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Is Your Business Ready for the New Generation of Analytics?

January 25, 2021 TIBCO Spotfire

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New year, new generation of analytics. The last year brought a lot of changes, including shifts within the analytics landscape to bring together capabilities that support agility and speed in decision making. This year, prepare your business for any unexpected changes and “bake in” agility and resiliency with real-time analytics.

Is your organization ready to meet the growing demand for robust, fast, and flexible analytics?

In an upcoming webinar with TIBCO, “Readying Enterprises for the New Generation of Analytics,” Dan Vesset of IDC will share recent research on what businesses need from their analytics teams and applications to support this new area of growth.

Among the findings to be discussed are:

At least 70% of managers and directors surveyed said their executives need their enterprises to become more data driven
49% of organizations surveyed say that they are very or substantially challenged by their inability to synthesize data into actionable information
More than half of the organizations surveyed planned to spend more on Big Data and Analytics, regardless of their stage in IDC’s Recovery Phase mapping.

During this 45-minute webinar, Vesset will engage in a discussion with TIBCO’s Director of Product Marketing, Lori Witzel, conduct a deep dive into next-generation analytics architectures, and provide directional guidance for organizations looking towards improved decision making through analytics.

Move from Crisis to Recovery with Hyperconverged Analytics

Through an integrated approach to powerful visual analytics, embedded data science, and seamless streaming analytics, TIBCO Spotfire^® enables modern analytics architectures across a variety of use cases and industries. This new modern approach—hyperconverged analytics—supports data exploration, data management, and AI-driven decision automation for improved business outcomes.

Through an integrated approach to powerful visual analytics, embedded data science, and seamless streaming analytics, TIBCO Spotfire enables modern analytics architectures across a variety of use cases and industries. Click To Tweet

To ensure that your business benefits from this new generation of hyperconverged analytics, register for the webinar now. And for more findings and expert advice, download the full IDC report.

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TIBCO4Good and She Loves Data Offer Free Data Skills Workshops During a Time of Vulnerability

January 20, 2021 TIBCO Spotfire

Reading Time: 2 minutes

New to designing meaningful, interactive data visualizations and dashboards? Want to learn how to better understand and prepare your data? Then TIBCO4Good^™’s recently launched “Back on Your Feet” program is for you. Built in partnership with Singapore Management University (SMU) and She Loves Data, this global program can help you up your data visualization and dashboard building skills and stay competitive in today’s professional job market.

Back on Your Feet Program: Empowering Individuals Impacted by the Pandemic

The “Back on Your Feet” program was designed specifically to help educate individuals affected by the global COVID-19 pandemic. It offers a series of workshops and training sessions to empower individuals who may have lost their jobs due to the pandemic and want to increase their competitiveness in an increasingly tough marketplace.

SMU, a premier university in Asia, internationally recognized for its research and distinguished teaching, has developed the course content, including discussions on how to design, develop, and deploy analytic dashboards. “The pandemic has upended the lives and livelihoods of many around the world. As an engaged city university with a strong suite of expertise in computing research and education, the School of Computing and Information Systems is keen to contribute to this meaningful program by TIBCO through our partnership with She Loves Data to upskill and re-skill individuals impacted by the economic malaise, thereby creating a positive impact on the community in Singapore and beyond,” said Professor Pang Hwee Hwa, Dean of SMU School of Computing and Information Systems.

TIBCO4Good and She Loves Data Offer Free Data Skills Workshops During a Time of Vulnerability — From left to right: Nina Conseil, Global Certification Programs at She Loves Data, Bernard Tay and Justin Choy are Teaching Assistants and Rafael J. Barros is Senior Lecturer at the School of Computing and Information Systems, Singapore Management University

Program Benefits and Session Structure

Upon completion of the workshops, participants are certified as dashboard and forecasting specialists and receive a free TIBCO Spotfire^® license for a year. The program began in APJ in November and December 2020, will extend to the U.S. in early 2021, followed closely by EMEA.

Here’s a quick overview of the program structure:

Module 1: Dashboard exploration as an end user; Marking and filtering concepts
Module 2: Asking the right questions by understanding what data is important; Foundations of charts and basic visualizations
Module 3: Basics in data cleaning, advanced visualizations, and connecting to multiple data sources
Module 4: Designing the dashboard for end-user consumption

Your Chance to Up Your Dashboarding Skills

Join us for the second edition of a series of four training modules designed to help you become a dashboard specialist. In the first session, 230 attendees participated actively in the program. Register now for the next event on February 20th!
And to learn more about other TIBCO4Good initiatives helping communities around the world, head to www.tibco.com/tibco4good.

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“Without Data, Nothing” — Building Apps That Last With Data

January 20, 2021 Sisense

Every company is becoming a data company. Data-Powered Apps delves into how product teams are infusing insights into applications and services to build products that will delight users and stand the test of time.

In philosophy, a “sine qua non” is something without which the phenomenon under consideration cannot exist. For modern apps, that “something” is data and analytics. No matter what a company does, a brilliant app concept alone is insufficient. You have to deftly integrate data and analytics into your product to succeed.

Whatever your audience, your users are getting more and more used to seeing data and analytics infused throughout apps, products, and services of all kinds. We’ll dig into ways companies can use data and analytics to succeed in the modern app marketplace and look at some now-extinct players that might have thrived with the right data in their platforms.

data analytics successful apps blog cta banner 770x250 1 “Without Data, Nothing” — Building Apps That Last With Data

Sentiment analysis in customer messages

Yik Yak was an anonymous chat app that looked promising initially but failed because of problems that could have been resolved with data and analytics. What made Yik Yak popular was the exotic feature that enabled members to chat anonymously with others in the same geographic vicinity. Unfortunately, that feature was also the cause of the app’s demise: Yik Yak capitalized as a startup with about $ 75 million and grew to a value of $ 400 million before uncontrolled cyberbullying ruined its reputation. After Yik Yak’s name was spoiled as a result of abusive chat, the company could not sell ads on its platform, meaning it could no longer monetize its innovative concept.

How could Yik Yak have used data and analytics to avert disaster? Luma Health showed how message data can be analyzed for mood and meaning by using AI/ML methods on a data lake of chat messages. Yik Yak could have tagged message content with the originating IP address and then quickly blocked messages from that IP after abusive language was detected. This hindsight can now become foresight for other enterprising companies.

The benefits of leveraging collective data

Color Labs was another successful startup whose failure could have been avoided with the right analytics. Although the company’s investment in AI and convolutional neural networks (CNNs) may have been significant, in retrospect, an innovative use of these technologies on the right data could have given it a better shot at survival. The basic service model behind Color Labs’ app was that users would share images and then see images from other users who were posting pictures in the same vicinity (a media-based counterpart to Yik Yak’s concept). The app failed in part for reasons that new dating apps often fail: Needing to go live with a million users on day one! Color Labs’ users joined up only to find little or nothing posted in their vicinity, giving them little incentive to post and share. and leaving them feeling alone in an empty room. The company ultimately folded.

How could data insights have solved this problem for Color Labs? Leveraging the right collective datasets with CNNs could have identified images tagged to a geographical place already freely shared on the internet. Those images could be used to populate the app and get the user engagement ball rolling. Using CNNs in that way is expensive but justifiable if it means keeping the company afloat long enough to reach profitability. New dating app startups actually use a similar trick — purchasing a database of names and pictures and then filling in the blanks to create an artificial set of matches to temporarily satisfy new subscribers’ cravings for instant gratification (one such database is marketed as “50,000 profiles.”) The gamble is that new subscribers will remain hopeful long enough for a number of subscribers to join up and validate their existence. Color Labs could have benefited from existing media with a much lower cost in terms of ethical compromise as well.

Forecasting and modeling business costs

Shyp was an ingenious service app that failed for a number of reasons, but one of those reasons could have been fixed easily with data insights. The basic innovation of Shyp was to package an item for you and then ship it using a standard service like FedEx. The company’s shortcut, which turned out to be a business model error, was to charge a fixed rate of $ 5 for packaging. Whether the item to ship was a mountain bike or a keychain, the flat rate of $ 5 for packaging was a hole in Shyp’s hull, one that sank the company in short order.

Shyp’s mistake could have been resolved cleverly by using the wealth of existing data about object volume, weight, fragility, temperature sensitivity, and other factors to create an intelligent packaging price calculator. Such a database could even have included local variations in the price of packing materials such as foam peanuts, tape, boxes, and bubble wrap, and have presented the calculation at time of payment. Flat fees are attractive and can be used as loss leaders when trying to gather new customers or differentiate oneself in a crowded market, but if you aren’t Amazon, then you need to square the circle somehow. A data-driven algorithm for shipping prices (or whatever your service is) doesn’t just make good business sense — it can even be a selling point!

Social vs. personal networks: Sentiment analysis in data

“Path” fashioned itself an anti-Facebook: According to its founder, former Facebook developer Dave Morin, Path was a “personal network,” not a social network, where people could share “the story of their lives with their closest friends and family.” And for a moment it almost looked like Path might allow people to do just that. The startup boasted a whopping $ 500 million value with steadfast investor confidence that lasted all the way until it faded into obscurity, ultimately being purchased by a Korean tech firm and then removed from app stores. Path intended to enforce its mission to provide personal networks of true friends by limiting each user’s friend count to 50. The friend limit was perceived as detrimental to Path’s success at a time when Facebook users often had thousands of friends, but this alone did not account for the apparent irrelevance of the novel app. What was the missing piece? Data analysis.

Path could have sustained itself as a stalwart alternative to Facebook users disenchanted with the endless mill of likes and heart emojis. The key would have lain in sentiment analysis of user message content: By using natural language processing methods to distinguish close friends from distant acquaintances, Path could have offered its users an innovative platform for knowing who their “real friends” were.

Data analytics and the competitive future

We have seen that startup apps based on ingenious concepts and with funding levels over $ 100 million failed for a variety of reasons that could have been ameliorated or averted with savvy, transformative uses of data, analytics, and insights. One of the original e-hailing taxi companies failed for no other reason than the founding designers’ lack of awareness that Yellow cab drivers in New York at that time did not carry mobile phones!

Data is not only useful for calculating and forecasting the future, it’s a must-have for your app. Every company with a novel concept to unleash into the market must face the reality, as these companies did, that a good idea alone won’t guarantee an app’s success. Innovative use of data in concert with that idea is something that no modern app can survive without.

“Without Data, Nothing” — Building Apps That Last With Data

Jack Cieslak is a 10-year veteran of the tech world. He’s written for Amazon, CB Insights, and others, on topics ranging from ecommerce and VC investments to crazy product launches and top-secret startup projects.

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The Missing Link: Blockchain for Digital Supply Chains

January 18, 2021 TIBCO Spotfire

Reading Time: 4 minutes

A new operational backbone: the digital supply chain

As our business frameworks and structures have evolved to become predominantly data-driven digital entities, a new electronic backbone of partners, suppliers, and industry associates has crystallized and become the new substrate for all operational functions. That new foundational fabric has a name; we call it the digital supply chain.

Composed of logically aligned collections of people, processes, products, and places, the digital supply chain also includes new artificial intelligence and machine learning (AI/ML) functions for predictive intelligence and a number of virtual “employees” in the form of digital twins. Where we used to define digital twins solely in the context of machines in the Internet of Things (IoT), we can now establish digital versions of human workflow procedures, entire teams, complete departments, and whole companies.

The foundational fabric: blockchain

But as digital twins are employed, deployed, and (mostly) enjoyed as valuable members of the new digital supply chain, we must think about a system of control to ensure that we know what functions they are performing and the results of their simulation calculations. That foundational fabric also has a name and you’ve already heard of it; we call it blockchain.

Using blockchain allows us to track and support a live, parallel digital twin deployment. Blockchain may be utilized to store key milestones or states in the lifecycle of a digital twin, and be augmented with a high-speed cache or state store to facilitate access to live, rapidly-changing operational data that doesn’t fit into blockchain storage structures.

With data potentially cryptographically linked to the blockchain distributed ledger, this additional event-driven state store typically captures the current or real-time status of the digital twin (e.g. as a passenger is checked into their flight or as a shipment is loaded on a truck) and any uncorrelated events or transactions. It may also be queried by external tools to obtain the latest image or snapshot of the digital twin. As digital twins expire or become stale, data is typically flushed from this state store and moved to other analytical stores or data lakes, forming the basis for a complete, end-to-end contextual view of the twin.

A decentralized tamper-resistant store

Blockchains store data in a tamper-resistant, distributed, and “append-only” storage layer that is cryptographically derived and shared. Adding transactions to this ledger typically involves reaching agreement on the validity of the transaction between multiple blockchain network participants. In concept, if not practice, members of a digital supply chain should be able to agree on the validity of transactions in a relatively fluid manner. The cryptographic “chaining” of the data makes it difficult to change the transaction once it has been added to the ledger.

Without providing a re-analysis of how blockchain has evolved and how both public permissionless and private permissioned blockchains are implemented (there is plenty to read on this across the web), let’s look at the use of permissioned enterprise blockchains with regard to digital twins in the supply chain.

For digital twins that span multiple organizations, data or transactions must be shared in a trusted, secure fashion between multiple known parties, have a degree of needed business logic transparency, and have a shared, decentralized, tamper-resistant store. To meet these needs, blockchain can act as an additional layer to a parallel or multiple digital twin deployment. A tamper-resistant store is key, especially in environments where mission-critical or life-critical operations depend upon it—like many digital twin supply chain functions.

This type of functionality can be useful when deploying digital twins that need to securely store and share key states or checkpoints between multiple parties (e.g. product delivery milestones across a supply chain), meet regulatory compliance requirements, reduce the chances of fraud, or record key decisions being made by various actors, including AI/ML models, in a complex system.

Smart transactions, smart contracts

There’s a lot of talk surrounding digital business and arguably too much generic showboating surrounding the development of so-called digital transformation initiatives. Putting some meat on the bones of these new platform advancements requires us to define exactly where we will be deploying new software code. In the context of this discussion, that deployment surface is smart contracts, i.e. the business logic or code that runs within a blockchain network to define the parameters and logic of the transactions that can take place.

There are many definitions and descriptions of smart contracts and each blockchain framework that supports this capability tends to implement it differently. As applications in their own right, smart contracts are used to automate the execution of business logic against transactions, validate that a transaction should be written to the ledger, and write to the ledger in a way that supports transparency and trust. Again, for digital twins that are operating in parallel to distributed or complex systems, the ability to distribute business logic in a transparent and secure manner can prove beneficial.

Benefits of blockchain for supply chain management

We’ve moved beyond what we used to call Business-to-Business (B2B) operations at this point and entered a space where digital twins are transacting with each other autonomously and automatically inside the digital supply chain. Of course, the trade off of moving to this new tier is additional complexity. So, this consideration must be weighed against the obtained benefits in any firm’s own personal cost-benefit analysis.

The ability of blockchain to track digital twins with a high degree of transparency and traceability can also help with future legal requirements, especially when it comes to the import of raw materials. As an example from several years ago, the U.S. obliged its publicly listed companies to fully document their supply chain for tantalum, tungsten and tin, related ores, and gold. Soon afterward, the Organisation for Economic Co-operation and Development (OECD) issued guidelines on the due diligence of companies with regard to supply chains of minerals from conflict and high-risk areas.

Prepare for the future of blockchain with digital twins

Future considerations for the use of blockchain with digital twins include the creation of common marketplaces and representing shared assets as tokens for fractional ownership and sharing purposes. As digital twins become more complex and as network complexities increase, it is possible that blockchain will (in some form) become a more prevalent component of a digital twin runtime architecture.

Blockchain-backed digital twins can be complex to develop and execute, but the right tools make it far easier. Read this paper to learn more about use cases and applications for digital twins, key technology foundations, blockchain as an enabler, and more.

There’s arguably too much generic showboating surrounding the development of so-called digital transformation initiatives. Putting some meat on the bones of these advancements requires us to define exactly where we will be deploying new code. Click To Tweet

And join me for the TIBCO LABS Quarterly Update on February 4th 10:00 AM PST to discuss how organizations can apply capabilities related to IoT, edge analytics, blockchain, process mining, augmented reality, and more to meet business needs.

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6 Strategies for Achieving Your Business Goals in the New Year

January 15, 2021 TIBCO Spotfire

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Happy New Year! 2021 has officially arrived and we’re sure that you’re already chasing down your goals for the new year, ready to face whatever challenges you might meet along the way. In this month’s TIBCO tips blog, we’re highlighting different ways to help you to work towards achieving your 2021 business goals.

Data Governance: How to Move from Strategy Into Practice

Many organizations are realizing that to drive business value with data, they need to understand the context of the data and its master lineage. They need efficient data governance with robust metadata management—which isn’t a simple ask. Learn about the art of technology for data governance and gain insights into how metadata technologies can support your organization’s strategies and data governance program success in this webinar.

Team with TIBCO Webinar: Washington University in St. Louis School of Medicine

Staff Scientist Jack Bramley of Washington University in St. Louis School of Medicine joined the Team with TIBCO webinar series. He discussed how the school is using TIBCO Spotfireand TIBCO Data Science software in its genomic screening platform to fight neurodegenerative diseases. Watch this fascinating session to learn how you can manage complex datasets and uncover insights to drive innovation.

TIBCO Data Virtualization Named a Leader by GigaOm

As the demand and complexity of data continue to grow, companies need a solution to manage all of their data across the organization. That’s where data virtualization comes in, bringing together your diverse, disparate data sources in one place for easy access and control. The recent GigaOm Radar report provides an expert evaluation of top vendors and predicts market movement in the data virtualization space. Learn more about TIBCO Data Virtualization software, rated a Fast Mover according to GigaOm.

Learn How You Can Add Agility and Pivot Faster

Market volatility is creating unprecedented challenges, leaving many organizations in need of greater agility to keep up. Quickly connecting digital assets, regardless of where they are hosted, is a key goal. To navigate this challenge and reduce time to market, the TIBCO Cloud Integration platform makes it easy for everyone in your business to share and discover digital assets. Read about how the TIBCO Cloud Integration iPaaS can help your users pivot more quickly in this blog post.

Stay on Top of TIBCO Data Science at the Virtual TIBCO Analytics Meetup

Keeping your software products up to date is the easiest way to push your business forward and get the most out of your investment. Every quarter, our analytics experts get together to keep you updated and answer questions. In February’s session, we will also include a demo on how to identify and classify patterns of interest in big data, which is a critical part of any manufacturing scenario. Join the live discussion with Chief Analytics Officer Michael O’Connell and the TIBCO Data Science Team.

Industry-Specific Ebooks Are Here!

Learning from industry leaders is a great way to advance your business. Gaining insights into their challenges and business transformation outcomes can help your organization reinvent itself and reach new heights. Learn from leaders in Manufacturing, Retail, and Financial Services by downloading our industry-specific ebooks.

TIBCO Cloud Integration makes it easy for everyone in your business to share and discover digital assets. Read about how the TIBCO Cloud Integration iPaaS can help your users pivot more quickly. Click To Tweet

Make sure to check back in February for more tips from TIBCO on how to keep pushing your business forward towards its goals for the year!

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How Profectus Delivers Value from Data

January 9, 2021 Sisense

Every company is becoming a data company. In Data-Powered Businesses, we dive into the ways that companies of all kinds are digitally transforming to make smarter data-driven decisions, monetize their data, and create companies that will thrive in our current era of Big Data.

Streamlining data management across high-volume transactions

Profectus is an international technology and services company that provides leading technologies for rebate and deal management, contract compliance and accounts payable audits. Founded 20 years ago and with offices in Australia, NZ, USA and The UK, their solutions are leveraged by 100 ASX listed companies, including Westpac and HSBC, Coca Cola Amatil, Vodafone, Coles, Kmart, JP Morgan, and Rio Tinto, just to name a few.

For Profectus, data is absolutely everything. From accounts payable data coming in as direct feeds from ERP finance systems, to hundreds of thousands of invoices Profectus’ solutions ingest on behalf of its customers, along with any agreement data that their customers have with their suppliers.

“We crunch enormous Accounts Payable data files, and thousands of rebate agreements, and invoices,” Profectus’ Chief Technology Officer, Mark Webster told attendees. “In the retail sector, for one of our biggest customers, we have 4TB of data that we crunch through every few months. That’s billions and billions of rows of data that we go through to find the different variances in order to find the best value for our customers.”

packages CTA banners BI and Analytics1 How Profectus Delivers Value from Data

Part of Profectus’ suite of services is ensuring that every transaction is aligned with a particular deal. But Mark revealed that despite the data-rich services the company provides, a lot of teams still use Excel spreadsheets.

“These have their limitations due to their size and data sets,” he explained. “And when you become a large organization, spreadsheets just aren’t going to cut it for you anymore.”

According to Mark, Profectus found that on average, somewhere between 3.5-4 transactions per 10k transactions contained an error. This number may seem relatively insignificant, but when repeated across millions or even billions of transactions, these errors add up.

“With our solutions, we’re able to save millions of dollars for our clients, simply because we are able to find the details of these transactions buried deep in the data,” Mark explained. “And the reason why we’re able to do that is because we really pride ourselves on focusing on the detail and accuracy of our data analysis. We don’t use aggregate data, we don’t use rollups. We use full detail — and that’s where we find the full value.”

Leveraging smarter data tools to unlock deeper insights

Profectus does a lot of processing, with around 90 people in their office busy “crunching” through row by row of data. But with the company growing fast, the challenge is finding a better way to boost the productivity, efficiency, and accuracy of processing these vast volumes of data at scale.

“Our COO was wondering, how could we possibly bring on more customers and then try to grow the team?” Mark said. “If a customer signs up, well sales are doing their jobs properly. But as they bring all these extra customers on, who can service them? Our business is growing, but our cost base is growing with it, because we just have to hire more and more people to trawl through more and more spreadsheets — that can’t be the sustainable way to do it.”

Profectus began looking for technology to take over and find a solution to automate the process of extracting extremely large volumes of data.

“We wanted to have algorithms, ‘visualization stations’, that actually tease out the differences in the data in a lot more automated way, so that we’re not just throwing more and more human capital at it, but actually leveraging smarter technology,” he added. “Spreadsheets just die at a certain size, and communicating the results becomes extremely difficult.”

“Think about the resources taken for teams to carefully handcraft and curate large spreadsheets, then attach them into an email. Then the customer comes back with various edits and more attachments. Trying to merge all the edits and figure out which version is the right one just gets out of control. And this whole process just breaks down at scale.”

Discovering the “single source of truth” with Sisense

For Profectus, having a streamlined, automated online system, where there’s a single source of truth was their “holy grail” solution.

“We did a very thorough and rigorous examination of the BI space and we put all of the different platforms through the ringer, but Sisense came out as the leading BI solution on the market,” Mark said. “With Sisense, not only is the data stored safely and securely, but we can extract the full value from our data and we can get the consistent repeatable and scalable answers our business needs.

“We also are using embedded analytics, with a portal that our customers can log in to and see easily for a more unified customer experience — and Sisense allows us to do this far more easily.”

Importantly, it was the sheer scalable power of Sisense’s solution that Profectus found was unmatched in the market.

Unlocking data in Snowflake to deliver insights through Sisense

With a high-powered data warehouse in place, Profectus needed a tool to unlock data that answered critical business questions. Through a combined pairing of Sisense and Snowflake, the Profectus team is now able to unlock the data in Snowflake with datasets they provide, including CSVs, spreadsheets, and third-party API integrations. Snowflake’s speed supports the live connections, ensuring Profectus sees the freshest data in its warehouse whenever up-to-date metrics are needed.

“My team now relies on Sisense and Snowflake to simplify a variety of recurring data aggregation workflows, from reports to spend analysis. Anything that used to require manually aggregating and merging spreadsheets can be pulled out of Sisense.”

“As an example, we ran a representative data set that we had in our Snowflake data warehouse through a competing solution, but we killed the process at 20 minutes because that was already unacceptable both from a customer experience and cost perspective,” Mark explained. “With Sisense, we ran the same data set, and it processed the query within 20 seconds! That was our aha moment.”

“This sort of data efficiency gain is a big deal for us, because it helps us to achieve the scale we need to serve our customers and grow as an organization.”

The data-driven vision for the future

Moving forward, Profectus is excited to reap the benefits of its new “project Delta,” which involves leveraging Sisense’s solution as part of a revolutionary shift towards smarter data-driven decision making.

“Project Delta for us is all about leveraging the right technology solutions to instigate new and exciting change,” Mark explained. “We want to enable behavior change in our customers, and for our customers to be able to optimize their business decisions, transform the way they do business with their suppliers, and help them enjoy much greater value. We’re confidently shifting towards automating a lot of our processing, taking the problem away from all the 90 people who have to manually check line after line of data, and actually getting the computer to do the job.”

“Importantly, we’re putting the right visualizations online to solve our communications problems, so our customers, their suppliers, and our own analysts can all log into the same solution and look at the same source of data treatment. They can all actually see the same story at the same time consistently, with full version control and no errors.”

Ultimately, Profectus wasn’t just looking for a “software vendor,” but a technology and business partner to work together, to help bring these great solutions to market.

“This is where Sisense really shines for us, because they have very much the same vision that we have around how to unlock insights from data and then take powerful actions based on those insights,” Mark added. “Sisense has a very compelling vision, which fits perfectly with what we’re trying to achieve.”

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David Huynh is a Customer Success Manager with Sisense. He holds a degree in Business Information Systems and has spent the last 9 years in a variety of fields including sales and project management. David is passionate about helping businesses leverage data and technology to succeed. When not in the office, he enjoys cooking, travelling, and working on cars.

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Blog – Sisense

Technology as a Disruptor to Optimize Operations and Explore New Revenue Streams

January 9, 2021 TIBCO Spotfire

Reading Time: 4 minutes

This blog was written by TIBCO Director of Digital Strategy Alessandro Chimera and originally published on Connected Technology Solutions.

Unless they re-think their business operations, they will fail. The average professional is also facing a challenge, one where a change in their habits is top of the list. Suddenly, we are required to travel less, attend fewer meetings, not eat at restaurants. Still, at the same time, we are streaming more content, making use of food delivery services, attending virtual meetings, and using eLearning platforms.

One industry heavily impacted is the travel industry, which now needs to re-arrange its offerings to optimize its business. In short, what is now required is a form of “recasting your business” – the new business imperative.

If the current situation and history have taught us anything, it is that when a crisis happens, traditional operational models are no longer valid. Companies need to react quickly and create, validate, and adopt a completely new strategy to keep their business running, as well as generate enough margin to weather the crisis. But it isn’t just the travel industry that is impacted; financial services, telecommunications, manufacturing, transportation, retail, healthcare, government, hospitality, and the energy sector are all facing the same difficulty.

How to Adapt
If we take a moment to analyze the actions financial services organizations need to take, the quickest action at their disposal is to speedily rebalance all of their investment lines and make smarter, event-driven decisions. On the other hand, a telecommunications business needs to gear itself to handle an increase in connections, additional load on their networks, and focus on providing reliable services to a burgeoning number of people whose only means of connecting with their communities is through communication services.

Another heavily impacted sector is manufacturing, as they see orders dropping or canceled because customers are focusing their primary needs elsewhere. There are delays in the supply chain, raw materials sourced internationally are delayed, and new procedures as a result of the pandemic are being implemented to ensure the safety of workers. Some of these businesses may well have to consider a temporary reduction in their workforce.

Transportation was the first industry to feel the direct impact as flights were canceled, borders closed, passengers assigned to new flights, and flight schedules have had to change and adjust at a moment’s notice. The IATA predicts that there is approximately a $ 63billion worldwide passenger revenue loss as a result of the current social distancing requirement.

The travel bans we are seeing from the US, Europe, Africa, and Asia have grounded thousands of flights. If 550 flights are canceled a day, that is a total of 125,000 daily passengers. Then there is also air cargo to consider. It was estimated that in January, which wasn’t even the peak of the crisis, air cargo decreased by 3.3%. We don’t have new figures, but that must have more than tripled by now.

Who is Ready
Very few players in these industries were prepared; for the most part, the majority were utterly unprepared. Let’s look at the lockdown in Italy, my home country, when it was first implemented it generated an increase in eCommerce of 56,8%, mobile traffic doubled, and systems had to scale to support the additional loads they were experiencing.

Manufacturers started to optimize their processes and operations by analyzing their data to create an understanding of how to best face the new climate they find themselves in. This was particularly true for food processing and manufacturing plants, which were experiencing a massive surge in demand as Italians were urged to stay home. Conversely, retailers and distributors evidenced a 12.2% increase in sales as a result of new demand.

On-demand media and streaming entertainment services also started facing pressure, a sudden surge in customers with more extended usage patterns had them reeling as the load placed on their networks had them at breaking point.

But not all have seen an increase in demand, and the entire hospitality industry had to come to a hard stop: major events were canceled or postponed, corporate travel restrictions have led to empty hotels, and major hotel chains are waiving cancelation fees for existing and new bookings, to at least ensure future business by not alienating customers.

Complete About-Turn
We often speak about business evolution and business transformation and how it needs to happen at speed. However, no one could have anticipated the rate at which it has been forced upon us. Some countries are already under lockdown, which means their window of opportunity has passed. Others need to hasten in their efforts to reinvent their go-to-market strategy completely.

Unfortunately, for many, they never invested in the tools to better analyze and make sense of their data. This left them entirely on the backfoot as they can’t tell if the new business processes/models they want to put in play will work.

The spotlight is on all businesses to act quickly and to connect and unify their data sources to recast the value potential of this data and intelligence so that they can take advantage of new channels and customers and leverage new revenue streams.

It is a lesson in understanding and a call to better adapt to what customers are looking for, monitoring their current behavior, and knowing how quickly you can adjust your business. If ever the term reinvention was relevant, it is now, in the current business climate we find ourselves. The key to this lies in knowing that decision-making relies on data-driven insights that provide you with the know-how of how to optimize your execution model to make the alternative business models you are exploring work.

We often speak about business evolution and business transformation and how it needs to happen at speed. However, no one could have anticipated the rate at which it has been forced upon us. Click To Tweet

Failure is not an option. Strategies need to be tested quickly and digitally, to predict an outcome. Lastly, but most importantly, you need to get closer to your customers. Understand that their buying power has moved online, they are more selective, more frugal, and discerning, and that customer intimacy is now a digital concept. If you get this mix right, they will return, and when the world rights itself, their loyalty will see them return as a customer.

Visit tibco.com to see how we can help you begin your digital transformation today.

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Visualize 5 Cool Insights on Holiday Tree Trends Over Time

December 31, 2020 TIBCO Spotfire

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?

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.

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Sisense and Signals Analytics Bring the Power of External Data to the Enterprise

December 30, 2020 Sisense

We’re stronger when we work together. In our Partner Showcase, we highlight the amazing integrations, joint projects, and new functionalities created and sustained by working with our technology partners at companies like AWS, Google, and others.

Business teams constantly want to know how their companies are performing — against their internal goals and those of the market they compete in. They benchmark their performance against their previous results, what their customers are asking for, what their customers are buying, and ideally what their customers will buy. To get their answers, businesses typically rely on data sources that are all internal, showing decision-makers only part of the picture.

That’s now in the past. Today, through a strategic partnership, Signals Analytics and Sisense are making it easy to incorporate external data analytics into a company’s main BI environment. The result is a broader, more holistic view of the market coupled with more actionable and granular insights. Infusing these analytics everywhere, democratizes data usage and access to critical insights across the enterprise.

Organizations who are truly data-driven know how to leverage a wide range of internal and external data sources in their decision-making. The integration of Signals Analytics in the Sisense business intelligence environment gets them there faster and seamlessly, without the need for specialized resources to build complex systems.

Kobi Gershoni, Signals Analytics co-founder and chief research officer

Sisense and Signals Analytics Bring the Power of External Data to the Enterprise

Why external data analytics?

The integration of Signals Analytics with the Sisense platform delivers on the promise of advanced analytics — infusing intelligence at the right place and the right time, upleveling standard decisions to strategic decisions, and speeding the time to deployment. Combining internal and external data unlocks powerful insights that can drive innovation, product development, marketing, partnerships, acquisitions, and more.

Primary use cases for external data analytics

External data is uniquely well-suited to inform decision points across the product life cycle, from identifying unmet needs to predicting sales for specific attributes, positioning against the competition, measuring outcomes, and more. By incorporating a wide range of external data sources that are connected and contextualized, users benefit from a more holistic picture of the market.

For example, when combining product reviews, product listings, social media, blogs, forums, news sites, and more with sales data, the accuracy rate for predictive analytics jumps from 36% to over 70%. Similar results are seen when going from social listening alone to using a fully connected and contextualized external data set to generate predictions.

The Sisense and Signals Analytics partnership: What you need to know

Signals Analytics provides the connected and contextualized datasets for specific fast-moving consumer goods (FMCG) categories
Sisense users can tap into one of the broadest external datasets available and unleash the power of this connected data in their Sisense dashboards
The ROI of the analytics investment dramatically increases when combining historical data, sales, inventory, and customer data with Signals Analytics data

Integrate external data analytics in your Sisense environment in three easy steps

Step 1: Connect

From your Sisense UI, use the Snowflake data connector to connect to the Signals Analytics Data Mart. The data can be queried live in the Sisense ElastiCube.

Step 2: Select

Once the data connection has been established, select the data types needed by filtering the relevant “Catalog.”

Step 3: Visualize

Select the dimensions, measures, and filters to apply, then visualize.

More data sources, better decisions

Your company is sitting on a large supply of data, but unless and until you find the right datasets to complement it, the questions you can answer and the insights you can harness from it will be limited. Whatever your company does and whatever questions you are trying to answer, mashing up data from a variety of sources, inside the right platform, is vital to surfacing game-changing insights.

To get started on the next leg of your analytics journey start a free trial or become a partner.

traditional vs cloud data warehouse blog cta banner 770x250 1 Sisense and Signals Analytics Bring the Power of External Data to the Enterprise

Tags: advanced analytics | analytics implementation

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Blog – Sisense

Accessing Kafka’s Real-Time Analytics Is Easier Than Ever

December 28, 2020 TIBCO Spotfire

Reading Time: 2 minutes

More and more major companies are realizing the full value of having real-time data-driven analytics at their fingertips. Everything from temperature sensor tracking and machinery wear-and-tear to social media metrics and targeted online searches to fraud and forecast trends can be critical information to a successful modern business.

In light of this, organizations have been turning en masse to Apache Kafka, and with good reason, as it’s just about the perfect tool for integrating these wildly diverse streams of real-time data across multiple, connected applications to improve decision-making.

However, many businesses still have not been able to take advantage of the benefits of the “real-time” aspect of these analytics.

The Problem with Kafka: Accessing Real-Time Information

Whether it’s an analyst doing reports or a data scientist applying machine learning methods to the data, they’re usually viewing it in aggregate from a traditional database, and typically don’t get to interact with it in its natural and most useful form—real-time.

The issue behind accessing real-time data is that most business intelligence, data science, and data management tools do not natively connect to Kafka. This means that getting useful analytical insights from Kafka usually requires custom coding as well as several complex components that are expensive, difficult, and time-consuming to implement.

Introducing TIBCO Cloud Data Streams for Kafka

But now, with TIBCO Cloud™ Data Streams, we’ve taken the expensive, custom-coding headache out of making that Kafka connection. Business users can just connect TIBCO Spotfire^® software to Kafka messages and go.

With a native low-code, or, in most cases, no-code Kafka connection from TIBCO, analytics agility can be achieved in just minutes. Now, there’s nothing to stop you from taking advantage of what Kafka’s real-time analytics has to offer.

When TIBCO and Kafka Work Together, Businesses Win

As Kafka adoption becomes more widespread, the massive advantage in the practical application of real-time analytics continues to grow increasingly evident. Some recent use cases include:

Real-time Monitoring of Sporting Events: TXODDS, a real-time aggregator and distributor of sports betting information, absorbs data from systems monitoring thousands of live sporting events in real-time, using a network of Kafka messages. The messages carry real-time inputs, such as which players are on the field, the score, and even the weather. These messages are fed to the TIBCO-powered TXODDS “brain,” which can compare current game conditions to history, execute sophisticated artificial intelligence (AI) learning models to predict which way the game is likely to go based on in-game data, and transmit a stream of data and predictions to their subscribers.

Predictive Global Bank Operations: A top-tier financial institution uses TIBCO to monitor global trading activity and get a real-time view of the impact of client orders, trading activity, and IT infrastructure all at once. Based on Kafka messages, the bank has predictive operations that can spot and stop problems before they happen, increasing agility and requiring fewer resources for citizen developers.

Near-Instant Fraud Detection: Another well-known bank is using Kafka and TIBCO to detect credit risk in real-time without any human intervention. Credit card scans are captured as real-time triggered events that stream through Kafka. The system learns what a fraud-like transaction looks like and makes an autonomous decision based on its learnings.

By building a bridge between open-source developers and business users, TIBCO helps you come together as a team to manage Kafka-powered business systems.

To learn how to analyze Kafka data in minutes, download this ebook “How to Easily Get Real-time Analytics from Kafka.”

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Why external data analytics?

Primary use cases for external data analytics

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Step 1: Connect

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The Problem with Kafka: Accessing Real-Time Information

Introducing TIBCO Cloud Data Streams for Kafka

When TIBCO and Kafka Work Together, Businesses Win

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