The Forrester Blog For Information & Knowledge Management Professionals

Predictive analytics/data mining

November 19, 2008

Enterprise Mashups Need Complexity To Create Value

Gilyehuda By Gil Yehuda
Those who drink the Web 2.0 Kool-aid live in a idealistic world where we can mentally connect a great idea to a great implementation of that idea. We live on faith that the great implementation will come, since there are plenty of smart people out there who will eventually figure out how to make value out of technology building blocks. Sometimes our faith is tested when the killer-app does not show up for a long time. But evidence can restore our faith.

When I first saw mashups, I thought they were pretty cool. The canonical examples of this technology were all about the placement of data points onto a map. With mashups you can visualize where Fortune 100’s top companies to work for are located, and you can find a mailbox nearby. It’s certainly nice to use once in a while, and maybe worth bookmarking. But will this alone transform a business? Likely not.

Sharing location information via an online travels social network, like Brightkite, FireEagle, Bluenity, Dopplr, or TripIt, is also pretty cool. Using the integration hooks into Twitter, Facebook or LinkedIn, I can begin to share location information with those I trust. I can post where I am located now, and where I plan to be in the near future. I believe there could be value in this activity, but it’s not yet transforming the way I use information into business results.

But I am now beginning to see how these services combine to build a useful application. The “aha” moment for me was when I stopped looking for one mashup, or one sharing app, and saw how companies can combine multiple streams to create value out of data. What if you take a map mashup, a calendar mashup, a travel micro-share feed, an events feed, and dataset from a CRM system containing the names of locations of my customers? I trust that smart people can take these and create value. Why? Am I drinking the Kool-aid? No – I see signals that indicate this is happening.

Look at the new LinkedIn application widgets that mash-in LinkedIn data. My TripIt tool reminds me of a future trip to London, and tells me that I have a few LinkedIn contacts there. Based on information in my LinkedIn profile, LinkedIn tells me about relevant upcoming events. I found an interesting event in London. Will my contact attend that event? What if they’ll be traveling to Boston when I’m in London. Doh! So close.

But I see the outline of a new pattern. Whereas each data mashup is interesting, the right combination can transform my work behavior. There’s a who, what, when, and where, that all have to intersect onto a map and onto a calendar.

I recently met Sanjay Vakil of LuckyCal, who understands this pattern well. He is connecting the dots to create transformative value out of data streams. His product has some growing up to do before it is ready for enterprise rollout. But his product today combines a mapping mashup (telling me which of my contacts are where I am going to be), with a calendar mashup (matching when contacts of mine will be near me), and with an events stream (telling me what other events are taking place there at that time). Hey, that's the pattern: a set of data streams intersecting to create valuable information out of available information – but onto multiple mashup surfaces.

Suddenly the neurons start to fire. We need more than a single stream of data pins on a map to get our attention. As the LuckyCal product matures, it can become the paradigm for an enterprise mashup - triangulation. If it adds the data streams that matter most to me, (e.g. my CRM data), along with other streams and network information, it results in new information. The triangulation of these data sets means that I could predict whom I meet and what to do when I plan my trips. Moreover, my manager would be able see where the team’s travelers are now, and where they will be in the near future. My sales manager could see which of us will be traveling nearby other clients, and she may want take advantage of the proximity opportunities. Travel still happens, but we can get more value out of each trip. Enterprises like to hear that.

So, if you combine two mashups and couple of data feeds, you can create transformative value from readily available information. I had faith this could be created, but now that I see signals that others are implementing solutions like this. I have renewed faith in the relevance of mashups to enterprise computing. It's just more complex than splashing a data set onto a map. That's OK, enterprises are used to leveraging complexity to create value. And mashups can be the building blocks to enable their success.

September 15, 2008

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William Band
Research coverage for Business Process & Applications professionals

Customer relationship management applications, customer experience management, stakeholder alignment, enterprise CRM
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Matthew Brown
Research coverage for Information & Knowledge Management professionals

Marketing and advertising, enterprise portals, intranets and extranets, information and knowledge management
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Peter Burris
Research coverage for Technology Product Management & Marketing professionals

Enterprise marketing platforms, marketing automation, high-tech, application development
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Bobby Cameron
Research coverage for CIOs

IT governance, risk, and compliance; the marketing of IT; serving the business; security and risk
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Marc Cecere
Research coverage for CIOs

Designing IT organizations, changing the culture of an IT organization, IT strategic planning
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Patrick M. Connaughton
Research coverage for Business Process & Applications professionals

Supply chain management services, supply chain management applications, enterprise mobility, RFID
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Alex Cullen
Research coverage for CIOs

IT organization; IT strategy, planning, and governance; organizational design and change management, IT management
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Boris Evelson
Research coverage for Information & Knowledge Management professionals

Information and knowledge management, business intelligence, OLAP, data warehousing
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Chip Gliedman
Research coverage for Business Process & Applications professionals

Customer relationship management, help desk/service desk, customer service and support, packaged applications
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Paul D. Hamerman
Research coverage for Business Process & Applications professionals

ERP, human capital management, financial management, business performance solutions
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Brian W. Hill
Research coverage for Information & Knowledge Management professionals

eDiscovery, archiving, records and retention management, enterprise content management (ECM)
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Bradford J. Holmes
Research coverage for Vendor Strategy professionals

Tech marketing tools and best practices; government, high-tech, tech marketing strategies
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Rob Karel
Research coverage for Information & Knowledge Management professionals

Information and knowledge management, integration technologies, metadata management, extract
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Rob Koplowitz
Research coverage for Information & Knowledge Management professionals

Information Workplace, collaboration strategy, collaborative platforms, SharePoint
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George Lawrie
Research coverage for Business Process & Applications professionals

Retail information technology; consumer goods supply chain; pricing, promotions, and revenue optimization; collaborative processes such as trade promotions management and sales; and operations planning
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Sharyn Leaver
Research coverage for Business Process & Applications professionals

Packaged applications, business process management, ERP, application strategy and selection
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Craig Le Clair
Research coverage for Information & Knowledge Management professionals

ECM, BPM, output management, document processing services
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Pete Marston
Research coverage for Business Process & Applications professionals

Customer relationship management, sales force management, software-as-a-service, outsourcing
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Kyle McNabb
Research coverage for Information & Knowledge Management professionals

Information and knowledge management, document imaging, eForms and information capture, enterprise content management
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Thomas Mendel, Ph.D.
Research coverage for Vendor Strategy professionals

Product portfolio strategies, mobile services, business service management, data center management
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Connie Moore
Research coverage for Information & Knowledge Management professionals

Information and knowledge management, business process optimization, IT organization, enterprise content management
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Leslie Owens
Research coverage for Information & Knowledge Management professionals

Information and knowledge management, taxonomy and classification, enterprise search platforms, text mining and analytics
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Natalie L. Petouhoff, Ph.D.
Research coverage for Business Process & Applications professionals

Customer service and support, customer experience, customer experience management, business strategy for customer experience
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Lisa Pierce
Research coverage for IT Infrastructure & Operations professionals

Voice services, telecommunications services by region, remote access infrastructure, networking
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Tom Pohlmann
Research coverage for CIOs

Business models, high-tech, corporate strategy, tech sector economics, product and solutions strategies
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Stephen Powers
Research coverage for Information & Knowledge Management professionals

Information and knowledge management, digital asset management, enterprise content management, Web content management
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Stefan Ried, Ph.D.
Research coverage for Vendor Strategy professionals

Enterprise architecture, Service-oriented architecture, application platforms and programming strategy; application development
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Ted Schadler
Research coverage for Information & Knowledge Management professionals

Real-time collaboration tools (instant messaging, presence, document sharing, etc.), cloud-based collaboration and email, mobile collaboration tools and applications, virtual worlds for the enterprise
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Claire Schooley
Research coverage for Information & Knowledge Management professionals

eLearning, information and knowledge management, videoconferencing, Web conferencing, enterprise collaboration, new workforce, retiring workforce
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Scott Tiazkun
Research coverage for Business Process & Applications professionals

Financial management; governance, risk, and compliance; financial management applications; security and risk
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Zach Thomas
Research coverage for Business Process & Applications professionals

Human resources management applications, compensation, recruitment strategies, packaged applications
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Tim Walters, Ph.D.
Research coverage for Information & Knowledge Management professionals

Web content management, enterprise content management, digital asset management, information and knowledge management
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R "Ray" Wang
Research coverage for Business Process & Applications professionals

Enterprise apps and ERP, software contract negotiations, software partnerships and ecosystems, customer data integration
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Doug Washburn
Research coverage for IT Infrastructure & Operations professionals

Green IT, IT organization, IT infrastructure and operations, IT management
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Gil Yehuda
Research coverage for Information & Knowledge Management professionals

Enterprise Web 2.0 and Social Computing; collaboration strategy, tools, and culture; virtual communities of practice; virtual team collaboration
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March 19, 2008

Oh No, Not Another 2.0 -- Database 2.0? Data Warehousing In The Cloud!

Jameskobielus_4By James Kobielus

Boris Evelson's latest post on free BI got me thinking about another type of freedom.

Boris commented on the newly announced beta of a gratis, lightweight, Panorama-powered BI/OLAP-engine add-on to Google's hosted apps. You know, whenever anybody mentions BI/OLAP, I think of analytical databases, hence data warehousing (DW). And when my thoughts turn to DW, I often wonder when these dimensional data stores will be let loose from their earthly tethers and begin to float free in the SaaS cloud. This is no blue-sky speculation, but rather an inevitability in a world shifting to subscription-based SaaS for on-demand delivery of all infrastructure and application services. Where database services are concerned, this trend even has a name in popular circulation: Database 2.0 (aka "cloud databases").

Let it be known that Google is one of the pioneers in Database 2.0, though they haven't tooted their horn or done anything particularly special in this regard (smaller SaaS solution providers such as Trackvia, DabbleDB, and Zoho have more full-featured Database 2.0 offerings than Google, albeit not particularly BI/OLAP/DW-focused). A year or two ago, Google went open beta (still in that phase, actually) with a hosted database service called GoogleBase. Now, from what I've seen, GoogleBase is not a general-purpose transactional or analytical database. And it’s certainly not a DW or data mart in the clouds. Instead, GoogleBase seems to be an online repository -- or rather, depository -- into which external parties submit structured data for Google to crawl and index deeply for access from Google's big whompin' search engine.

Even more noteworthy is Microsoft's recent foray into the Database 2.0 space -- a move that some might consider a "validation" of this approach in the eyes of enterprise I&KM professionals. Microsoft has just rolled out a beta of its hosted SQL Server Data Services. The vendor has started to host services that have heretofore have been available only from SaaS partners. This is, of course, a key piece of the Redmond WA-based vendor's begrudging effort to push more solutions into a Microsoft-hosted SaaS cloud. However, from what I can see so far, Microsoft is simply hosting a subset of the functionality of its general-purpose RDMBS platform for OLTP and OLAP. However, Microsoft has not specifically optimized SQL Server Data Services for OLAP, unlike any truly scalable BI/OLAP/DW platform.

Back to Google for a sec. What I fully expect from them in the coming year or two -- and from every SaaS cloud everywhere before long -- are feature-complete, hosted, subscription-based DW services for high-performance, high-volume, complex analytics. Naturally, this cloud should be called DW 2.0. It should leverage the full virtualized, distributed, scalable, grid-enabled computing fabric that the Googles of this world can bring to bear on the very largest structured data sets, most resource-intensive query-processing tasks, and richest visualizations imaginable. Per Boris's suggestion, it could even serve as a supremely scalable BI, data mining, or predictive analytics "sandbox" for developers and power users who have no other speedy, cost-effective alternatives for procuring the necessary horsepower for various projects and production requirements.

I second Boris’s challenge: Google should consider integrating the Panorama OLAP-engine add-on (remember, it's just a beta) with a more analytics-enabling future version of GoogleBase (which is also still a beta). In so doing, Google -- if it eventually decides to go into full production with all this -- would be able to offer full-featured DW and BI services on a hosted platform that is as infinitely scalable as the concatenated string of Os inside the ever-extensible company name that displays within its multipage search-result screens. I also share Boris's concern that whatever hosted OLAP/BI/DW services Google eventually offers may lack enterprise-grade metadata management, data cleansing, data-source connectivity, security, and other key features.

I also expect Microsoft to evolve SQL Server Data Services in the DW 2.0 direction, an effort that no doubt would intensify if Mr. Ballmer succeeds in grabbing Yahoo. I'd like to see Microsoft cross-synthesize SQL Server Data Services with any hardware-partner-powered OLAP-acceleration approaches it may or may not be developing under its DW appliance initiative. At the very least, I'd like to see Microsoft provision some seriously scalable DW horsepower in its data center, perhaps through a partnership with Teradata.

Clearly, DW 2.0 services will need to be an order-of-magnitude more powerful than what we've come to expect under the first generation of SaaS-based BI/DW offerings on the market. Whether dedicated to a single customer's requirements or divvied up on a shared-tenant basis, DW 2.0 could be the biggest, baddest, most virtual DW "appliance" of them all. And it would be another key step in the progressive virtualization of the entire SOA stack, apps, middleware, hardware, and data services across the  Enterprise 2.0 or Web 2.0 fabric.

Oh yes, yet another 2.0 -- or two -- for you. Wouldn’t it be interesting if Google and/or Microsoft acquired a DW appliance vendor? I would not be at all surprised if announcements such as these precipitated from the cloud of pregnant possibilities.

And is it too far-fetched to imagine that Microsoft might turn around and acquire Teradata if the Yahoo takeover falls through? My crystal ball's still a bit cloudy on the matter.

But, hey, I'm free to speculate.

February 15, 2008

Complex Events, Simple Experiences

Jameskobielus_6By James Kobielus

Before the week is out, a few more thoughts inspired by various things I experienced at and around Forrester's Enterprise Architecture (EA) Forum last week in beautiful (but surprisingly chilly) Coronado, California.

What stuck with me was the presentation and demo by Kevin Lynch, CTO of Adobe. Though I was already quite familiar with Adobe’s Flex technology for rich Internet applications (RIA) technology, I liked the fact that Lynch presented Flex this time around as a business tool--in other words, as an interactive visualization technology for business intelligence (BI), business performance optimization, and event-rich analytics. All of which made perfect sense in a forum for enterprise architects.

As I was watching the demo, I began to think that RIA can be a double-edge sword, where BI is concerned, in terms of RIA’s potential to deliver meaningful, actionable intelligence for decision support.

On the one hand, as Lynch demonstrated, BI application developers can easily--if they don’t restrain themselves--craft any arbitrarily complex configuration of dashboards, scorecards, graphs, reports, query boxes, tickers, widgets, pop-up windows, and other visual (and audio) UI elements to deliver every imaginable form of intelligence to the user through every device or application at their disposal. And, in fact, as more BI environments begin to deliver more real-time event-driven refreshes direct-from-the-source, the more the potential for overburdening the poor end user’s overfull cranium. Where CEP for I&KM is concerned, this can easily degenerate into a nightmare scenario of information overload.

Or the BI/CEP application developers can deliver simplicity. They can use back-end event engines, business rules engines, and other infrastructure to conceal distracting complexities. Earlier that week, I was meeting with a vendor that provides real-time DW, plus in-database analytics, plus rules engines that can deliver, triggered by streaming data, simple recommendations through an Information Worker’s BI environment. For example, the DW/CEP/BRE/analytics environment might provide account reps with crisp, time-sensitive, context-sensitive recommendations to respond to an irate customer while they’re still on the phone--to keep them from bolting to the competition.

All of which brings me to a closing thought re this particular post. The problem with the term “complex event processing” is that it seems to imply a complex UI--hence, that CEP's potential user base is limited to rocket scientists, Wall Street quants, IT industry analysts (gasp!), and other folks who are professionally obliged to handle (indeed, embrace) complexity.

But complexity is part of the problem, not the solution, where CEP for I&KM is concerned. We can’t stop the world of business from growing more multifaceted. But we can and should filter it all down to the simplest, most meaningful, most actionable experience, targeted specifically to each user, and contextualized precisely to each and every occasion.

Down to a pure and beautiful crystallization.

February 11, 2008

Complex Event Processing (CEP) For I&KM — Mouthfuls, Morsels, And Meaningful, Manageable, Multifaceted Streams of Real-Time Intelligence

Jameskobielus_7By James Kobielus

This past week’s Forrester Enterprise Architecture (EA) Forum was quite an excellent experience. Being new to Forrester, it was a splendid opportunity to introduce myself to our customers, engage them in face-to-face inquiries, and present my research priorities. Not being new to the analyst space, it was also a chance for me to re-introduce — hence recontextualize — myself, and my focus areas, within the Forrester universe of research client groups, orbits, and domains.

As far as “what I cover” elevator pitches go, mine is two-thirds nailed down, not requiring any excess breath to explain. First and foremost, within the Information and Knowledge Management (I&KM) orbit, I’m Forrester’s lead analyst for Data Warehousing (DW). Secondly, I’m also the lead analyst on Predictive Analytics and Data Mining, an area that clearly plays into my DW coverage (analytic data marts, for example).

But my third focus area is more of a mouthful. In my one-on-ones at last week’s forum, I had to resort to drawing messy diagrams full of acronym balloons and wayward connecting arrows to contextualize it in the larger Forrester — and enterprise architecture — schemes of things. Here now comes another attempt, purely verbal this time, not necessarily elevator-pitch-perfect (still needs intensive nuancing), but hopefully delivered in digestible morsels that Forrester customers will find thought-provoking and inquiry-generating.

My third lead focus area is Complex Event Processing (CEP) for I&KM. At the EA Forum, I was quick to point out that Forrester already has a lead analyst for CEP: Charles Brett, who approaches the topic from an Application Development and Program Management perspective and has just published an excellent report on CEP.

As the “for I&KM” tag indicates, I’ll be looking at CEP in a slightly different context: as an enabler for truly real-time BI, predictive analytics, and business performance optimization. Indeed, most CEP applications rely on the BI portfolio of interactive visualization, dashboarding, scorecarding, reporting, query, predictive analytics, and data mining tools to support agile response and proactive coordination around real-time, emerging, or breaking business opportunities and threats. Behind it all is a low-latency middleware fabric that enables continuous monitoring, aggregation, correlation, and filtering of event data captured from operational applications, business process management systems, databases, and other sources.

So far, CEP has had only a minimal footprint in the BI arena, mostly because BI applications still rely primarily on historical data that has been consolidated in DWs, hence provide, at best, "near real-time" refreshes. Where enterprises have ventured into truly subsecond-latency CEP, they have traditionally implemented is as a stovepipe separate from their BI environments. CEP infrastructures typically incorporate their own, distinct, event-optimized service layers for interactive visualization, dashboarding, modeling, repository, rules engine, resource connection, and administration.

However, it’s only a matter of time before most BI vendors partner with CEP pure-plays, or acquire them outright, in order to strengthen their real-time functionality. We expect to see SAP/Business Objects, SAS, IBM/Cognos, Oracle/Hyperion, Microsoft, Information Builders, and MicroStrategy venture into the CEP arena in the next 1-2 years. Likewise, it’s very likely that a now-independent Teradata, which has taken the lead in real-time DW, will snatch up a CEP vendor to build out its real-time BI/DW portfolio. IBM's recent acquisition of CEP pure-play AptSoft shows that it is serious about CEP for I&KM, as does TIBCO's  acquisition of Spotfire.

Rest assured: I won't cover CEP as a stovepipe. You can expect to see CEP — as an enabler for real-time analytics and business optimization — incorporated as a cross-cutting theme throughout my Forrester coverage areas.

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