-time staff to respond to customer queries, retailers can now tap into a pool of freelance product experts who work from home and will help customers on behalf of the retailer.

For example, Lowes uses a team of freelance home improvement experts to respond to its customers. These gig-economy experts are pre-vetted on their expertise — in this case, home improvement. Many other retailers utilize freelance experts for chat to help with beauty products, photography, consumer electronics, etc.

These expert advisors work from home, choose their own hours, and jump onto the conversational platform whenever they want to live chat with customers of a particular retailer, or even multiple retailers’ customers, to answer product questions or upsell. The freelance advisor gets paid per chat session they participate in and earns a commission of sales they help to make.

From a retailer’s perspective, they have best-of-breed product experts helping convert and upsell customers who are identified as having serious intent on their website, without the expense of paying full-time staff.

Conclusion

E-commerce continues to grow exponentially, but with Amazon always just one click away, retailers can outdo the competition by providing a better customer experience and adding the human element to their website. Live chat is the main portal for connecting online customers to people from your company, or someone who works on your behalf.

A live chat or conversational platform is only as good as the technology and the team behind it. Retailers who see it as a crucial part of their e-commerce experience and use the technology to the best of its ability will experience greater conversions and customer satisfaction scores compared to those who do not.
end enn Conversational Platform Trends for 2021


Terrence%20Fox Conversational Platform Trends for 2021
Terrence Fox is head of innovation and strategy at iAdvize.

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Database trends: Why you need a ledger database

January 18, 2021   Big Data
 Database trends: Why you need a ledger database

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The problem: The auto dealer can’t sell the car without being paid. The bank doesn’t want to loan the money without insurance. The insurance broker doesn’t want to write a policy without payment. The three companies need to work together as partners, but they can’t really trust each other.

When businesses need to cooperate, they need a way to verify and trust each other. In the past, they traded signed and sealed certificates. Today, you can deliver the same assurance with digital signatures, a mathematical approach that uses secret keys to let people or their computers validate dates. Ledger databases are a new mechanism for marrying data storage with some cryptographic guarantees.

The use cases

Any place where people need to build a circle of trust is a good place to deploy a ledger database.

  • Crypto currency like Bitcoin inspired the application by creating a software tool for tracking the true owner of every coin. The blockchain run by the nodes in the Bitcoin network is a good example of how signatures can validate all transactions changing ownership.
  • Shipping companies need to track goods as they flow through a network of trucks, ships, and planes. Loss and theft can be minimized if each person along the way explicitly transfers control.
  • Manufacturers, especially those that create products like pharmaceuticals, want to make sure that no counterfeits enter the supply chain.
  • Coalitions, especially industry groups, that need to work together while still competing. The ledger database can share a record of the events while providing some assurance that the history is accurate and unchanged.

The solution

Standard databases track a sequence of transactions that add, delete, or change entries. Ledger databases add a layer of digital signatures for each transaction so that anyone can audit the list and see that it was constructed correctly. More importantly, no one has gone back to adjust a previous transaction, to change history so to speak.

The digital signatures form a chain that links the individual rows or entries. Each signature is constructed to certify the data in the new row and also the data in the previous row. Taken together, all of the signatures added over time certify the sequence that data was added to the log. An auditor can look at some or all of the signatures to make sure they’re correct.

In the case of Bitcoin, the database tracks the flow of every coin over time since the system was created. The transactions are grouped together in blocks that are processed about every ten minutes, and taken together, the chain of these blocks provides a history of the owner of every coin.

Bitcoin also includes an elaborate consensus protocol where anyone can compete to solve a mathematical puzzle and validate the next block on the chain. This ritual is often called “mining” because the person who solves this computational puzzle is rewarded with several coins. The protocol was designed to remove the need for central control by one trusted authority — an attractive feature for some coin owners. It is open and offers a relatively clear mechanism for resolving disputes.

Many ledger databases avoid this elaborate ritual. The cost of competing to solve these mathematical puzzles is quite high because of the energy that computers consume while they’re solving the puzzle. The architects of these systems just decide at the beginning who will be the authority to certify the changes. In other words, they choose the parties that will create the digital signatures that bless each addition without running some competition each step.

In the example from the car sales process, each of the three entities may choose to validate each other’s transactions. In some cases, the database vendor also acts as an authority in case there are any external questions.

The legacy players

Database vendors have been adding cryptographic algorithms to their products for some time. All of the major companies, like Oracle or Microsoft, offer mechanisms for encrypting the data to add security and offer privacy. The same toolkits include algorithms that can add digital signatures to each database row. In many cases, the features are included in the standard licenses, or can be added for very little cost.

The legacy companies are also adding explicit features that simplify the process. Oracle, for instance, added blockchain tables to version 21c of its database. They aren’t much different from regular tables, but they only support inserting rows. Each row is pushed through a hash function, and then the result from the previous row is added as a column to the next row that’s inserted. Deletions are tightly controlled.

The major databases also tend to have encryption toolkits that can be integrated to achieve much the same assurance. One approach with MySQL adds a digital signature to the rows. It is often possible to adapt an existing database and schema to become a ledger database by adding an extra field to each row. If the signature of the previous row is added to the new row, a chain of authentication can be created.

The upstarts

There are hundreds of startups exploring this space. Some are tech companies that are approaching the ledger database space like database developers. You could think of some others as accidental database creators.

It is a bit of a reach to include all of the various crypto currencies as ledger databases in this survey, but they are all managing distributed blockchains that store data. Some, like Ethereum, offer elaborate embedded processing that can create arbitrary digital contracts. Some of the people who are nominally buying a crypto coin as an asset are actually using the purchase to store data in the currency’s blockchain.

The problem for many users is that the cost of storing data depends on the cost of creating a transaction, and in most cases, these can be prohibitive for regular applications. It might make sense for special transactions that are small enough, rare enough, and important enough to need the extra assurance that comes from a public blockchain. For this reason, most of the current users tend to be speculators or people who want to hold the currency, not groups that need to store a constant volume of bits.

Amazon is offering the Quantum Ledger Database, a pay-as-you-go service with what the company calls an “SQL-like API”. All writes are cryptographically sealed with the SHA-256 hash function, allowing any auditor to go through the history to double-check the time of all events. The pricing is based upon the volume of data stored, the size of any indices built upon the data, and the amount that leaves. (It’s worth noting that the word “quantum” is just a brand name. It does not imply that a quantum computer is involved.)

The Hyperledger Fabric is a tool that creates a lightly interconnected version of the blockchain that can be run inside of an organization and shared with some trusted partners. It’s designed for scenarios where a few groups need to work together with data that isn’t shared openly. The code is an open source constellation of a number of different programs, which means that it’s not as easy to adopt as a single database. IBM is one company that’s offering commercial versions, and many of the core routines are open source.

Microsoft’s Blockchain service is more elaborate. It’s designed to support arbitrary digital contracts, not just store some bits. The company offers both a service to store the data and a full development platform for creating an architecture that captures your workflow. The contracts can be set up either for your internal teams or across multiple enterprises to bind companies in a consortium.

BigchainDB is built on the MongoDB NoSQL model. Any MongoDB query will work. The database will track the changes and share them with a network of nodes that will converge upon the correct value. The consensus-building algorithms can survive failed nodes and recover.

Is there anything a ledger can’t do?

Because it’s just a service for storing data, any bits that might be stored in a traditional database can be stored in a ledger database. The cost of updating the cryptographic record for each transaction, though, may not be worth it for many high-volume applications that don’t need the extra assurance. Adding the extra digital signature requires more computation. It’s not a significant hurdle for low-volume tables like a bank account where there may be only a few transactions per day. The need for accuracy and trust far outweigh the costs. But it could be prohibitive for something like a log file of high-volume activity that has little need for assurance. If some fraction of a social media chat application disappeared tomorrow, the world would survive.

The biggest question is just how important it will be to trust the historical record in the future. If there’s only a slim chance that someone might want to audit the transaction journal, then the extra cost of computing the signatures or the hash values may not be worth it.

This article is part of a series on enterprise database technology trends.

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Get ready! Top Dynamics 365 Trends Coming your Way in 2021

January 15, 2021   CRM News and Info

xget ready top dynamics 365 trends coming your way 2021 625x316.jpg.pagespeed.ic.Id 3PmwwB3 Get ready! Top Dynamics 365 Trends Coming your Way in 20212020. A year we will remember. A year that was not quite as we expected it to be – to say the least!  Still, the Earth keeps spinning, the software world keeps evolving, and you don’t want to fall behind. 

There are several Dynamics 365 trends out there and you should keep an eye on them. Why are they important? These trends will shape your professional landscape in 2021 and beyond, so insights into what to expect and where to invest your efforts can make a difference.

Let’s have a look at our top 6 and provide specific examples as we go along. That’s the best way to get to grips with the latest tech and understand what it means in a living, breathing business context.

What Are the Essential Dynamics Trends for 2021?

2021 has plenty of exciting innovations in store, many of which are just beginning to reveal their full potential. To keep your finger on the pulse, let’s get started and focus on the top tech trends for Microsoft Dynamics users in 2021:

  1. Use Blockchain to Prove a Document’s Authenticity
  2. AI, the Slow but Strong Trend
  3. Integrate with Microsoft Teams for Better User Adoption
  4. IIoT Meets Dynamics 365
  5. Guarantee Security for Software Integrations
  6. Beware of your Dynamics 365 Storage Options

Read on and make sure that you take the right turns as the new year unfolds!

Dynamics 365 Trends #1 – Use Blockchain to Prove a Document’s Authenticity

Exciting and futuristic, Blockchain has been a buzzword for some years now. Above all, people associate Blockchain with Bitcoin and other cryptocurrencies. As Blockchain use evolves, experts predict that it will become less about cryptocurrency and more about using it for a different aim: prove a document’s authenticity.

Did you even know you can use Blockchain technology’s security and distributed features to prove a document is untampered? Well, it turns out that you can, this is available on the market now. And the good thing about it is that your files and documents become trustworthy data. In other words, your files become a sound base for your company’s strategic business decisions. That makes all the difference. 

Stefano Tempesta, Microsoft Regional Director and advisor to Australia’s National Blockchain Roadmap, believes that “With blockchain, you can imagine a world in which every agreement, every process, every task, and every payment would have a digital record and signature that could be identified, validated, stored, and shared. Intermediaries like lawyers, brokers, and institutions like notaries might no longer be necessary. Individuals, organizations, and machines would freely transact and interact with one another with little friction.”. In an article on the future of Blockchain, he discusses possible uses of one such solution for SharePoint documents that is already out on the market and that can be easily integrated with Dynamics 365. We will certainly hear more about that during 2021.

Dynamics 365 Trends #2 – AI, the Slow but Strong Trend

AI has been a promising trend for 30 years or more now. Don’t you have the feeling we keep hearing AI is going to be the next big thing? As we enter 2021, I think it is time to realize AI is not a “big burst” type of trend. It is a continuously growing trend that goes into more and more areas of our daily lives. We currently see significant improvements in machine vision, natural language processing (NLP) and automated speech recognition (ASR). These will facilitate the structuring of unstructured data such as images or emails.

In the big world of Dynamics 365, we see AI coming into very distinct areas, from Dynamics 365 Fraud Protection to Dynamics 365 Virtual Agent for Customer Service. The area where we expect the most significant impact of AI will be in Dynamics 365 Customer Insights, with AI helping to define segments and predictive models.

Dynamics 365 Trends #3 – Integrate with Microsoft Teams for Better User Adoption

Not even Microsoft would have guessed Teams would reach 115 million daily active users like it did back in October 2020. Microsoft Teams has become ubiquitous, thanks in large part to need for remote work and remote events. 

This makes the integration with Microsoft Teams a plus for other products. Moreover, it is also a way to help drive other products’ user adoption. Within Microsoft 365 business you can see all Office apps fully links with Teams and that also happens with SharePoint. The level of integration for Dynamics 365 is not the same just yet, but the trend is for Dynamics 365 to be more and more integrated with Teams. Currently, you have the Dynamics 365 app available for Teams. Besides the normal use of the app within Teams, you can “chat” to get the D365 information you need from within Teams. You can also add a Dynamics 365 tab into a Microsoft Teams channel and access customer engagement app records there. This way, you and your team members can collaborate on one or multiple records (Accounts, Contacts, Opportunities, among others).

If you have custom applications that are important in your business daily routine, you can take this one step further and consider surfacing them in Teams. This is a new and evolved means of getting new users to use those custom applications, therefore driving user adoption. It might even help existing users get into the habit of using those same apps more.

Dynamics 365 trends #4 – IIoT meets Dynamics 365

Dynamics 365 offers organizations across different industries the ability to know their customers as well as their own organizations. The idea is always to enable predictive insights and, therefore, smarter decisions. 

Next on our big rundown of Dynamics trends for 2021 is the trend to enable this in manufacturing and industrial settings. How? By connecting Dynamics to shop floor information, leveraging data from machines and sensors. This gets the information to where the organization needs it – in 2021, we will be evolving from reactive decisions to proactive analytics that can support the decision process. 

Yes, this is definitely the most industry-specific trend on the list. Nonetheless, for this industry, this trend is a game-changer. By using Dynamics to make these analytics and insights accessible throughout an industrial organization, great things will happen.

There are many interesting use cases for combining IIoT with business software like Dynamics:

  • Go for predictive maintenance and prevent machine breakdowns by monitoring your machines’ condition and performance during regular operation and spotting early signs of the problem.
  • Implement remote monitoring and stay informed (real-time) by viewing the information you need with the appropriate detail level.
  • Improve production planning by having all the relevant information right where you need it, and you can finally make production planning more information-based and much more straightforward.

As you can see, IIoT meeting Dynamics covers a range of possibilities and concepts, giving it various use cases. As such, it’s one of the 2021 trends you can’t afford to ignore.

Dynamics 365 trend #5 – Guarantee Security for Software Integrations

The next trend in our rundown is security related. There is an increasing need to share data while maintaining privacy and security. That is NOT going to stop in 2021.

In our hyper-connected digital age, the trend for 2021 is to guarantee security when software integrations are involved. Truth be told, it is natural to assume that there is no danger in integrating two separate software pieces if you are already using them both. The only problem is that that assumption is wrong.

Let’s have a look at an example. Say you use Microsoft Dynamics 365 and Microsoft SharePoint. One day you discover that Microsoft provides an integration between the two. Cool! You can have the documents you previously had piled up in Dynamics automatically transferred to SharePoint but still readily accessible from Dynamics. It sounds like a brilliant idea!

You could very easily overlook the fact that the privileges for the documents that you had carefully set up in Dynamics are not going to be transferred to SharePoint. Everyone can see everything from the SharePoint side! Unknowingly, you would have created a security and privacy threat.

Luckily, the fact that there are more integrations than ever also means the solutions for these integration security problems are showing up – and this trend will be stronger throughout 2021.

For example, for the Dynamics and SharePoint integration problem above, you now have a solution. Moreover, you also have an add-on to that solution that ensures an automatic organization into folders of those documents on SharePoint.

Dynamics 365 trends #6 – Beware of your Dynamics 365 Storage Options

The last in our rundown of Dynamics trends for 2021 is storage. It was already common for Dynamics 365 admins to look for alternative storage for documents and attachments. The motivation for this was saving on costs and increasing performance. Alternative storage locations were frequently SharePoint or Azure Storage.

In 2021, we perceive that security is becoming one of the primary motivators for using alternative storage. As a result, we are already seeing new providers emerging in a market that felt consolidated up to now.

For example, in German-speaking countries, Dracoon is getting strong and will release the possibility of integrating with Dynamics 365 still in this quarter.

Takeaways

By embracing the prevailing trends in 2021 and using them to your advantage, you will accelerate your business’s growth in an ever-changing landscape.

You can hit the ground running as a new year unfolds!

Talk with Connecting Software’s experts if you want help putting these trends to practice in your organization. They will be more than happy to answer any questions you might have or jump on a quick call to show you how all this can work.

 Get ready! Top Dynamics 365 Trends Coming your Way in 2021

By Ana Neto

Software engineer since 1997, she is now a technical advisor for Connecting Software.

Connecting Software is a producer of integration and synchronization software solutions since 2004. We operate globally and we are also a proud “Top Member 2019” at CRMSoftwareBlog.

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Visualize 5 Cool Insights on Holiday Tree Trends Over Time

December 31, 2020   TIBCO Spotfire
TIBCOSpotfire ChristmasTree scaled e1608573759606 696x365 Visualize 5 Cool Insights on Holiday Tree Trends Over Time

Reading Time: 3 minutes

Did you know Thomas Edison’s assistants proposed putting electric lights on Christmas trees? There’s a long and rich history surrounding holiday trees, in America and around the world. According to the History Channel, symbolic traditions involving evergreen trees in winter began in ancient Egypt and Rome and continue to take on new meaning today. 

New Holiday Traditions: Annual Analytics

Here at TIBCO, we’ve started our own holiday tradition involving the classic festive trees: using our data visualization software to understand trends in holiday tree data. Last year, we shared our analysis and “treemap” visualization (quite literally a treemap of trees) via TIBCO Spotfire®. This year, we dived even deeper into the data, using the new Spotfire Mods functionality to design custom apps for greater interactivity. Here’s what we found:

  • Top Tree Producing States: All 50 states contribute to the holiday tree industry, but our analysis shows the greatest production occurs in Oregon, North Carolina, Michigan, and Pennsylvania. Also interesting is that while Oregon and North Carolina are top producers overall, states like Ohio and Michigan definitely over-index for total tree producing counties as a percentage of their total land area. 
 Visualize 5 Cool Insights on Holiday Tree Trends Over Time
Immersive, interactive exploration of a bubble “tree-map” visualization Mod alongside county-level Spotfire geoanalytics  [*source: USDA census data]    
  • Artificial vs. Real Tree Sales: As you can see below, artificial tree sales have been on the rise over the last decade, with 162 percent growth between 2004 and 2018. Artificial trees are taking over. Actually, 81 percent of the trees on display, whether in storefronts, businesses, or homes, in 2019 were of the artificial variety. But what does that mean for the global economy when China produces 80 percent of artificial trees worldwide and given that artificial trees cannot be recycled like real trees?
 Visualize 5 Cool Insights on Holiday Tree Trends Over Time
Tree sales volume over time in this area chart visualization Mod in Spotfire [*source: National Christmas Tree Association] 
  • Rising Average Price of Real Trees: According to an article in the Hustle, “During the recession in 2008, ailing farmers planted too few trees. As a result, prices have been much higher since 2016.” The article also cites the National Christmas Tree Association as stating that the average retail price for a real tree in 2019 was $ 75. Obviously, this is a huge market, but one that continues to shift with economic and social changes—which makes us wonder just how different our analysis next year will look.
  • Consumer Demand Lower in 2019: In the area chart visualization above, we see that sales for natural trees still account for a larger share of the market. However, the artificial tree category set new high marks for sales in each year progressively from 2016 to 2018. Why could this be? One hypothesis might be that as Baby Boomers retire as “empty-nesters” and downsize their homes, they are buying fewer trees, but let us know your thoughts on this surprising find. 
  • The More the Merrier? Multiple Trees: According to a survey by the American Christmas Tree Association, the number of households in the United States that display more than one Christmas tree has grown by 10 percent from 2014 to 2019. In 2019, approximately 16 percent of American households display multiple trees. But will this trend continue or, as with the overall tree sales, will the number of trees per household decrease in the coming years?

We’ve started our own holiday tradition involving the classic festive trees: using our data visualization software to understand trends in holiday tree data. Click To Tweet

A New Tradition: Immersive Yourself in Custom Analytics Applications 

But this is just one festive story you could tell around data trends. What about shopping trends this year, will there be an increase in small business online sales? What will be the top gifted items in 2020? 
You tell us! Join our tradition, and read our whitepaper to learn how the immersive qualities of Hyperconverged Analytics will create new value for your business. For a closer look at all of “What’s New in Spotfire®” including visualization Mods, watch our 20-minute intro webinar on demand. 

Previous article20 for 2020: Looking Back on a Year of Blogging

Shannon Peifer is a Marketing Content Specialist at TIBCO Software in Denver, CO. She graduated from the University of Texas at Austin in 2018 with a double major in marketing and English honors, and loves writing engaging content related to technology. Shannon grew up overseas, and loves to explore new places. When she’s not writing, you can find her swimming laps at the pool, gulping down iced lattes at local coffee shops, or scouring the shelves at the bookstore.

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9 trends in enterprise database technology

December 30, 2020   Big Data
 9 trends in enterprise database technology

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The database has always revolved around rock-solid reliability. Data goes in and then comes out in exactly the same way. Occasionally, the bits will be cleaned up and normalized so all of the dates are in the same format and the text is in the same character set, but other than that, nothing should be different.

That consistency is what makes the database essential for any enterprise — allowing it to conduct things like ecommerce transactions. It’s also why the database remains distinct from the data warehouse, another technology that is expanding its mission for slower-twitch things like analysis. The database acts as the undeniable record of the enterprise, the single source of truth.

Now databases are changing. Their focus is shifting and they’re accepting more responsibilities and offering smarter answers. In short, they’re expanding and taking over more and more of the stack.

Many of us might not notice because we’ve been running the same database for years without a change. Why mess with something that works? But as new options and features come along, it makes sense to rethink the architectures of data flows and take advantage of all the new options. Yes, the data will still be returned exactly as expected, but it will be kept safer and presented in a way that’s easier to use.

Many drivers of the change are startups built around a revolutionary new product, like multi-cloud scaling or blockchain assurance. For each new approach to storing information, there are usually several well-funded startups competing to dominate the space and often several others still in stealth mode.

The major companies are often not far behind. While it can take more time to add features to existing products, the big companies are finding ways to expand, sometimes by revising old offerings or by creating new ones in their own skunkworks. Amazon, for instance, is the master at rolling out new ways to store data. Its cloud has at least 11 different products called databases, and that doesn’t include the flat file options.

The other major cloud providers aren’t far behind. Microsoft has migrated its steadfast SQL Server to Azure and found ways to offer a half-dozen open source competitors, like MySQL. Google delivers both managed versions of relational databases and large distributed and replicated versions of NoSQL key/value pairs.

The old standards are also adding new features that often deliver much of the same promise as the startups while continuing support of older versions. Oracle, for instance, has been offering cloud versions of its database while adding new query formats (JSON) and better performance to handle the endless flood of incoming data.

IBM is also moving dB2 to the cloud while adding new features like integration with artificial intelligence algorithms that analyze the data. It’s also supporting the major open source relational databases while building out a hybrid version that merges Oracle compatibility with the PostgreSQL engine.

Among the myriad changes to old database standards and new emerging players, here (in no particular order) are nine key ways databases are being reborn.

1. Better query language

SQL may continue to do the heavy lifting around the world. But newer options for querying — like GraphQL — are making it easier for front-end developers to find the data they need to present to the user and receive it in a format that can be dropped right into the user interface.

GraphQL follows the standard JavaScript format for serializing objects, making it easier for middle- and front-end code to parse it. It also hides some of the complexity of JOINs, making it simpler for end users to grab just the data they need. Developers are already adding tools like Apollo Studio, an IDE for exploring queries, or Hasura, an open source front-end that wraps GraphQL around legacy databases like PostgreSQL.

2. Streaming databases follow vast flows

The model for a standard database is a big ledger, much like the ones clerks would maintain in fat bound books. Streaming databases like ksqlDB are built to watch an endless stream of data events and answer questions about them. Instead of imagining that the data is a permanent table, the streaming database embraces the endlessly changing possibilities as data flows through them.

3. Time-series database

Most database columns have special formats for tracking date stamps. Time-series databases like InfluxDB or Prometheus do more than just store the time. They track and index the data for fast queries, like how many times a user logged in between January 15 and March 12. These are often special cases of streaming databases where the data in the streams is being tracked and indexed for changes over time.

4. Homomorphic encryption

Cryptographers were once happy to lock up data in a safe. Now some are developing a technique called homomorphic encryption to make decisions and answer queries on encrypted data without actually decrypting it, a feature that vastly simplifies cloud security and data sharing. This allows computers and data analysts to work with data without knowing what’s in it. The methods are far from comprehensive, but companies like IBM are already delivering toolkits that can answer some useful database queries.

5. In-memory database

The original goal of a database was to organize data so it could be available in the future, even when electricity is removed. The trouble is that sometimes even storing the data to persistent disks takes too much time, and it may not be worth the effort. Some applications can survive the occasional loss of data (would the world end if some social media snark disappeared?), and fast performance is more important than disaster recovery. So in-memory databases like Amazon’s ElasticCache are designed for applications that are willing to trade permanence for lightning-fast response times.

6. Microservice engines

Developers have traditionally built their code as a separate layer that lives outside the database itself, and this code treats the database as a black box. But some are noticing that the databases are so feature-rich they can act as microservice engines on their own. PostgreSQL, for instance, now allows embedded procedures to commit full transactions and initiate new ones before spitting out answers in JSON. Developers are recognizing that the embedded code that has been part of databases like Oracle for years may be just enough to build many of the microservices imagined by today’s architects.

Jupyter notebooks started out as a way for data scientists to bundle their answers with the Python code that produced it. Then data scientists started integrating the data access with the notebooks, which meant going where the information was stored: the database. Today, SQL is easy to integrate, and users are becoming comfortable using the notebooks to access the database and generate smart reports that integrate with data science (Julia or R) and machine learning tools. The newer Jupyter Lab interface is turning the classic notebook into a full-service IDE, complete with extensions that pull data directly from SQL databases.

7. Graph databases

The network of connections between people or things is one of the dominant data types on the internet, so it’s no surprise that databases are evolving to make it easier to store and analyze these relationships.

Neo4j now offers a visualization tool (Bloom) and a collection of data science functions for developing complex reports about the network. GraphDB is focusing on developing “semantic graphs” that use natural language to capture linguistic structures for big analytic projects. TerminusDB is aimed at creating knowledge graphs with a versioning system much like Git. All of them bring efficiency to storing a complex set of relationships that don’t fit neatly into standard tables.

8. Merging data storage with transport

Databases were once hidden repositories to keep data safe in the back office. Delivering this information to the user was the job of other code. Now, databases like Firebase treat the user’s phone or laptop as just another location for replicating data.

Databases like FaunaDB are baking replication into the stack, thus saving the DBA from moving the bits. Now, developers don’t need to think about getting information to the user. They can just read and write from the local data store and assume the database will handle the grubby details of marshaling the bytes across the network while keeping them consistent.

9. Data everywhere

A few years ago, all the major browsers began supporting the Local Storage and Indexed Storage APIs, making it easier for web applications to store significant amounts of data on the client’s machine. The early implementations limited the data to 5MB, but some have bumped the limits to 10MB. The response time is much faster, and it will also work even when the internet connection is down. The database is not just running on one box in your datacenter, but in every client machine running your code.

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Anti-Predictions: 8 Future-proof Analytics Trends for 2021 and Beyond

December 12, 2020   TIBCO Spotfire
predictions scaled e1607100229271 696x365 Anti Predictions: 8 Future proof Analytics Trends for 2021 and Beyond

Reading Time: 3 minutes

This is not one of those “crystal ball” new year prediction blogs. In the wake of a most unpredictable year full of black swan events, now is the time for data scientists and business analysts to humbly take the hard-learned lessons of 2020 and move forward. 

So, rather than chase buzzword mysticism of sage prognostication, let us default back to a tried-and-true model for charting a future-proof course forward: industry research trends. 

The Eight Trends That Will Matter Most

Professional research fields often seek validation of directional trends with a minimum of three data points. It’s the magic number, and the basis for establishing the beginning of a true “pattern.” As such, the following is an index of these rolled up trends as themes which echoed persistently from industry analysts as top analytics trends for 2021. And check out companies that are ahead of the curve in each category and next steps for your business! 

Intelligent, adaptable business…

Very complex global market conditions will demand more shifts and pivots again in 2021, and organizations will need to be lean and agile enough to respond in real time. If 2020 taught us anything: in business climates with rapidly changing global market conditions, decisions must be data-informed, but perhaps most importantly, nimble enough to adapt to both risk as well as new opportunity as they develop—on much shorter frequencies and turnaround.  

Ahead of the curve: CargoSmart. WATCH 

More AI-driven automation in the workplace… 

With as many as one in every four remote workers supported by new forms of automation (Robotic Process Automation (RPA), etc.), more artificial intelligence (AI) Proof-of-Concept projects will continue to roll off the line and progress into production environments. While there will be more automation in decision environments, humans will remain a vital cog in the decision-making process. 

Ahead of the curve: Bayer Crop Science innovating with image analysis and more. READ 

Growth on The Edge… 

Computing continues to get closer to where data is actually generated. As a result, real-time analysis of those edge events is being built into models sooner—when and where decision makers need it. With the explosion of sensors and connected smart devices, ever-increasing Internet of Things (IoT) data exhaust will be the fuel for optimization loops to predict and improve future performance. 

Ahead of the curve: Siemens Mobility. WATCH   

Trust and ethics: more accountable AI…

Trust will remain the top spot reason why executive decision makers don’t believe AI-recommendation systems. While 94 percent of leaders who’ve adopted AI trust their data, only 64 percent of those trust it to be reliable enough for business change. Further operationalization of “responsible AI” will be underpinned by the growing discussion of digital ethics and bias.  

Next step: For more, read APEX of Innovation blog on AI. 

Closed-loop decision models…

Businesses will need to leverage learnings and harness collective knowledge as a shared asset in 2021. Using closed-loop decision models to accomplish this, organizations can accelerate knowledge sharing and develop pipelines to support learning. 

Ahead of the curve: Mercedes-AMG Petronas F1’s industrial optimization model. READ 

Convergence of analytics technology continues…  

Whether machine learning, data management, or governance, these formerly discrete market categories will continue to intersect. This new, tightly-integrated approach, what we call Hyperconverged Analytics, brings together visual analytics, data science, and streaming capabilities together in a seamless experience, delivering immersive, smart, and real-time business insights.

Ahead of the curve: WATCH how AA Ireland uses the Hyperconverged Analytics solution for real-time pricing. 

Interactive discovery is now table stakes…

With Natural Language Query (NLQ) and similar capabilities making great strides, these features and functionality have now become commoditized and are no longer differentiating in the market. “Analytics culture” will remain a top barrier to full realization and adoption of augmented intelligence. 

Next step: For more, read about Interactive AI in TIBCO Spotfire®.  

More momentum in network graph analytics…

Interest in graph and network analysis will continue to grow in future years. Organizations seeking connections across datasets will implement network graph analytics to identify the most valuable relationships and explore unknowns.  

Next step: How Hyperconverged Analytics is enabling immersive, smarter network analysis. READ  

With rapidly changing global market conditions, decisions must be data-informed, but perhaps most importantly, nimble enough to adapt to both risk as well as new opportunity as they develop—on much shorter frequencies and turnaround.  Click To Tweet

For more top analytics landscape trends, watch our webinar with Doug Henschen of Constellation Research: Analytics in 2021: Move from Insight to Predictions and Real-time Action.

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Fear! Excitement! Trends disrupting your career in the 2020s!

December 3, 2020   Tableau
shutterstock 174475871 Fear! Excitement! Trends disrupting your career in the 2020s!

Do you feel left behind? If you are witnessing today’s unprecedented speed of technological change, a sense of apprehension would not be surprising.

In a hyperspeed environment, individuals cannot gain expertise quickly enough. By the time you learn and master a topic, that expertise already seems obsolete. From a corporate perspective, a lack of technology talent pushes companies toward other options, one of which is automation to reduce reliance upon human workers.

Our current automation trend will eliminate a large chunk of today’s jobs. However, that same disruption causes many more opportunities to emerge for the right individuals. Do not be careless and allow your career to be destroyed in the 2020s. Be aware of technology trends, prepare, and pivot to a new place of success.

Here are five areas you should watch in the next few years.

CLOUD

Motivated by competitive and cost-saving reasons, companies are migrating on-premise applications and data onto cloud platforms such as Amazon Web Services, Microsoft Azure, and Google Cloud. Companies benefit by eliminating the significant overhead private data centers, hardware, and support services. Plus, they gain market agility by being able to scale digital assets almost immediately.

Companies will eliminate the jobs associated with legacy, on-premise support. With talent at a premium, companies may retrain these individuals for other roles, but the cold reality is most management might instead eliminate long-time legacy employees and replace them with new talent.

Software vendors will reduce costs by moving to cloud-only solutions, eliminating the need to install and support on-premise applications. Field technical staff who performed these roles will no longer be needed; only a smaller core group for the centralized cloud support will remain.

AUTOMATION

Companies will continue automation, combining software with artificial intelligence and machine learning, to reduce costs, gain competitive advantages, and increase revenue. With smart automation, firms will replace many individuals who perform repeatable tasks in controlled environments. It’s a simple decision: automated work can be performed 24×7 without stoppage and at lower costs than humans.

Vendors will provide automated tools to accelerate the movement from on-premise applications to the cloud platforms. During the next few years, you will see a mad rush to push business applications onto cloud platforms.

NEW COMPETITORS

New endeavors with new technology will emerge and disrupt legacy businesses. One advantage is they do not have the baggage of legacy platforms, bureaucracy, and long-time employees. These nimble barbarians will attack the fortresses of established empires, speeding the decline of well-known companies.

DISPOSABLE TECHNOLOGY

Rapid technological improvements mean that older technology needs to be thrown away sooner. Ongoing changes, new competition, along with lack of talent pushes companies to speed their elimination of legacy applications and old ways of doing business.

When everything becomes a paid cloud service, companies need fewer technical support employees. However, individuals who can train others in emerging technology will be important. Because modern tools change quickly these tech trainers must quickly pivot and learn. Instead of working for one company, these individuals may provide global online services, generating both active and passive income. To meet demand, online courses and certifications will grow.

CELEBRITY TALENT

While automation will eliminate many legacy jobs, rapidly changing technologies and lack of resources will provide a Wild West goldrush for savvy individuals in the 2020s. Some will become solopreneurs with a strong social media presence, causing firms to find a new HR model, other than their legacy comand-and-control methods designed to restrict employee behaviors.

Instead of dependency upon full-time employees, companies will leverage project-based, remote talent who can be shuffled in and out as needed. Firms will need to develop the culture and skills for working with free agents. A corporate initiative will begin to resemble the effort of producing a blockbuster movie using contracted talent during development.

As a result of a smaller talent base, corporate work conditions will change. Work-from-home will gain even more acceptance and individuals will not need to live within an hour commute of a downtown office building. Instead, technology will be securely available from cloud platforms and workers will spread out, with less clustering in mega-urban centers. Headquarters will become occasional convention sites for talent community-building, celebration, and edification events.

Depending on your worldview, the technology trends of the 2020s are either fear-inducing dangers or exciting opportunities. Make sure you wield this double-edge sword properly. Contact me at Doug@kencura.com.

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Five Technology Trends in Capital Markets

November 19, 2020   Microsoft Dynamics CRM

From an industry perspective, it’s all too common to lump all things money-related into a single pool and call it FSI – or the Financial Services industry. But those working in this channel know all too well about the myriad differences – from subtle to substantial – between, say, banking and insurance, or between capital markets and credit cards. Yes, they all deal with money…

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