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(the color might not share correct on slideshare) Might want to download to view... Some late work we put together for the executive main stage keynotes at TIBCO NOW, our annual user conference. Here is some nice supporting imagery using powerpoint on a uniquely formatted screen
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- 5. Visual & Embedded Analytics 2016 Analytics that amplifies experience and accelerate digital transformation
- 7. “Great graphics amplify human understanding." -Edward Tufte “Great VISUAL ANALYTICS amplify human understanding." Christof Ahlberg A weak player with a great computer interface beats a great computer.” Gary Kasparov
- 8. Cognitive computing should augment, not replace, human thought AUGMENT INTELLIGENCE
- 9. Fastest time to insight Answer more questions in less time Inline data wrangling You must be immersed in the data to see what’s important Analytics apps at scale Broadcast good ideas across the company Embedded BI Every App is Better with BI AUGMENT INTELLIGENCE
- 10. Dashboards that amplify thought Fastest time to insight Answer more questions in less time Powerful new visualizations Immediate actions on insights
- 11. “We have a small team of rock-star data scientists – we use Spotfire to distribute their most insightful models to our 1,000+ stores” Analytics apps at scale Broadcast good ideas across the company
- 12. In-line Predictive & Prescriptive AnalyticsAnalytic Dashboards & Guided Apps Analytics apps at scale Broadcast good ideas across the company Collaborative Insights
- 13. Inline data wrangling You must be immersed in the data to see what’s important
- 14. Data transformations at your fingertips Interactively create new data Self documenting workflow Inline data wrangling You must be immersed in the data to see what’s important
- 15. Embedded BI Every app is better with BI 87% of applications have embedded BI today, and will require embedded BI in the future.
- 16. New Charts New Dashboards and Theming New Data Wrangling New iPad Client Server designed for DevOps & massive scale MAKING THE FUTURE POSSIBLE. The re-architected Spotfire client and server architecture
- 17. Fastest time to insight Actions, more visualizations, printing, hybrid cloud Inline data wrangling Smart data blending, edit and share workflows Analytics apps at scale Hybrid cloud, Omni device Embedded BI More and better services for embedded BI Analytics: What’s next
- 22. Component Exchange and Partner Marketplace Product Idea Portal Trust RadiusBest Practices Wikis Community Focus
- 23. TIBCO’s leading technology… …add fast-start Accelerators… …provides what Digital Businesses need now Fast Data Platform TIBCO Accelerators Digital Solutions Introducing TIBCO
- 24. The New TIBCO Accelerator Engineering & Enablement Team A team of top field engineers, now embedded in TIBCO engineering A mission to build free, re-usable, engineered Accelerators for the TIBCO community A community for collaboration Introducing TIBCO TIBCO Accelerators TIBCO Accelerator Engineering TIBCO Community Accelerator Accelerator Accelerator
- 25. Visual Analytics StrategiesReusable Code, Architecture and Best Practices Operational Dashboards What is an accelerator?
- 26. NEW INDUSTRIAL EQUIPMENT ACCELERATOR NEW CONNECTED VEHICLE ACCELERATOR EDITIONS – SHIPPING, AIR ACCELERATOR FOR APACHE SPARK FX Dealing Accelerator 2016 Accelerators Deploy Faster. Fail Faster. Collaborate Faster.
- 27. Streaming Analytics, Operational Intelligence & Accelerators
- 28. Fastest time to insight Answer more questions in less time Inline data wrangling You must be immersed in the data to see what’s important Analytics apps at scale Broadcast good ideas across the company Embedded BI Every App is Better with BI One more thing... Streaming Analytics Our business operates in real-time and we need to automate decisions... AUGMENT INTELLIGENCE
- 29. When the temp sensor reading increases by more than 20 degrees in any 15 minute window, then shut the machine off & create a BPM case Min, Max, Slope Streaming Analytics Your Business must automate to thrive
- 30. LiveView Web Operational dashboards in minutes, not months
- 31. Cloud First Streaming analytics in the cloud More Acceelerators New editions, more collaborations More ease of use LiveView Web Streaming Analytics: What’s next
- 32. Fastest time to insight Answer more questions in less time Inline data wrangling You must be immersed in the data to see what’s important Analytics apps at scale Broadcast good ideas across the company Embedded BI Every App is Better with BI Streaming Analytics Our business operates in real-time and we need to automate decisions... AUGMENT INTELLIGENCE
- 33. Great visual analytics. Answer more questions in less time Inline data wrangling. You must be immersed in the data to see what’s important. Analytics apps at scale. Broadcast good ideas across the company. Embedded BI. Every app is better with BI Streaming analytics. Your Digital business must automate to thrive. AUGMENT INTELLIGENCE
- 34. Fastest time to insight. Inline data wrangling. Analytics apps at scale. Embedded BI. Streaming Analytics Accelerators AUGMENT INTELLIGENCE Summary
- 45. WHAT’S THE PROBLEM.. First Last Addr1 Addr2 City State Zip DOB Jon Smith 1030 Main St. Princeton NJ O8540 Oct 12 79 10/12/97 Jon Smiht 1030 Main Princeton NJ 0854O Mary Smith 1030 Main Street Princtun New Jersey 3/11/1981 Smith Kevin 1030 Main St Princeton NJ 08540 12/6/2003 John Smyth Main Street 103A Pton NJ 08540 10/12/79 Smith 1030 Main St. Princeton NJ Jon
- 46. TIBCO® Patterns © Copyright 2000-2011 TIBCO Software Inc.
- 47. THE PROBLEMS WE ALL FACE. > “Chamberlain” ≈ “Chumberland” - are they the same person?
- 50. JMS WCF
Editor's Notes
- ToDo– Per RDM, this will be a new graphic with themes overlaid. ToDo– Don’t’ call them themes, but principles. Script has been updated. To Do: Match to Matt’s final slide Layer on Ease of Use, Cloud First, Industrialization AFTER showing the different IT groups and different clouds
- WE’VE FORMED A TEAM OF TOP FIELD ENGINEERS AND WE’VE EMBEDDED THEM IN ENGINEERING. UNIQUE VIEW OF CUSTOMERS THEY HARVEST THE BEST USE CASES, BEST PRACTICES, AND FORMALLY RELEASE ACCELERATOR TECHNOLOGY FREE. OUR SELFISH GOAL IS SIMPLY TO HELP YOU GET MORE VALUE, MORE QUICKLY FROM OUR PLATFORM.
- http://www.forbes.com/sites/gartnergroup/2015/08/14/big-data-fades-to-the-algorithm-economy/#11dcc64b5114 Big Data Fades to the Algorithm Economy By Peter Sondergaard Gartner, Inc. Big data is the oil of the 21st century. But for all of its value, data is inherently dumb. It doesn’t actually do anything unless you know how to use it. Oil is useless thick goop until it’s refined into fuel. Big data’s version of refined fuel – proprietary algorithms that solve specific problems that translate into actions – will be the secret sauce of successful organizations in the future. The next digital gold rush will be focused on how you do something with data, not just what you do with it. This is the promise of the algorithm economy. The closely guarded secret Algorithms are already all around us. Consider how Google’s proprietary algorithm in the driverless car functions as the connective tissue that combines the software, data, sensors and physical asset into a true leap forward in transportation. After all, what makes Google one of the most valuable brands in the world? It isn’t data; it’s the company’s most closely guarded secret, its algorithms. High frequency trading is another example. A trader’s unique algorithm drives each decision that generates a higher return than competitors. The algorithm trumps the data that it accesses. A brave new world of opportunities Where does this ultimately lead? Software that thinks and does. Cognitive software that drives autonomous machine-to-machine interactions. Artificial intelligence. Today, the opportunities for organizations and technology providers are enormous. For organizations, the opportunity will first center on monetizing their proprietary algorithms by offering licensing to other non-competing organizations. For example, a supply chain company can license its just-in-time logistics algorithms to a refrigerator manufacturer that seeks to partner with a grocery chain to automatically replenish food based on your eating habits. Why invent or slowly develop sophisticated algorithms at huge cost when you can license and implement them quickly at low cost? For technology providers, a new opportunity exists to develop and sell algorithms that help connect their customers’ existing offerings to others via the Internet of Things, or a veritable ‘meshternet’ as it will become, differentiating their services in the marketplace. Once media hype increases around initiatives such as the recently announced Google Brillo, a system that allows easy connection between devices, this will undoubtedly become a topic of fevered questioning for CIOs at C -suite meetings The growth opportunities and benefits of efficiency that exist when inert things can communicate autonomously to take actions without human intervention will be something every CEO and CIO will want to explore.
- http://www.forbes.com/sites/gartnergroup/2015/08/14/big-data-fades-to-the-algorithm-economy/#11dcc64b5114 Big Data Fades to the Algorithm Economy By Peter Sondergaard Gartner, Inc. Big data is the oil of the 21st century. But for all of its value, data is inherently dumb. It doesn’t actually do anything unless you know how to use it. Oil is useless thick goop until it’s refined into fuel. Big data’s version of refined fuel – proprietary algorithms that solve specific problems that translate into actions – will be the secret sauce of successful organizations in the future. The next digital gold rush will be focused on how you do something with data, not just what you do with it. This is the promise of the algorithm economy. The closely guarded secret Algorithms are already all around us. Consider how Google’s proprietary algorithm in the driverless car functions as the connective tissue that combines the software, data, sensors and physical asset into a true leap forward in transportation. After all, what makes Google one of the most valuable brands in the world? It isn’t data; it’s the company’s most closely guarded secret, its algorithms. High frequency trading is another example. A trader’s unique algorithm drives each decision that generates a higher return than competitors. The algorithm trumps the data that it accesses. A brave new world of opportunities Where does this ultimately lead? Software that thinks and does. Cognitive software that drives autonomous machine-to-machine interactions. Artificial intelligence. Today, the opportunities for organizations and technology providers are enormous. For organizations, the opportunity will first center on monetizing their proprietary algorithms by offering licensing to other non-competing organizations. For example, a supply chain company can license its just-in-time logistics algorithms to a refrigerator manufacturer that seeks to partner with a grocery chain to automatically replenish food based on your eating habits. Why invent or slowly develop sophisticated algorithms at huge cost when you can license and implement them quickly at low cost? For technology providers, a new opportunity exists to develop and sell algorithms that help connect their customers’ existing offerings to others via the Internet of Things, or a veritable ‘meshternet’ as it will become, differentiating their services in the marketplace. Once media hype increases around initiatives such as the recently announced Google Brillo, a system that allows easy connection between devices, this will undoubtedly become a topic of fevered questioning for CIOs at C -suite meetings The growth opportunities and benefits of efficiency that exist when inert things can communicate autonomously to take actions without human intervention will be something every CEO and CIO will want to explore.
- What makes anticipation difficult? (in this slide we will visualize the idea that there is a lot of data, BIG Data that companies have to handle and it is helpful when people can identify patterns in this chaos to gain a two-second advantage. Any Text? [Carmen: There is no text here, just the title slide which is What makes anticipation difficult? Show something about seeing patterns where there are lots of data points. Maybe something with Morse Code?] Butterfly image
- People love those who can predict the future. But predicting what will happen next is not an easy task. Someone even predicted that the world will end on May 21st, 2011.
- Today is {insert date} and I am happy to be here and speak not about prophecies (based on assumptions and crystal balls) but about predictions, based on data and science. Imagine being able to predict not what will happen next month or next year, but in the next few weeks, or days, or even seconds, when it still counts. Would that be useful to your business? Wouldn’t it be satisfying if, as you’re flying to Barcelona, you received an offer for tickets to a show while you’re in the air, instead of a pamphlet in your mail that arrives two weeks later?
- But how do we learn how to predict? Let’s look at athletes. Psychology research shows us that the advantage top athletes have is based on several acquired skills, which all of us can develop and use to thrive in business. For top athletes, information used in the right context leads to timely execution, which gives them a tremendous advantage in the moment of truth, or when it matters the most. It is this combination that gives top athletes an advantage – at TIBCO we call this a 2-second advantage – that allows Federer to return a lightening quick cross-court winner or Kasparov to take a queen to checkmate. Top tennis players can predict what type of serve they will receive (and therefore return 150mph serve) because they know how to focus only on the most relevant cues in an opponents’ movement pattern. They know how to pick up clues about what the opponent will do. For instance, they look at the trunk and hips of their opponents to learn whether the shot will go to a forehand or backhand. Novices are likely to look at the forearm and the racket, which give very little information about where the ball will go. In other words, top athletes know where to look. Picking up only on relevant cues and reacting to them quickly leads to business growth. For example, a bank may monitor how long people stay on the phone in order to get help. If the waiting time is excessive, the rep must be careful about making a promotion. But “waiting time” and “excessive” are different concepts if you are on hold in Hong Kong vs. Singapore. In the former, don’t try to make a promotion if waiting time exceeds 20 minutes. If the latter, should 7 minutes pass by, better keep quiet. In either case, you adjust in the moment because you know what cues to look for. Finding the right cues is easy when you have access to information that has been packaged into meaningful patterns, based on many prior experiences.
- Take for instance the example of Garry Kasparov, who was the first chess player in history to play against Deep Blue, an IBM computer. Over eight days and six games, Kasparov threw his eccentric and hot-tempered moves in an ambitious man vs. machine battle. Animated and agitated, often throwing tantrums, right before the 40th move in the final game, Kasparov took his watch from the chess table and put it on his wrist (his emblematic sign that a match was nearly over). Three moves later, Kasparov had won. How is it possible that a man who can process only three moves per second could beat a machine that at the time could process 100 million positions per second? It turns out that processing speed was not the only thing needed for winning. What was necessary was access to lots of information derived from experience, from meaningful games and events that had been lived and learned. Deep Blue would eventually turn around and beat Kasparov a year later. At the following encounter, the computer was able to process 200 million moves per second but the win was attributed to another invention: the computer had been loaded with a knowledge base of opening games played by grandmasters over the last 100 years. Programmers had realized that in addition to computer speed, knowledge was indeed power. This type of meaningful knowledge, organized in patterns is what enables Amazon to complete 1/3rd of their sales on predictive behavior. Customers who bought this book also bought this book….Or Netflix to say “if you’ve liked this movie, you’re likely to like this movie.” Amazon and Netflix use this patterns while the customer is still in the experience, is still “in the game”. What type of customer behaviors would you be able to model in order to gain a 2-second advantage? When top athletes process information, they recognize patterns (unlike novices who see information as a blur), they see an ordered set of possibilities, which in turn makes them respond in a smooth, calm, targeted, economical way. Watch a tennis pro and you will appreciate the control and fine movement. Compare this with the lack of smoothness and unity from a novice (psychologists call this “muscle anarchy”). Translating this to business, how often do you see companies reacting in a hasty, uncontrollable way to something they did not expect? Do you work for such a company now? What patterns can you build that will enable you to respond in a smooth, calm, targeted, economical way? Prior patterns and optimal models become automated and this is why top athletes can usually spot the right move right away from a multitude of alternatives. Think of just the opening of a chess game. There are 30 ways to move one piece in the beginning, and 30 ways in which the opponent responds. This means that there are 800,000 possible moves after each player has moved one piece. A few moves after that, and we’re talking a trillion of possibilities. Eventually, there are more positions possible on the chessboard than there are atoms in the known universe. What are some events/transactions in your current business that could be automated so that you can start building models that may help you predict what your customers may do next? The amazing part is that top chess players do not waste time with moves that are unfavorable. They only concentrate on moves that have the greatest promise. In fact, in another experiment, where researchers had asked chess players to reason out loud the next move, researchers found that they were not thinking 4 or 5 moves ahead as you or I might suspect. Top chess players would normally identify the correct move right away. This is because much like the average English speaker masters about 20,000 words, the top chess player has mastered at least that many meaningful patterns from prior games. Immediacy equals timely execution. Access to the right information right away is not sufficient. Top athletes are successful when they operate in an optimal context. In one of the most famous experiments in psychology, two American researchers asked groups of chess masters and novices to look at a chess board containing 20-25 chess pieces, set up as they would normally appear in a typical game. Both groups were shown the boards briefly and then asked to recall the position of each piece. Chess masters could recall the position of every piece, while novices could recall six at the most. The researchers repeated the test, except this time, they arranged the chess pieces randomly so they would not resemble a real game. In this context, chess masters were no better than novices. Lack of context disrupts performance because it negates years of practice and experience and because it breaks connections that are meaningful to the next move. Attention to context is critical to success. In this down spiral economy, businesses must learn how to look at everything all at once because so many elements are interconnected.
- Overall, looking at the right information right away enables top athletes to adopt a strategic position a bit earlier. Meaningful and automated patterns provide immediacy. It is because of this combination that we exclaim as we watch an impeccable Beckham goal: Perfect timing! It is because of this combination that a customer receives a promotion from a telecom carrier right before they were ready to interrupt their service. Perfect timing. It is because of this combination that a credit card company can put a stop to potential fraud minutes later after a card is being misused by an unauthorized buyer. Perfect timing. Keep in mind that when thinking patterns are automated, they also free up psychological resources to think about additional strategy and looming emergencies – such as what to do when you’re down a few points or what to do when you’ve lost a few customers.