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Monthly Archives: September 2019

Pictures at an Oracle Exhibition: OpenWorld 2019

September 30, 2019   CRM News and Info
oracle openworld 2019a Pictures at an Oracle Exhibition: OpenWorld 2019

I don’t want to call this a full-blown deep analysis of Oracle OpenWorld 2019 and Oracle’s positioning in the business; however, what Oracle has done over the past year, culminating in what they presented at the conference deserves some mention and at minimum some profoundly…random thoughts.  I hope that you are willing to accept that much of this is raw material.

OpenWorld 2019

So Ladies and Gents, the product of my fevered mind…

Oracle is ready

We live in a technology – and business – world defined by platforms and ecosystems. The days of the technology stack are over.  Period. I hope that’s emphatic enough to let  you know how adamantly I believe that. No major technology company can survive simply by trying to sell its tech stack components to its potential and actual customers. We live in a world driven by the ability to deliver outcomes. For those at the more sophisticated and conceptual level, it’s a world of jobs to be done (JBTD), not products and toolsets – whixc exist for the enablement pleasure of outcomes and JTBD.  

Oracle, while somewhat late to the game, has figured that out.  And, something I would not have said a year plus ago, made the pivot. They are now focused on platforms, ecosystems, outcomes and, unbeknownst to them, JTBD. While I am unaware if they are methodological advocates of service dominant logic and the world of Vargo and Lusch, I see that they are starting to think and practice with a similar outlook.  But more than that, they are now ecosystems and platforms aligned with the market – and you can’t ask for more than that.

According to Oracle VIPs, some of their platforms — such as machine ;learning – are for internal use only; that is,  they use them for the purposes of building solutions. Some of them are public – their cloud platform as an Infrastructure as a Service (IaaS) being one of those.  But all in all they have moved to platforms as the foundation for their — and their customers’ — technology needs.

There are multiple signs that they are taking the ecosystems piece seriously. Steve Fioretti, long-time rock star Oracle veteran and friend has moved from his job as the VP, Customer Service and then Customer Service and Sales formerly known as the Engagement Cloud to becoming the person (a VP position too) in charge of the ISV program. His job is to build a partner ecosystem (not a channel per se) to support the Oracle platform and the subsequent ecosystems of demand/need that serves their customer base best as it evolves.  Building out this partner ecosystem is a core need

This leads me to the conclusion that as of  OpenWorld 2019, Oracle has pivoted from:

  1. Technology Stack (2017 and earlier) to:
  2. Platforms & Solutions jointly, not ecosystems  (Oracle MCX 2018) to:
  3. Platforms, Solutions, Customer Experiences ecosystems in concept(Oracle MCX 2019) to:
  4. Platforms & Ecosystems (Open World 2019)

Platforms + Ecosystems + Oracle = Sweet.

Oracle Redwood UI/UX is more than a pretty face

Hillel Cooperman and Jenny Lam do not only do the best UI/UX design work in the industry but they are both helping drive and signify what is the biggest change in culture in Oracle’s history. Openness,and — dare I say it —  fun are now part of how Oracle does things.

The work that Hillel and Jenny are spearheading is fundamental to the look and feel of not only the applications and platform, mobile, cloud etc but are fundamental to the company.  They are both a reflection of and a driver of how Oracle is feeling about itself and how much it means to the company to do things that look good, feel good and at the same time satisfy the sensory needs of contemporary customers. Here’s a short look at Redwood as presented at OpenWorld:

See how much nicer that makes the post look. Kind of proves my visceral point.

Their commitment to contemporary design goes a lot further than most – and extends well beyond their own technological and cultural requirements. I had a conversation with  Oracle Executive Director of Corporate Citizenship Colleen Cassitty, who told me of Oracle’s Design Tech High School launched on the Oracle Campus in 2014 that is committed to the very principles and practices that Hillel and Jenny are bringing to the Oracle culture and technology. Here’s a link to a video done on the High School. It was done by a Brazilian film company but most of it is in English, sprinkled with Portuguese. 

But Redwood isn’t just a design initiative and this isn’t lipstick on a pig.  This is a signal and a supportive driver of a profound, company-wide change in the culture of Oracle. They are moving from a company that was misaligned and pretty arrogant to a well-aligned and customer-focused company that truly is drinking the Gatorade (emphatically NOT Kool-Aid) of collaborating with a younger generation of customers and its older connected representatives – in a B2C and a B2B or a B2B2C world.

Newco, Oldco: Oracle in transition

Many moons ago, when I was a young warrior, I was subjected to more than one discussion among people who had been at PriceWaterhouseCoopers f.k.a Price Waterhouse and Coopers and Lybrand – two separate companies. These were somewhat excruciating, but I assumed it was part of my warrior survival training, so I never complained. I stayed taciturn.

The merger between the two companies had just happened, which makes it 1998, so I was a youngster of 48 years old. The excruciating part of the discussion was that each time a person from the newly formed PwC was introduced to someone they hadn’t met before they would say something like, “Randall Cobb Jr, oldco Coopers and Lybrand.”  They had this clear “thing” between newco (PwC) and oldco (Price Waterhouse or Coopers and Lybrand).

But as ridiculous as saying literally “newco” and “oldco” was, it does reflect what Oracle is going through as a company and its nothing short of breathtaking when it comes to the culture. Oldco Oracle was not, shall we say, the easiest company to get along with or work with or even pay attention to. It’s culture was, if I am being nice about it, difficult, and being honest, really bad, except for some wonderful pockets of sanity and decency (Anthony Lye’s CRM business unit for example). It was internally depressing – over the years, I had dozens of Oracle employees call me about going elsewhere.  Personally, I had had multiple difficulties with Oracle. I couldn’t work with them as a partner (I worked for a company with a decent-sized Oracle practice and was responsible for securing partnerships among my other duties), as an analyst and when engaged by them. That said, I did see they had one great silver lining and that was their middle management – the Senior Directors, Vice Presidents and SVPs and occasional EVP (hear that, Steve Miranda, one of the truly good ones?) who were a pleasure to work with. They were good human beings who got stuff done and thus kept Oracle at least on the business apps side more than competitive.  But the company’s culture was considered pretty toxic by me and many others.

Well, guess what? Not only has that gone away but what has apparently replaced it is the nearly breathtaking opposite – and it extends — apparently — to the whole company.  There is a Newco Oracle.  What I have seen is that the culture is now open – to ideas, to treating people humanely, to doing philanthropic good, to creativity, to collaborating with customers rather than just selling and servicing them – and to aligning themselves with their customers and prospects and the market as it is and to some extent, though there is still a fair amount of work to do here, with the future.

Before I get too effervescently effusive, this is early on in the company’s transformation. They still do not have a visionary culture, though it is now beginning to show some flair and creativity. They still have some significantly large parts of the organization that remain well ensconced in the cultural marshes. But on the whole it is not just refreshing but exciting to see what is a renaissance of a company – and a damned huge one – underway and while the baggage is not entirely gone, much of it has been discarded. 

Some of the signs of that are the way that customers are being thought of. In the past, by Oracle’s admission, they treated customers as objects of a sale. “Here’s what you need, customers, buy it, use it, it’s good, we will support it.  But you should buy these products.” And “you want that, sure, we’ll sell it to (even though they don’t really need it).” Now they have learned by their own admission to say “no” when customers want to buy something that they don’t need and to ask customers what they need and what outcomes they are looking for, not what products do they want to buy. They have gone from a product-centric outlook to a —  gasp! — customer-centric (if not fully customer-engaged) outlook. That is a MAJOR transition. It extends so many other ways that might sound trite and not business-like but make a huge difference in both employee morale and attitude and are signals that Oracle is changing.  For example, Brent Leary and I did several episodes of CRM Playaz, our insanely popular (according the Playaz Global Ratings System) show at Oracle MCX last March. One of the episodes, embedded here, was a rap battle between Jeff Wartgow and Steve Fioretti two VPs on the CX side. Know what makes this amazing? This was ORACLE’S idea, not ours. It is something our fevered brains might come up with, but the fact that Oracle (specifically the supercool Kim Guillon, AR rock star) came up with it, knocked us OUT, and we just went ahead and did it.

Watch it here:

Hilarious. No? Yes?

This is something that would have been unfathomable a few years ago but is indicative of a change at Oracle that has been brewing culturally for the last 18 months or so. This, in combination with the technology and the overhaul of the look and feel of everything at the company that I spoke of earlier, is telling me that Oracle, as formidable as it has been in its Death Star history is now moving much more toward the light – and will be a force to be reckoned with because of, among other things, the cultural transformation and the impact the new look is having on everything they do. 

If you prefer to not trust me – and I am sad that you might not – you can trust the good folks at diginomica.  Here’s what they said about Oracle Business Apps (my primary area of focus of course) and the ever popular good man Steve Miranda. See? 

To reinforce the point, an attendee comment lifted from diginomica’s OpenWorld coverage:

“I went along to OW for the second day and was impressed by the refreshingly low key and unpretentious presentation atmosphere, and spent most of the day talking to attendees rather than going to sessions.”

That is NOT the Oracle of yore. But it is Oracle at, and in, the moment.

But let’s not stop there. Let’s also consider what — at least from the business apps side –was the most important moment at OOW: the official announcement of the actual release of CX Unity – another weapon in the Oracle competitive arsenal. 

CX Unity isn’t a CDP but it is something of great significance

CX Unity is, praise be to Poseidon, not being touted as CDP but is instead being allowed to be what it is – a customer intelligence platform that is architected with contemporary enterprises in mind. Rob Tarkoff in his keynote on CX said (slightly paraphrased) “Calling CX Unity a CDP is like calling a Ferrari just a car.”  And while I’m not a car guy, it’s both an apt description and also not even enough.  CX Unity is exactly what Oracle says it is: “A complete customer intelligence platform for managing all (B2B and B2C) customer data.” (Again, mildly paraphrased) 

Arguably Oracle’s most important release in quite awhile – and to me with all my biases intact – more important than even Autonomous Linux and Autonomous Databases, CX Unity provides the foundation for not just significantly improved user interactions (hyperpersonalization) but more granular ways to intervene in those interactions (micro-moments). This was made posssible with the integration of long time Oracle acquisition Blue Kai and ID Graph into CX Unity.  It’s incredibly well thought out. And, true to one of Oracle’s traditions even in the worst moments, delivered as promised. 

Oracle SO nice to their…partners formerly known as competitors

Larry Ellison spent a good deal of time waxing enthusiastically about Oracle’s strategic partnership with Microsoft – the cloud interoperability partnership announced last June. If you want some interesting takes on both the announcement and Larry’s speech on it at OpenWorld, read the links I provided.  What makes this significant aside from Larry and Oracle taking sides in the Azure vs. AWS wars, is that this is coming at a time when in the past, Microsoft was one of the enemies. Oracle’s entire strategy is shifting to much more partner friendly at the grand strategic level down to the more tactical “filling the holes in the ecosystem”  I will have a LOT more to say about this overall (well beyond Oracle) in an upcoming post because its an actually important “trend” that I’m seeing at the enterprise tech level. But, to keep this hyperfocused and away from my usual meandering, this partnership – given the titanic nature of the two companies, has industry-wide significance.

So what was the downside? Anything? I mean…anything?

Well, honestly, the downsides were more conference related than Oracle transformation related.  Here are a few nitpicks and one or two things that were still clearly missing, just kind of proving the points I made when I wrote my post a few months ago on why Oracle won the Watchlist 2019.

Here are the nitpicks and the more substantial concerns all rolled into one. You can figure out which is which:

  1. The way they do keynotes needs to be rethought. I saw several and aside from Steve Miranda’s and Rob Tarkoff’s, most were pretty poorly organized and presented. They were “oldco” Oracle, product focused, not resonating with the audiences particularly. They didn’t really have any inspirational outside speakers. They didn’t highlight the philanthropic side of the company. The demos, while interesting, were (again except for business apps) showing off product, not outcomes enablement. You get the drift. Fix it, Oracle.
  2.  The message around Autonomous (Linux, Database, Cloud) was creepy even though the actual work that Oracle is doing in this area is really promising. It was “it will reduce human error by reducing human involvement”  It kind of came across that “since the problem with human error was humans, take the humans out of the equation and there won’t be errors.” The overall theme seemed to be this will replace human beings and thus eliminate error which is a I think missing the purpose of AI/ML etc which is to enhance and enable human capabilities, not replace them. Also, I’m a bit hard pressed to figure out how Autonomous Linux replaces a person (Charlie Brown’s buddy Linus maybe?). This was transmitted kind of poorly. It made it seem as if humans were flawed machines. Uhhhh, no. The ironic thing is what they are technologically doing is potentially game changing but telling the world that way about it – Skynet.  So rethink the message, stay strong with the tech.
  3. The lack of any public emphasis on corporate philanthropy is actually a problem. Doing Good with a capital G is something that generations from baby boomers to Gen Z are looking for from contemporary business. Oracle needs to get past the “ask don’t tell” on this and proactively talk about the good they are doing. 

Summary

Oracle OpenWorld 2019 was a stunning confirmation that Oracle is undergoing what is best characterized as a contemporary Renaissance. Aligned with the market, dramatic cultural transformation best reflected by the UI/UX Oracle look and feel and sensory immersion led by Hillel Cooperman and Jenny Lam, the focus around platform, ecosystems, and outcomes, the friendly focus on strategic partnerships and the vastly improved and truly released CX Unity are telling – and they are telling me and others that Oracle is now a formidable contemporary force in the technology world. Which is SO nice to see. A long way from oldco to newco, but they are there.

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Will Smith Set To Play Ex-Crime Boss Nicky Barnes In New Netflix Film

September 30, 2019   Humor
 Will Smith Set To Play Ex Crime Boss Nicky Barnes In New Netflix Film

According to Deadline, Will Smith is set to star in the upcoming Netflix film The Council as the New York crime boss Nicky Barnes. This project will reunite Smith with Peter Landesman whom he worked with on the film Concussion. Landesman wrote the screenplay for The Council and will executive produce the project.

The film will tell the story of the all-Black, Harlem-based crime syndicate headed by seven men, most prominently Nicky Barnes. The Council’s dream of a self-sufficient, self-policed Black city-state that would use funds through revolutionizing the drug game is at the center of Landesman narrative. In addition, Landesman’s script tracks the rise of Barnes’ public persona, which is most famously captured by the 1977 New York Times cover where he was dubbed “Mr. Untouchable.”

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DataRobot launches AI Catalog to enable enterprise team collaboration

September 30, 2019   Big Data

Machine learning and RPA company DataRobot today announced the latest release of the DataRobot Enterprise AI Platform, which includes the changes for automated feature engineering and the debut of AI Catalog, a service that lets enterprise teams search customer data in order to build and deploy AI models or make predictions.

AI Catalog utilizes tech from Cursor, a company acquired in February by DataRobot for an undisclosed amount. Cursor was born out of experiences at LinkedIn, where Cursor cofounder and DataRobot VP of product management Adam Weinstein led an analytics team. The challenge at that time was helping data scientists and engineers find scattered data in a large organization and then understand how to make data searchable and sharable to enable team collaboration.

AI Catalog will seek to achieve the same goals.

The update will also include automated feature engineering, which creates features that enable the enhancement of RPA by sharing related or secondary data sets. Automatic feature generation will grow more powerful with the growth of AI Catalog, Weinstein told VentureBeat.

“We actually don’t want you to even have to do that [identify secondary data sets] in the long run. [Today] I think there’s sort of this chicken and egg problem, but once users start using the catalog and the data is populated there, we can actually look to that catalog, automatically identify those data sets, and do the whole thing without any user assistance,” he said.

Automated feature engineering can help enforce governance within organizations to implement common standards and definitions like, for example, ensuring a common definition of customer churn.

Data scientists will also be able to use the Enterprise AI Platform with Apache Spark SQL to combine multiple data sets from Hadoop, disparate text, or other sources in an AI Catalog.

“I can actually combine all those within DataRobot without leaving the platform, using Spark SQL. And then we’ll emit a new data set that you can then use for projects to create new models or create predictions,” Weinstein said.

The platform update also includes MLOps, a service introduced last month that takes existing DataRobot services for AI and combines them with tools from machine learning operations company ParallelM, which was acquired by DataRobot in June. The service operates with Apache Spark and Kubernetes and comes with tools designed to help organizations deploy models in production — such as a dashboard for automatically identifying systems that need to be retrained to improve performance.

Despite heavy investment in AI talent and many insisting that we now live in an AI world, most businesses still struggle to deploy AI in production. According to a November 2018 PricewaterhouseCoopers survey, only 4% of business executives reported successfully deploying AI systems.

Earlier this month, DataRobot raised a $ 206 million funding round, bringing its total funding raised to more than $ 400 million.

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Five Steps for Building a Successful BI Strategy

September 30, 2019   Sisense

We’ve been talking a lot recently about companies needing to use their data in order to stay in business in the future. We’ve even gone as far as saying that every company is a data company, whether they know it or not. And every business – regardless of the industry, product, or service – should have a data analytics tool driving their business. With that being said, it’s not enough to just have a tool. Every business needs a business intelligence strategy to take it forward. 

As the Global Team Lead of BI Consultants at Sisense, I can say that the projects I’ve worked on where a BI strategy was involved, were more successful than projects without a strategy. The BI strategy played a major role in the setup, execution, and ongoing implementation of the BI platform. And it can do the same for you.

But what is a BI strategy in today’s world?

A business intelligence strategy is a blueprint that enables businesses to measure their performance, find competitive advantages, and use data mining and statistics to steer the business towards success. 

Every company has been generating data for a while now. The question is, what are you doing with it? Here are the five steps you should follow when building a data strategy.

Enterprise Overview 770x250 770x250 Five Steps for Building a Successful BI Strategy

#1 Find out where you are (so you’ll know where to go)

Our go-to approach for analytics that feeds well into a BI strategy is the Evolution of Analytics chart (below). Originating with Gartner, this chart includes the analytic features needed for a full analytics strategy, and what our AI team believe to be the absolute future of analytics – Cognitive Analytics.  

In order to know where to go, you must first find yourself on this chart. Most companies find themselves in the bottom left corner, in the Descriptive Analytics and Diagnostic Analytics sections. You likely already have some form of scheduled reports, are drilling down into your data, discovering what is in your data, and may even be visualizing to some extent. But as you can see from this chart, there is so much more you can be doing … and it’s easy to get there with the right business intelligence strategy. 

#2 Plan your objectives (and map the supporting data) 

At this stage, you will need to plan your business goal. It may be an oxymoron, but with so much data out there, the more focused you are in planning your business goals, the better off you’re going to be. Essentially, your data needs to address a business question or a business need. Do you want to be more efficient? Find a bottleneck in R&D? Share knowledge with customers? Add value to your solution? 

With a goal of getting to the end of the chart with predictive and prescriptive analytics, you can ask questions like: Are we going to hit our targets by the end of the year? What is the market segment we should focus on? Is there a bundle of products we should suggest based on our historical performance? What are the main contributors to close a deal? And is there a set of different elements we should combine and/or follow to make a bigger impact in the market? 

When working with customers we’ve found that a good place to start is with finance and sales data. Uncovering insights in this key area can make a major impact on the growth of the company. Let’s take revenue growth, for example. In order to analyze revenue growth, you will first need all of the sales information related to revenue. This information may come from Salesforce, or from your ERP system like Oracle, as well as from any other marketing technology that may hold customer experience information. 

Bigger companies have complicated tech stacks with multiple touchpoints that are collecting piles and piles of customer data that needs to be evaluated to see which technologies are relevant to this specific objective. Again, the granular focus on your objective here will help define which datasets you need for this objective. 

Also, keep in mind which types of data are missing as that may be critical in putting together the bigger picture and may prevent you from reaching the predictive analytics stage and the future of your BI strategy. 

The end result of this step should be a set of KPIs that support your objective, and a clear map of the data sources you will need to analyze and visualize these KPIs.

#3 Define how the data will be shared (and how it will be distributed)

Before you start executing on the plan, there is one very important question that needs to be answered. 

How are you going to release the solution?

I know, this seems like an obvious question, but when so much data is concerned, this is one of the most critical items to be defined in your strategy. There are two basic strategies that your company can take: 

A Decentralized Approach

Some organizations empower its end users with interactive dashboards. This is where the term citizen data scientist comes into play. Citizen data scientists do not need to be data scientists, they just need to know their way around the data, and that begins with giving them access to more than just a dashboard. These are the employees you’d consider power users. They’re the ones that are defining what is needed in the department and need the insights to make decisions. In large enterprise organizations, this scenario can free up bottlenecks with IT and data teams, enabling departments to do a lot of the data analysis on their own. 

A Centralized Approach

On the flip side, we have organizations that have decided to be in complete control of the data that is distributed, including who sees what, and how much of it they can touch. Take Nasdaq for instance. Their BI strategy took into consideration their sensitive data, huge distribution channels, and the need for better governance to reach one version of the truth. Building on this strategy, Nasdaq provides its customers with dashboards, but it does not provide them with the ability to work directly on the data models. There is a certain amount of drill-down that each customer can perform to see more details, but the data is strictly governed with system level, object level, data level, and row-level security.  

If your solution is going to be embedded within your product, there are a few more questions you should be discussing, how and where to embed, how to scale when you’re going to hit the critical mass number of users, what will be the process of moving from development to product, and are you going to freeze the code during that time?  

Also consider how the BI solution will be communicated to the company or customer, and how you will support the adoption of BI in the organization. Options include emails, meetings, PR, training, enablement, maybe even old-fashioned documentation. 

Spend some time on this with your team members, stakeholders, and management and go over all the scenarios. As your BI strategy materializes, you will be thankful that you did. 

#4 Deliver your solution (and focus your efforts) 

You may think it’s too early to think about, but part of your BI strategy needs to be how you’ll deliver the solution to your end-users, or your entire company.

Some of this may come naturally with the decision on how you will share data. For instance, for a centralized approach (where the user has no room for adjustments) you will need to put more effort into training and documentation. For a decentralized solution, you may want to do short release cycles, asking for feedback on each release, and then incorporate that feedback into the next release.  

By outlining the delivery method in your BI strategy, you can plan how you want to focus your efforts. Do you need to work on creating more data governance or put more effort on training and documentation? 

#5 Find the roadblocks (and push through them)

Now that you have a clear idea of what kind of questions you need to ask, and what kind of data you need to support that, you will now need to understand who are the gatekeepers in this scenario. The gatekeeper in this situation is basically who or what is standing in the way between you and the data.  

Your data can be stored in a database or may even be located with a third party vendor. If you are outsourcing HR services to a company that is managing your hiring pipeline, or if you have cloud-based service providers like Marketo for managing marketing campaigns or Quickbooks for financial services, then you will need to plan how to connect to their data and learn about its structure in order to use it properly. 

For some third-party applications, there may be a simple API that can be used to import the data. For the IT department, it may be just the manager’s permission and a couple of signatures that you will need to find in order to access the data. This all takes time and resources that need to be allocated inside your BI strategy.  

Another roadblock may be the personnel you need to implement your strategy. Don’t forget to plan your workforce ahead of time, not only for the first release but for future changes and enhancements down the road.

Go Big, go data

We are firm believers in a data and BI strategy. We’ve been with customers when the light bulb goes off when all the pieces fall into place when their first dashboard delivers that ‘Aha! moment’ that changes the shape of their business forever. It’s moments like these that make me proud to be a BI consultant helping customers build their data strategy and find insights in their data. 

The digital transformation of your business must happen – regardless of the industry, product, or service – you must develop a data strategy that will drive your business forward.

Enterprise Overview 770x250 770x250 Five Steps for Building a Successful BI Strategy
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WHEN ADS WERE LESS P.C. AND MORE ENGAGING

September 29, 2019   Humor


H/T: KIM

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ANTZ-IN-PANTZ ……

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Amazon’s Vesta no-show highlights the challenges of home robots

September 29, 2019   Big Data
 Amazon’s Vesta no show highlights the challenges of home robots

You’d think Amazon would be the one to shake up a product category that has chewed up and spit out startups and corporate giants alike, but the company’s next flagship robot seemingly remains a work in progress. At a press event in downtown Seattle, some expected Amazon to preview a home robot that’s reportedly like a roving Echo Show, replete with wheels, microphones, and a display. But the announcement never came, and Amazon’s reticence might speak to the many challenges inherent to home robots — and indeed, robots at large.

Amazon’s robot — code-named Vesta, after the Roman goddess of the hearth  — apparently packs far-field microphones and speakers that enable it to understand and respond to the thousands of commands Alexa recognizes. It’s said to be able to navigate through homes using computer vision and techniques like simultaneous localization and mapping, and select Amazon employees are reportedly piloting it ahead of a launch as soon as this year.

An unforgiving market

Home robotics — and robotics generally — has proven a tough nut to crack for even the best-funded ventures.

In April, Anki — the San Francisco startup behind AI-imbued robotics toys like Overdrive, Cozmo, and Vector — closed its doors after raising close to $ 200 million in venture capital from Index Ventures, Two Sigma Ventures, J.P. Morgan, Andreessen Horowitz, and other investors. Anki claimed to have sold 6.5 million devices total, and 1.5 million robots last August alone, and revenue was close to $ 100 million as of year-end 2017.

Its crash and burn followed that of Bosch-backed startup Mayfield Robotics, which was developing a larger, pricier ($ 700) home robot dubbed Kuri. Robotics company Jibo, which engineered a social robot featuring a bespoke conversational assistant, shut down earlier in the year. Honda canceled its Asimo program. And in a somewhat related development, industrial robotics company Rethink Robotics was recently forced to cease operations after attempting unsuccessfully to find an acquirer.

But that hasn’t stopped others from forging ahead. Temi, a startup headquartered in New York that’s developing a $ 1,500 telepresence robot with voice assistant integration, recently raised $ 21 million in part from former Alibaba chief technology officer John Wu. Separately, wellness robots like Mabu and Diligent Robotics’ Moxi have found their way into hospitals, homes, and nursing centers, where they’re doubling as orderlies and symptom trackers for chronically ill patients.

Perhaps the best-known home robot success story is that of iRobot, which has sold more than 25 million units to customers around the world. Chief technology officer Chris Jones attributes its success to its singular focus on housecleaning — and to perseverance in the face of logistical challenges.

“You have electrical, mechanical, software … and all that has to come together in a practical package that actually does something valuable, and getting those to work together efficiently and effectively is a challenge,” said Jones. He described the industry as an art rather than an exact science. “Every home is different — people interact with robots differently. It’s a tall order, and that’s why staying focused on practicality really matters.”

Becoming human-like

Amazon’s home robot will have to overcome formidable barriers to success, chief among them a lack of emotional intelligence and customers’ sky-high expectations.

On this first point, Alexa AI chief scientist Rohit Prasad recently revealed that teams at Amazon are experimenting with systems that detect happiness, sadness, and anger from voice alone. The initial fruit of that labor, frustration detection, emerged this week.

Facial and object recognition are poised to play a key role in this as well, and Amazon has all the technical resources necessary to build a robust system. Its AWS DeepLens camera can run pre-trained or custom AI models to perform sentiment analysis and detect a variety of activities, such as brushing teeth or playing the guitar. AWS’ controversial Rekognition service can suss out sentiment and more. Amazon’s Echo Look taps computer vision to recognize clothes. And just this week, Amazon deployed an AI model to the Echo show that’s able to make out common pantry goods.

In a home robot, facial recognition could be used to record photos or videos around the house or greet kids when they return home from school. As for object detection, it might help to personalize product recommendations and spot signs of a break-in a la Amazon’s Alexa Guard feature. Or it could work in tandem with services like Amazon Key to follow strangers around the room, paving the way for the remote installation of home furniture or appliances that can’t be simply dropped off at a doorstep.

Needless to say, it’s critical work; emotional intelligence and contextual awareness can lead to interactions that feel more natural. But studies have shown that people are predisposed to name and even ascribe motivations to robots, which indicates that robots will need to be communicative in addition to perceptive.

Teams like those behind Mayfield’s Kuri and Anki’s Vector laid the cornerstones for paradigms of emotional expression. Kuri responded to nearly every turn in a conversation with animated expressions, including a confused “huh?” emoji if it didn’t understand something or a “got it” following a command. And Vector, a tiny handheld robot with dual treads and an articulated “head,” conveying feelings of nervousness, joy, panic, annoyance, excitement, and more with animations and sound effects.

“We explored putting third-party interfaces into robots and found that having to say a hotword [like ‘Alexa’ or ‘hey, Google’] felt awkward and mechanical,” Anki Mark Palatucci told VentureBeat in a previous interview. “We wanted [Vector] to feel more personal — more emotional.”

Amazon’s robot would do well to follow their leads, perhaps with expressions, animations, or sound and with music and activity recommendations tailored to habits and sentiment. It’s a future Amazon inched toward with Alexa Hunches, which proactively recommends actions based on data from connected devices and sensors, and with a feature that takes into account the proximity of devices when Alexa responds to commands like “Alexa, turn on the lights.”

Function over form

Whatever form Alexa’s robot takes, its size and appearance will be key to mitigating the preconception problem. As Palatucci explained, there’s an uncanny valley in robotics: People except more large and human-like robots.

Aeolus is a prime example. The janitorial ‘bot can identify objects, clean the floor with any off-the-shelf vacuum, and grasp things like drinks. The only problem? It moves at a snail’s pace. In a demo at CES last January, Aeolus took a full minute to pick up a stuffed animal and put it in a nearby bin.

Optimists like Misty Robotics CEO Tim Enwall firmly believe every home will have a highly capable robot within 20 years, while more cautious observers like Carnegie Mellon University professor of robotics Henny Admoni expect it’ll be 5-10 years before mass-produced robots can pick up after kids, tidy furniture, prep meals, and complete other domestic chores. As for folks like Jones and iRobot CEO Colin Angle, they predict that a family of machines rather than a single robot will work together to perform chores like folding clothes, washing the dishes, and assisting older or disabled family members.

“The home can handle several different types of robot. You’re going to be able to buy them incrementally, each specialized to do a purpose really well, and there’s going to be some things where combining functionality into one robot makes sense,” explained Angle.

That’s to say Amazon’s first home robot probably won’t fulfill the promises of a Jetsons‘ future, and that it will likely be the first of many models and designs to come. Of course, Amazon’s no stranger to playing the long game. Just this week, it announced Sidewalk, a wireless internet of things (IoT) protocol with which it hopes to supplant standards that have had than a decade head start. And it’s an open secret that Amazon lost a good chunk of change on early Fire tablet sales, which it’s long since recouped through sales of ebooks, Audible subscriptions, Amazon Prime Video rentals, and more.

When Bosch announced Mayfield’s shuttering last year, the company said it couldn’t find a “fit” to “support and scale” Kuri, a sentiment that resonated with Admoni. “I think [these companies] didn’t find a compelling use case,” he candidly told the Financial Times last year. Jones is of a similar mind — in an interview with VentureBeat at Amazon’s re:MARS conference last summer, he said that the robots that fail to catch on do so because they fall short of marketing promises.

If Amazon doesn’t play its cards right, it risks repeating history.

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5 Reasons to Become a TIBCO Partner

September 28, 2019   TIBCO Spotfire
Patner summit award winners 00001 e1569016186898 696x365 5 Reasons to Become a TIBCO Partner
TIBCO Partner Award Winners at TIBCO NOW Chicago 2019

We know you want to bring value and opportunity to your customers, and drive more sales and revenue for your business. What better way of doing that than becoming a TIBCO partner to stand out from your competition? The TIBCO Partner Program has been designed with you in mind, tailored to meet your individual business objectives. Through the program, we are committed to providing you with all of the tools to market, sell, and deliver industry-leading TIBCO solutions to your customers. 

Here are five reasons why you should become a TIBCO partner if you aren’t already: 

1. The Market Opportunity

Through the TIBCO Partner Program, you have access to the hottest technologies that enable digital transformation to help organizations quickly innovate and execute, reduce risk, and increase efficiency and customer satisfaction. TIBCO solutions drive innovation across industries such as government, healthcare, hospitality, manufacturing, media, and retail.

2. The Technology

The TIBCO Connected Intelligence product portfolio gives your customers the opportunity to interconnect everything, unify their data, and augment intelligence. Understand how your clients are utilizing Connected Intelligence to find the right tools in order to fulfill their crucial needs. These tools include API management, data visualization, AI & ML, and much more.

3. The Industry Leadership

TIBCO is recognized as a leader by leading analyst firms such as Forrester, Gartner, and others, constantly ranking high on their evaluation systems for various product capabilities. That’s essential, but so is what customers say. We get high marks on the TrustRadius user review site, and our customer case studies tell the tale of fast, efficient, successful engagements that solve problems and drive innovation everywhere. 

4. The Partner Program

Through our program, we offer all the resources you need to be successful. This includes product certifications, deal registration, MDF, marketing programs, sales enablement, teaming agreements, training, and margins up to 35 percent. What’s more, is that we are always offering new courses on TIBCO Academy supporting our latest product releases, solution, and use cases that you can take to your customers.

5. The Partner Summits 

Get a front-row seat to the Partner Summits, which take place during our TIBCO NOW conferences. From a warm welcome by TIBCO executive leadership to the latest on the launch of the TIBCO Partner Program and the new TIBCO Academy, to regional partner awards, the Partner Summit is dedicated entirely to updating you and your team on insights, strategy, resources, and tools to support your success.

See what other partners say about the benefits of the TIBCO Partner Program. Check out these partner testimonials captured at TIBCO NOW Chicago talking about how the TIBCO Partner Program has enabled them to create business opportunities for their customers. 

Already a partner? Register for our Partner Summit at TIBCO NOW London to mingle with your peers and TIBCO executives on all things partner related. 

Thinking about becoming a partner? Register through our Partner Portal today. 

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Business Process Management And Robotic Process Automation: Two Sides Of The Same Automation Coin

September 28, 2019   BI News and Info

Part 8 in the “Intelligent RPA” series about the evolution of robotic process automation and its potential impact on digital transformation.

Historically, companies have always been organized into silos. And when they started to deploy information technology, they implemented information systems that themselves were siloed: human resource management, accounting management, procurement management, logistics management, etc. The desire to streamline business processes has existed for years with huge demand for business process management (BPM) and more recently with robotic process automation (RPA).

What is BPM?

Business process management is a strategic, holistic, and structured approach for optimizing notable repetitive tasks. It deals with process orchestration, extension, optimization, and, of course, innovation. BPM manages structured business processes by bringing human and automated activities into a managed sequence of steps. It fosters teamwork, streamlines collaboration, and automates production workflows.

What is RPA?

Robotic process automation is a tactical, focused, and agile approach for accelerating manual processes. It deals with task automation in a user-centric way. Compatible with any application existing in the information system, RPA handles unmodeled, “naturally grown” processes with UI-based automation. Automation is necessary to integrate legacy systems where APIs don’t exist and direct access to the data is not available. RPA minimizes keying errors, speeds up work, and cuts costs. It frees employees from mundane, repetitive tasks and leverages their human skills for more important tasks.

Why not use BPM and RPA together?

BPM and RPA are fully complementary. They can be integrated seamlessly to leverage their advantages for intelligent automation.

Today’s solutions encompass services that manage workflows and business rules for decision logic to provide end-to-end process visibility. Architects can design and implement structured, automated processes in the cloud, while intelligent RPA helps run repetitive, rule-based, and user interface-focused tasks. An intelligent BPM (iBPM) workflow can trigger intelligent RPA bots and vice versa. RPA can be used as a middleware to gather data from core systems or external websites.

Let’s imagine a use case in banking for onboarding new customers:

  1. A request from a prospect, coming from an email received from the bank’s website or a visit to a bank’s branch, is handled by an intelligent RPA bot.
  1. The bot triggers the “Customer Onboarding” process in the workflow.
  1. The bank clear checks that it is not a cold lead and sends the hot leads to an attended RPA bot – a digital assistant, in our terminology – that helps gather data to execute the know-your-customer mandatory checks for new-customer approval.
  1. After approval, the workflow automatically creates the bank account and manages provisioning for the checkbook, credit card, web, and mobile app access, and finally sends a confirmation email to the new customer.
Blog 7 Business Process Management And Robotic Process Automation: Two Sides Of The Same Automation Coin

Additional scenarios could be found in structured enterprise processes, which can be made even more efficient with flexible task automation for things like invoice handling, asset and purchase order approvals, IT ticket creation, seat allocation as part of employee onboarding, request for material price changes, and so on.

Integrated this way, intelligent BPM and intelligent RPA can drive your organization to an unprecedented level of automation, providing the best for your employees and customers and accelerating the time to business outcomes.

Please visit our SAP Intelligent Robotic Process Automation web page, and contact us for more information about SAP Intelligent RPA and integrated business process management.

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Iniciar Sesion

September 28, 2019   Humor

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Acuerdo de privacidad de Facebook de $ 5 mil millones de dólares aprobado por la FTC Funcionarios estadounidenses aprobaron un acuerdo de privacidad récord de $ 5 mil millones con Facebook Inc. para resolver el escándalo de datos de Cambridge Analytica, dijeron las personas, lo que provocó una protesta inmediata de legisladores y defensores de la privacidad que dijeron que no fue lo suficientemente lejos. Read More

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Congratulations to the Winners of the “Back to School” Contest!

September 28, 2019   Self-Service BI

For our Back to School contest this year, we had so many amazing entries, showcasing creativity, design expertise, excellent use of Power BI, and of course a genuine love for education! Before we get to the winners, I want to take a moment to introduce our judges.

Because this was a Back to School contest, we could not have picked the winners without the help of two educators:
James Burke | Middle School STEM Teacher

Nicole Lange | Former High School Biology Teacher

Additionally, entries were evaluated by several members of the Power BI Product Team, including Rien Hu, June Punkasem, Kim Manis, Amanda Cofsky, Tessa Hurr, and Miguel Martinez.

Contest Winners

Our first place winner is Periodic Table of the Elements by David Eldersveld.

  • We loved how useful this lesson is; it’s a perfect supplement for any high school chemistry course.
  • Also, the author showcased superb use of Power BI features, such as report page tooltips, bookmarks, dynamic conditional formatting and dynamic measures.

If you are interested in learning how exactly the lesson was made, the author published a video playlist demonstrating the various parts of the creation process.

Our second place winner is Learning to Stay Healthy by Paul & Martin Consulting.

  • The lesson leveraged a wide range of Power BI capabilities to create dynamic backgrounds, What If parameters, and included several custom visuals and data sources.
  • It’s a visually fun and inviting lesson that we could easily see in any high school nutrition class.

The third place winner and also the community favorite is Estimate Electricity Energy Usage and Cost by Duc Nguyen.

  • The lesson was a creative, fun way to connect energy to our daily lives; therefore, it’s very useful for middle school and high school energy lessons.
  • The author demonstrated great use of Power BI by creating a truly interactive lesson, spanning across several data sources.

Congratulations to all winners and thank you to everyone that participated this year!

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