BI in Action Blog
|
April 08, 2008
Web 2.0 Will Reshape the Face of BI 
"Tectonic forces" are reshaping the business intelligence market as we know it, according to RV Ramanan, head of global delivery and chief software architect for Hexaware Technologies. These range from mergers and acquisition activity sweeping the market, to an increasing emphasis on pre-built analytics. Ramanan recently provided me with his insights on the forces that are reshaping BI as we know it. For example, he points to Web 2.0 as a new driver of a new breed of BI. He notes that while the concept of Web 2.0 was only coined four years ago, the rise of the collaborative Web that it's engendering "may have such profound impact on the business intelligence space, one that seems almost unbelievable for old fashioned data warehousing folks." The combination of BI with Web 2.0 approaches is "having a compounding effect on need fulfillment, which, for the information world means distributed centers -- and not just a data warehouse -- acting as service centers to provide information to the end consumer." He also notes that the reference data or metadata may also see distributed silos yet -- unbelievably -- with single versions of truth." Software as a Service, another facet of Web 2.0, also is reshaping the market as we know it. "The concept of software licensing as is prevalent in the BI world may also go a paradigm shift and may extend beyond SaaS, with a redefined paradigm of revenue sharing, like the telecom industries, as one may both be the supplier and consumer of information." Ramanan also sees the following trends for the year ahead in BI: The mergers and acquisitions that have taken place across the industry may drive more more enterprises to adopt suites, versus best-of-breed products. "Companies may want to align with the product vendor’s BI vision to get ample vendor support in product upgrades, product enhancement and availability of trained resources to implement the solutions." However, there will still be plenty of point solutions sold as well, especially for reporting, data integration, analytics, mining and making scorecards. The increasing "customer centricity" of businesses. "Based on our experience, in industries where there is a higher customer centricity like airlines, retail, banking, healthcare and telecom the need of analytic CRM, data mining and predictive analytics, operations research driven analytic methods and off the shelf analytic CRM solutions will be the key." Emphasis on performance management and financial performance management, versus simply "reporting". Ramanan observes that "across all verticals, the need of performance management solutions will continue to hold steam. There will continue to be need of more budgeting solutions, expense control tools, consolidated balance sheet analyzers and tools ( like EVA, six sigma, balance score card) that assist a better performing organization." Posted by joemckendrick in Business Intelligence • Decision Support • Management | Permalink | Comments (0) | TrackBacks (0) February 27, 2008IBM Leverages Cognos
My colleague Elizabeth Book Kratz caught this nugget of valuable information related to the IBM-Cognos acquisition, buried in IBM's latest announcement about its new System z10 mainframe: IBM’s Information on Demand strategy is helping customers gain access to the right information they need, when they need it, along with key business insights needed to address and respond to changing market demands. By deploying Cognos 8 BI for Linux on System z, customers will be able to easily report and analyze hundred of millions of transactions directly on the mainframe - ensuring everyone across the organization can quickly identify and respond to critical business trends. IBM is also announcing the immediate availability of DB2 for z/OS Value Unit Edition, which provides a new one-time-charge offering that enables the deployment of new application workloads. This offering strengthens the role of System z as a cornerstone for key business initiatives such as SOA, Data Warehousing, Business Intelligence and packaged applications such as SAP. DB2 for z/OS Value Unit Edition and IBM Information Server enable System z clients to further deliver trusted information for their dynamic warehousing requirements. In addition, IBM will bring new Master Data Management capabilities to System z in the second half of this year. This will include the InfoSphere Master Data Management Server for Linux on System z, which allows businesses to centrally manage customer, product, and account data for use across an enterprise. Posted by joemckendrick in BI Vendor Watch • Business Intelligence • Data Management • Decision Support • Performance Management | Permalink | Comments (0) | TrackBacks (0) February 05, 2008Taking People Out of the Equation
"Why are enterprise applications so dumb?" With an eye-grabbing headline like that, who could ignore our own James Taylor's latest message that true actionable analytics require the ability to respond automatically and intelligently to events? Today's BI and analytics solutions actually have a long way to go before they truly begin to make a difference and deliver value to organizations. Why? Because enterprise applications still "rely on human intelligence." Is this such a bad thing? Well, James provides a rundown on where the process gets slowed considerably: "Humans must use dashboards and reports to learn from their data, most decisions are managed with work lists, someone has to log on and act-on work list items before a process continues, and most alerting and monitoring functions are focused on telling someone what has happened rather than on doing something about it." Even the hot tickets of the moment -- Complex Event Processing/Business Activity Monitoring -- will fall short, James warns, "unless systems can respond intelligently and automatically to most events and this means making decisions about how to act without this reliance on people." I agree with James that automated decisions triggered by events are the next big step in analytics. However, it seems that this is a huge leap for many organizations to take. One, because it requires a great deal of trust in systems acting on an unattended basis. We are seeing a lot of rudimentary automated decisioning occurring at a systems and nuts-and-bolts levels -- with self-healing networks, for example, that can automatically reroute workloads if transaction demand spikes. Some e-commerce Websites will provide automated approvals for loans or other transaction elements. But, again, it may take time before these automated pathways start being applied to critical business decisions that affect jobs and treasure. Posted by joemckendrick in Business Intelligence • Decision Support • Management | Permalink | Comments (0) | TrackBacks (0) January 31, 2008I Like This Quote: 'In BI, Strategy is Destiny'
"In BI, strategy is destiny... or should be." With these words, Jill Dyche, a leading thinker and consultant in the business intelligence space, admonishes BI professionals to keep their work in perspective. "In our rush to proselytize our existing capabilities, we forget what’s in the business’ pipeline. Most of this has to do with the lack of sustained and regular business requirements gathering." Jill hits the proverbial nail right on the proverbial head. All too often, the emphasis in solutions is on the technology, and efforts go into making sure all the bells and whistles are ringing and whistling as they should. I see this as the greatest failing in service oriented architecture, and this is also a failing in data management. To be sure, businesses suffer from failures in imagination, too. As Jill puts it: "it also has to do with the business’ failure to think big. After all, you’ve reengineered your supply chain and you now have query access into your ERP system. And your CRM project is finished, right? (The answer should be no...) Irrespective of your industry or market segment, your customers are very likely taking you for granted, and their likelihood to attrite is—as 2002’s popular colloquialism put it—only a mouse click away." But, back to BI and data management side of things -- Jill observes that BI and data managers she has worked with have done stellar jobs in timely delivery of BI reports, speedy data loading, or changed data capture. However, she adds, how many can say they have effectively addressed any of the following business inititiaves? - "Real-time individualization of customers, support of customer do-not-solicit requests, or customer and product hierarchy management" There are incredible solutions out there now in the BI and analytics market. However, they won't help the business if they're not being leveraged to their full capacity. Posted by joemckendrick in Business Intelligence | Permalink | Comments (0) | TrackBacks (0) January 30, 2008Wall Street Journal Columnist Heralds Death of 'Gut Instinct'
"When we remember 2008, it’s likely we’ll utter the following epitaph: Here lies gut instinct, once the basis of all business decisions. That’s because 2008 will be the year that businesses finally gain access to data that’s good enough to take quick action on." Ben Worthen, writing in The Wall Street Journal, observed the findings of Gartner's latest CIO survey that point to increasing reliance on business intelligence tools, and sees the fading of a business staple: gut instinct. Is this a good thing? Of course, the very purpose of this blogsite is to promote greater automation in information-gathering and decision-making, versus making unsubstantiated decisions that could affect jobs, careers, and millions of dollars in organizational treasure. We are seeing great strides being made in BI -- the past few years have been very much a so-called "inflection point" in the progress of these systems. We now have digitized every aspect of business operations, from point-of-sale to production. We have all the data needed to look at where a business is, and to some degree, where it's going. Worthen spoke to Gartner's Mark McDonald, an author of the survey of 1,500 CIOs, who noted that for the third year in a row, CIOs said that “business intelligence software” was their top tech priority. Now, IT departments are rolling out new tools "that let managers make decisions based on these trends." But is it possible to rely too much on cold, hard, data and charts, versus instinctual serendipitous knowledge? I think great decisions will still need to rely on both. But even our decisioning capabilities -- acting on all this business intelligence data -- is getting a tremendous boost from technology. As ebizQ colleague James Taylor observes in his latest post, "traditional BI tools are not, perhaps, the best way to get competitive advantage." Instead, James advises, "Enterprise Decision Management (EDM), or Business Decision Management, is the approach you need - it's an approach for automating and improving high-volume operational decisions. Focusing on operational decisions, it develops decision services using business rules to automate those decisions, adds analytic insight to these services using predictive analytics and allows for the ongoing improvement of decision-making through adaptive control and optimization." BI is just data, but putting actionable decision-making capabilities behind it makes it a powerful competitive weapon. Posted by joemckendrick in Business Intelligence • Decision Support • Management | Permalink | Comments (1) | TrackBacks (0) January 23, 2008New Approaches to BI are Brewing
Consumers are a fickle lot -- tastes may change from day to day. How do you keep them engaged with your brand and drive the market, and keep on top of business operations from across the globe? A real-time data warehouse helps. Katrina Coyle, BI manager with Molson Canada, recently explored the ways her company is leveraging new technology approaches to keep up with fast-changing trends across the beverage market. Her presentation was part of a new ebizQ Webinar I moderated, addressing the fast-changing world of business intelligence, which also featured noted author Don Tapscott and SAP's Lothar Schubert. (Audio replay available here. For highlights of Don Tapscott's remarks, check out my previous post here.) "We’ve been brewing beer for a very long time," Katrina noted, stating that "when you’ve been doing something as long as we have, you get a lot of habits that are pretty well ingrained. Trying to shaking the business out of those habits is a challenge." Molson's strategy to transform its organization includes reaching out to a new generation of younger adults through Web 2.0-based marketing strategies, and leveraging service-oriented architecture and data warehouse approaches to build its brands across the globe. An important emphasis is real-time analytics, Katrina said. "We are constantly having to shift and change and shift and adjust very quickly to changes in the marketplace, " she explained. "We all have to be extremely agile. You can’t spend a week trying to figure out whether the promotion is successful. You have to be able to react within hours." It used to be that companies didn't know if a promotion was successful until then end of a quarter, if then. Real-time analytics can look at patterns and trends and provide insights if something is working or not, enabling a quick change in direction. For example, one trend that Molson was able to jump on fairly rapidly was a sudden craze for cold beer in UK pubs -- long bastions of warm beer. Katrina explained that each of its global sites have their own go-to-market models, but all this information needs to be rapidly assimilated. "We have a data warehouse, with lots of information coming in different ways," she said. "It's not necessarily all coming from a centralized ERP system. We also have data coming in from AC Nielsen, for example. "We’ve got to bring that data in, and make sure that it has a harmonized look, so our business can actually make tactical decisions on it." By adopting in-memory technology available through SAP's BI Accelerator, Katrina reports that Molson has been able to move data quickly through its data warehouse. "We’re able to process data now in real time in our warehouse -- we’re not tied to a load once a day or once a week." (Audio replay available here.) Posted by joemckendrick in Business Intelligence | Permalink | Comments (1) | TrackBacks (0) January 19, 2008Tapscott: Web 2.0 is Reshaping Business Intelligence
I had the opportunity to moderate an ebizQ Webinar on the fast-changing world of business intelligence, with noted author Don Tapscott, Katrina Coyle, BI manager with Molson Canada, and SAP's Lothar Schubert. (Audio replay available here.) Don Tapscott, who broke new ground in 1996 with his book, The Digital Economy: The Promise and Peril of Network Intelligence, and recently co-authored Wikinomics: How Mass Collaboration Changes Everything, said BI is on the verge of a revolutionary transition. Tapscott sees the Web 2.0 world -- with its high degree of collaboration -- changing the face of BI, to "collaborative intelligence." Prior to the introduction of Web 2.0 methodologies, he explained, internal data had "been accessible in various limited ways through traditional ERP reporting systems, MIS and business intelligence." Now, Tapscott continued, "for the first time, this is all being supplemented by massive quantities of additional data that is created through these new models of collaboration, as consumers and employees use the new tools of collaboration -- wikis, blogs and social networks." "The marriage of this new accessible data with the firm’s traditional internal data creates an unprecedented challenge, as well as an opportunity to gain insight into the behavior of the company’s most important stakeholders, and to translate that knowledge into success in the marketplace." The speed of Web 2.0 processes is also changing what end-users expect from BI approaches as well. "Think about if you do a Google search, you get the results back instantly. If the results took half a minute, or five minutes, or 10 minutes, you’d probably stop using Google so much. Traditional BI was kind of like that -- which is part of why we didn’t use it so much Because you’re calling out to a disk, basically." In-memory technologies are also making new generation BI technologies lightning fast as well. Audio replay of the ebizQ Webcast, "The New Paradigm for Business Intelligence - Collaborative, User Centric, Process Embedded," is available here. Posted by joemckendrick in Business Intelligence • Management | Permalink | Comments (0) | TrackBacks (0) December 31, 2007BI, Delivered from the Cloud
A new report in Knowledge Management confirms a trend that began emerging over the past year -- business analytics delivered via Software as a Service. "More and more business analytics software providers are moving to address increasing market demand for software that is updated frequently, hosted off-site and purchased on a subscription basis," KMWorld notes. Factors propelling this trend include corporate budget constraints on traditional software, limited development resources for in-house BI software, and increasing maturity of BI-over-the-wire solutions. The authors note that they don't expect the whole BI world to move to the Cloud anytime soon, however. As they put it, the shift will be gradual, and both SaaS and traditional, on-premises, licensed software will co-exist within enterprises for a long time to come. A few months back, while preparing a report for Database Trends & Applications, I spoke with Tracy Trawick, consumer insights manager for Hamilton Beach, which employs such a hybrid approach to BI, getting the best of both worlds of SaaS and on-site. Hamilton Beach's market research department primarily relies on on-site software, but lately has begun tapping into SPSS's SaaS-based platform to cover a growing workload that end-users simply don't have time to sort through. "All the data manipulation on the back end is supported by SPSS," Tracy said. "We're using it for very template-based iterative projects so we don't use up a lot of programming time. I don't have the time to learn the logic and the programming tools." Tracy uses the SPSS SaaS platform to create and launch consumer market research surveys, and manipulate the data as it comes in. However, she still employs SPSS on-site software for more complicated projects. In line with the Hamilton-Beach example, I also spoke with Oliver Halter, partner with Diamond Management & Technology Consultants, who concurred that "companies currently tend to use SaaS on the fringe of their operations." Oftentimes, "this also means that the SaaS partner provides an additional service that makes it worthwhile for the company to outsource the software and function. Companies tend to have an easier time switching to SaaS if the data managed in these systems is 'non core' and is not considered a competitive advantage." Moving to a SaaS model has its share of challenges, however. Dilip Wagle, a partner with McKinsey & Company, told me that integration remains a big challenge, especially for companies seeking to leverage solutions from the Cloud. Dilip cautioned, for example, that "counter to the promise, the deployment and integration effort is not zero. Most effort is centered on integration and customization effort of single SaaS applications, especially in the enterprise space. Moreover, as companies increasingly move to more SaaS applications, integration challenges will manifest themselves in terms of integration with other SaaS applications." Data security and availability is also another challenge, and perhaps the achilles' heel of SaaS arrangements. What happens if the application provider goes out of business, or has a major network outage? SaaS customers need to make sure they have robust backup systems in place. Security raises more red flags. As Dilip warned, "pure 'in-the-cloud' services imply that all the customers data are essentially stored off-premise in a data center owned or contracted by the service provider. In the event of data center failure on the part of the service vendor, the customer has no recourse but to hope that data were appropriately backed up and managed in a secure fashion. The problem can be exacerbated if the SaaS vendor in turn, outsources back-end data center operations to yet another third party. This can complicate accountability and liability in the event of failure or security breaches." Posted by joemckendrick in BI Vendor Watch • Business Intelligence | Permalink | Comments (0) | TrackBacks (0) December 30, 2007Rumors of BI's 'Death' are Greatly Exaggerated
In a 2007 year-end wrap-up, InfoWorld declared BI to be "dead," citing it as it's ninth-most underreported story of 2007. Hmmm. An entire industry and technology sector disappears under our noses, and it only rates number nine as a news item? Actually, it appears the author, Bill Snyder, was being somewhat facetious, mocking the pundits that predicted the end of the market as we know it, resulting from the mega-acquisitions of leading vendors that took place over the past year -- Business Objects being gobbled up by SAP, Hyperion by Oracle, and Cognos now falling into IBM's orbit. But, keep in mind that there is still a huge market remaining with players such as SAS, SPSS, MicroStrategy, and Actuate. Oh, and what's the name of that vendor out in Washington state again? I think they have something or other linked to their database product. As Rob Tholemeier, a former industry analyst turned private investor, put it, the acquisitions of the big players creates space for other companies to flourish. The same thing happened to the database market, he notes: “There are more database companies around now than when Informix was purchased.” There's going to be plenty of competition and solutions for a long time in this market, with enough room for everyone. Long live BI. Posted by joemckendrick in BI Vendor Watch • Business Intelligence • Microsoft | Permalink | Comments (1) | TrackBacks (0) December 11, 2007Best Practices for Turning Useless Data into Actionable Information
ebizQ colleague James Taylor points to a new report out of Forrester (available to ebizQ members for premium download here) that discusses Business Intelligence strategies organizations need to follow in the years ahead. In the report, Forrester analyst Boris Evelson not only provides guidance on BI strategy, but also examines the meaning behind BI. James quotes Evelson's definition of BI: "A set of processes and technologies that transform raw, meaningless data into useful and actionable information." BI has certainly had its issues, as Evelson explains. "Even after decades of BI usage, most organizations find best BI doesn't sound like much fun, does it? To smooth things a bit, or at least relieve such angst, Evelson compiled a list of best practices in which to get BI started or kick-started within organizations, some of which are highlighted below. His advice overall: "Don't treat BI strategies as a project -- treat BI as a journey." Pick a senior executive sponsor who understands that measurement is management: "Look for an executive who has the entire picture of the enterprise objectives, goals, and strategies, and who has the know-how to link and translate them into the key performance indicators (KPIs) necessary to support these objectives." Put data governance and data stewardship in place: No effort will succeed without common data definitions across all business units. And, as noted above, measurement is vital, Evelson says. "Start small and pick the KPIs that are essential to operate the business. Pick only 10 to 20 KPIs and build the initial standards and governance with them in mind. Come up with standardized definitions of quality, sources of truth for the data, and business rules to calculate these KPIs/KPMs (key performance measures)." Conduct a "current state analysis:" Make sure that this analysis "includes all components of the BI stack and all of the processes and organizational structures surrounding your existing BI implementations. Both business and IT stakeholders have to be involved in this initiative." Define a logical and physical data architecture: Decide whether you will be deploying data marts, a data warehouse, or "semantic layers" (or EII, enterprise information integration architecture) that accesses operational data sources. Know they user: This sounds simple enough, but most organizations have a wide variety of user types that will have different expectations of the BI system. Evelson points out that there are typically three broad classes of users: strategic, tactical, and operational. For example, strategic users make very few decisions, but the decisions these users make have profound consequences for the business." These users "favor aggregated data that extends across business domains — they ask the big questions and need the big picture to do so, too." Operational users, on the other hand, "work on the frontlines — for example, the hundreds or perhaps thousands of representatives in call centers. These users don’t need cross-domain data, just data within their own set of applications. They don’t need the big picture, just a very granular view of many small pictures." Evelson also adds that most BI applications and data will require at least five terabytes' worth of storage space over the next five years. Lastly, addressing the biggest stick in many BI pundits' craws, Evelson advises not trying to fight BI-by-spreadsheet. "Excel’s local control, flexibility, and complexity are perfect matches for data-intensive analysts who like to run every scenario with constantly changing data. No BI tool is going to replace Excel entirely; the trick is a coexistence strategy between IT and the business." Or, as my colleague Michael Dortch (of RFG) so aptly put it a few months back: "Spreadsheets: can't work with 'em; can't work without 'em!" Posted by joemckendrick in Business Intelligence | Permalink | Comments (0) | TrackBacks (0) November 28, 2007BI on BI? Big Iron Still Delivers Data Punch
Big iron -- mainframes -- can be a powerful platform for managing BI data. Many organizations run their data warehouses on mainframes. However, many mainframes still lock data away into silos, requiring a lot of effort to extract information into systems running BI and analytic tools. That's some of the findings of a new survey of 430 members of the SHARE, which is primarily the IBM mainframe user group. I conducted and published the study as part of my work with Unisphere Research, which manages surveys for many user groups. The new SHARE study reveals that many mainframe systems are at the center of efforts to achieve enterprise data integration, as well as to extend applications into service-oriented architectures. Mainframes are evolving into a leading role both as a source of mission-critical data, as well as key services. However, the survey also revealed that most mainframe data is still locked up, and most integration efforts are still done with hand-coded scripting. There are proactive efforts underway to better integrate mainframe data with more distributed data environments, and to be able to deliver this data in real time, meaning within seconds. In addition, many organizations are showing an interest in service-oriented architecture (SOA) as a way to better leverage mainframe resources. The study found that at least half of the surveyed sites still use hand-coded scripts to move data from their mainframes to other platforms or databases. Mainframes store and manage much of an organization's enterprise data. However, most of this data remains inaccessible in these environments. In addition, most mainframe sites share only a small portion of their data across enterprise systems. A majority, however, do need to make what data is available viewable on a real-time basis. SOA is also an important initiative at many SHARE member sites. Close to one out of four respondents' companies have SOA efforts now in progress, and another one-third are planning or considering SOA. At least half of these efforts will employ mainframes in a central role. Most SOA efforts do not yet have an enterprise reach. However, many companies are preparing SOA to meet real-time requirements. Approximately 40 percent of companies are deploying or considering event-driven architecture-seen as a real-time adapting of SOA. Posted by joemckendrick in Business Intelligence | Permalink | Comments (0) | TrackBacks (0) November 26, 2007Looking Back at BI -- From the Year 2018
Will 2008 be the year that the long-fragmented BI market finally starts to congeal? Ten years from now, will mega-BI platforms be as commonplace as mega-ERP systems? Is this a good thing? Noted BI analyst William McKnight says this is exactly what is happening. With the wave of acquisitions that swept the BI world over the past year, companies may finally start to rally around popular solutions. As he notes in a recent blog post: "I think the business books in 2018 will look favorably on the recent moves of SAP, Microsoft, IBM and Oracle. The signal that BI had evolved to this point in maturity was when Oracle bought Hyperion." Don't expect an immediate market makeover, however. "I don’t expect the recent acquisitions to impact clients for quite some time," William says. He advises companies to start looking at the emerging suite solutions out there -- "to look ahead and figure out who they want to be in their approach to the market – a mega-vendor purchaser with a relationship and a commensurate built-in culture, or a company who values independence and will incubate their own culture. I believe 2008 will start to bring back the notion a 'primary' vendor." Posted by joemckendrick in Business Intelligence | Permalink | Comments (0) | TrackBacks (0) September 29, 2007BI 101
There's no doubt that business intelligence has crossed the chasm from the exclusive domain of specialists sifting through mounds of archived data to an everyday operational tool that leverages real-time data feeds for all kinds of workers. If you've been using these tools for a while, you probably know the lay of the land. For those just starting to explore the possibilities, the choices and levels of capabilities can be overwhelming. In this new report in InformationWeek, Mary Hayes Weier provides a practical overview of how to sort through the maze of business intelligence products on the market. Weier then reinforces points made in my previous post -- proceed with caution to BI democracy. "It's great that software vendors are creating BI apps for all kinds of workers, but proceed cautiously. If people aren't properly trained or if they query data in unconventional ways, the end result could be imprecise information, sluggish system performance, and ultimately bad business decisions. Choose the right tools, set policies, train users -- then outpace the competition with the power of your analysis." Well said. Posted by joemckendrick in Business Intelligence | Permalink | Comments (0) | TrackBacks (0) September 27, 2007BI 'Democracy': Too Much of a Good Thing?
One theme that is constantly being voiced by BI vendors and proponents these days is the deployment of these tools in more of a "democracy" setting -- making analytic capabilities to as many employees across the enterprise as possible. In essence, moving toward an analytocracy. (Like that word?) This is in line with the long-term drive to flatten the organization chart -- pushing decision-making as close to the line as possible. As I mentioned in a post a couple of months back, in a survey I helped conduct with Cognos and the Oracle Applications User Group, we found that we're still a long way off from the ideal analytocracy. BI reporting remains tied up in IT departments, and is still limited to analysts or certain decision makers. The majority of respondents to the OAUG survey report that it takes more than three to five days to get a report out of IT. Overall, the survey found, fewer than 10 percent of employees have access to BI and corporate performance management tools. Lately, Ann All over at IT Business Edge has wondered if perhaps we should tread with caution before rushing into unfettered access to BI. She points to a Computerworld article that describes the challenges two major corporations had when they opened up their BI more to the masses. For example, Del Monte had to wrestle with having several departments using different sets of business rules and filtering to produce reports, resulting in multiple different versions of the truth. The company’s director of business systems and decision support is quoted as saying that “too much flexibility and ad hoc capabilities in the hands of the wrong person can result in islands of autonomy, homegrown subsystem processes and the proliferation of multiple versions of the truth.” Valero Energy Corp. also encountered similar issues, with users running reports on multiple different versions of data before it consolidated all its reporting into a single data warehouse and set of front-end reporting tools. However, the company had to provide a great deal of end-user training and education to build usage of the new environment. “'Don’t assume, ‘If we build it, they will come,'" the IT director said. Posted by joemckendrick in Business Intelligence | Permalink | Comments (0) | TrackBacks (0) September 22, 2007A Tussle Over Semantics About Semantics
In my most recent post here at BI in Action, I attempted to wade into the often-arcane waters of Semantics. Many pundits have taken to calling the phenomenon -- whatever form it takes -- "Web 3.0," implying that things will move to a whole new level. Now, it seems Gartner has voiced its displeasure at the term "Web 3.0," saying that new technologies such as virtual worlds and the Semantic Web do not deserve their own new label. According to Gartner analysts, speaking at a recent conference and quoted in Network World, since things such as Semantic Web and virtual worlds are “not providing the same kind of fundamental change as blogs, wikis and social networking tools,” they don't qualify as a dot-oh release. As analyst Gene Phifer put it: “It’s not going to be another era like Web 2.0. However, there will be some very interesting innovative things coming out. If you’re in love with numbering schemes, maybe it’s Web 2.1.” Gartner projects a 42% compound annual growth rate in the Web 2.0 market through 2011. Best of all, much of the stuff is cheap, they said. Phifer pointed out that “mashup technology might cost a few hundred thousand dollars, while blogging and wiki tools could cost a few thousand. But that’s not as expensive as acquiring and managing a traditional software infrastructure. You’re not looking at humongous investments.” Posted by joemckendrick in Business Intelligence | Permalink | Comments (0) | TrackBacks (0) September 20, 2007Semantics: What's the Deal With That?
How relevant are Semantics to business intelligence and analytics? The irrepressible James Kobileus, a fan of all things Semantic (whom I frequently join in the SOA BriefingsDirect podcasts, aka the Gardner Gang), points to a post by Bill Inmon, the guru of gurus in data warehousing and analytics, who questions the value of semantics to the business: "I admit it. When it comes to Semantics, I don’t just get it. You can call me misguided, an old fuddy duddy, or just plain dumb. In one way or another, perhaps all of those names fit. But at the end of the day, I just don’t understand Semantics." A definition is in order here, but that definition can get pretty fuzzy. Even Wikipedia gets tongue-tied and convoluted trying to explain the concept. Essentially, Semantics is identifying the meaning that is attached to data, whether it's through tagging or associations or other means. It's not that Bill Inmon doesn't understand what Semantics are, but, rather, how they ultimately benefit the business. Folks have been talking up the "Semantic Web" (or Web 3.0) a lot lately, which, in theory, puts a great deal of data analysis capabilities out in the cloud versus having to buy, install, and maintain a lot of analytic tools on your own. Jim noted that one of things he likes about Semantic Web "is that one can pretty much connect it to anything one wishes on a philosophic, ontologic, metaphysic, technologic, or sociologic level." In other words, it throws open vast storehouses of information -- formerly locked away from view -- and enables any type of interpretation or leveraging the end-user sees fit. Isn't that ultimately the vision of BI and analytics in its purest form? To be able to ask any question, of any information source, at any time, and get an answer back. An InformationWeek article from May discusses how a couple of companies are already putting some aspects of Semantics into practice. At GlaxoSmithKline, an abstraction layer of semantic data is being tested in an effort to provide a more flexible IT infrastructure and increased productivity through automation. The goal, the article states, is to apply computer-based reasoning to evaluate and filter massive amounts of experimental data. At Eastman Kodak, Semantic Web tools are helping customers manage growing collections of digital images by inferring meaning from visual data. As Kodak chairman and CEO Antonio Perez put it, the goal is to have pictures "begin to recognize each other--so, without human instruction, a picture will use its metadata to find another picture with related metadata, so that all the pictures keep assembling in new groups, depending on how they relate to each other." Lorraine Lawson of IT Business Edge also puts Semantics in their proper perspective, quoting Uche Ogbuji, partner at Zepheira, a knowledge management company specializing in Semantic Web standards. Ogbuji stated (or understated) that Semantic Web technology “has suffered a lack of pragmatic focus.” However, "where the technology really shines, at least at this stage of development, is when it’s used with enterprise data architecture." Currently, most enterprise data architecture efforts are vendor-driven, rather than standards- and Internet-driven. Still, these are pilot efforts, and Bill Inmon ponders whether Semantics will ever show value in the market. "Perhaps semantics just doesn’t have a commercial application and never will. Perhaps the point of semantics is not to have commercial success. Another possibility is that semantics is a technology whose time has not yet come." Posted by joemckendrick in Business Intelligence | Permalink | Comments (0) | TrackBacks (0) September 18, 2007Competing on Analytics When There's Too Much Data
Tom Davenport coined the phrase in the title of his impressive book a couple of years back, and now everyone wants to do it: Compete on Analytics. It sounds so good -- but how close are we to this nirvana? That's a question I set out to answer in one of my latest articles in Database Trends & Applications, and it looks like there's plenty of movement in this direction. The challenge is that we've gone into overkill mode with the data we're gathering, and the technology to better help sort things out is still just arriving. Many companies are inundated with data, and are still mired in earlier generations of query and reporting products. As Eric Blankenburg, vice president of application and integration solutions at Avanade, told me, "Most organizations are barely at the toddler stage when it comes to analytics... We are drowning in information. It’s past the point where it is even possible for us to interpret the data and make reasoned decisions without some significant level of analytical support.” I also worked with Cognos, the Oracle Applications Users Group (OAUG), and Unisphere Research to assemble a survey of 296 data applications managers, who agreed with this prognosis: The study found that 91 percent of companies said that their decision-making capabilities were stymied by a lack of complete information. Yet, three out of four also report they suffer from ‘information overload.’ Identifying and separating out the pieces of data that have the most value may be like looking for a particular piece of straw in a haystack. Also, the majority of respondents to the OAUG survey report that it takes more than three to five days to get a report out of IT. Overall, the survey found, fewer than 10 percent of employees have access to BI and corporate performance management tools. The key to successfully competing on analytics is embedding analytic functionality in every mission-critical application across the enterprise -- not treating BI and analytics as standalone applications run separately from the action. Marc Andrews, director of strategy and business development for unstructured information at IBM, told me that “Most companies are using BI for traditional querying and reporting, not for real-time operational business intelligence. They’re not using it as part of their business applications - as part of processing a claim, as part of helping a customer resolve a problem, or as part of processing a transaction.” This also places a greater urgency on data quality as well. Mary Crissey, analytics marketing manager at SAS Institute, said that many companies may rush too fast to rely on real-time or near real-time data without vetting it for accuracy or timeliness. But the bottom line is prices for sophisticated analytic tools and software is coming down, to the point where more companies can afford to compete on analytics, and thus be in a position to reap the benefits. But it's going to take time. Posted by joemckendrick in Business Intelligence | Permalink | Comments (0) | TrackBacks (0) August 29, 2007Will Search Change the Way We BI?
"Can search deliver on the promise of ubiquitous BI? And, if not ubiquitous BI, how or why will search change the manner in which organizations generate and consume BI?" To answer these questions, Steve Swoyer recently spoke with some leading voices in the BI space, and comes to the conclusion that the jury is still out on these questions, but search is showing potential in as a BI front-end tool. "Search vendors," he writes in a TDWI report, "cite the can’t-miss Web search model on which the technology is based and say that enterprise search has a proven usability track record." Search isn't likely to replace more established reporting, BI, and enterprise data warehouse approaches, but enhance them or fill in gaps where information is difficult to access. Jill Dyche, a partner with and co-founder of BI and DW consultancy Baseline, and one of the most respected authorities on all things BI, said that she is seeing forward-thinking companies tap search technologies to complement existing BI and data warehouse implementations. Search tools also help clear up confusion and redundancy in larger organizations, which may have thousands of documents and hundreds of database instances scattered about. Plus, there's the search appliance. Dyche is quoted as observing that "most of our clients embarking on search are using it to track and manage their reports using search appliance technology. Hyperion—now Oracle—does this very well, using a Google search appliance. By exposing the metadata from BI tools, the search appliance can find reports and other documents and make them available to anyone with Web access." Steve cites an example of search-BI query fusion: "A more advanced BI search use case involves indexing reports across multiple BI platforms." Often, end-users need to search multiple systems one at a time in an attempt to gather all relevant reports. However, Steve adds, because there are so many vendors offering so many BI platforms out there, that it may be a challenge finding a search engine that can support so many formats. Posted by joemckendrick in Business Intelligence | Permalink | Comments (0) | TrackBacks (0) August 27, 2007BI Leader: BI Will Incorporate More Web 2.0, Social Networking, SOA
Business intelligence interfaces will borrow more form and function from the consumer space, and as a result, be simpler to use while delivering more sophisticated results. That's the view of Don Campbell, vice president of product innovation and technology at Cognos. One of my colleagues over at ZDNet, Larry Dignan, just reported on a chat he had with Campbell, who talked about the changing face of business intelligence. “The technology at home is creeping into the enterprise,” Campbell said. "At home we all Google to find information. To emphasize this point, Larry Dignan observes that Cognos has been hooking into search providers such as Google, Yahoo, Autonomy, Fast and IBM. "Under this concept, BI data would surface through a simple text box. You type in third quarter revenue and you’d get a chart, just like Yahoo or Google gives you the weather. Search on 'raincoats in Milan' and BI should return product specific sales by region via a simple search box." SOA is also a trend reshaping BI systems, Campbell said. Cognos' latest platform, Cognos 8, ditched a legacy What's next for BI systems? GPS is one exciting area of application, Campbell said. The other is "learning from the user:" Campbell says the next challenge for BI tools is learning from users, noting that today's BI tools "spit out information without much input from users." In the future, he said, BI systems will incorporate user tags and commentary. “The next generation of BI will be more comfortable understanding unstructured data,” he said. “Unstructured data will be as important as structured data.” Posted by joemckendrick in Business Intelligence | Permalink | Comments (0) | TrackBacks (0) August 19, 2007DataMirror Reflects IBM's Integration Ambition 
"Mirror, mirror on the wall, who is the fairest data integration vendor of them all?" A narcissistic IBM might well be asking itself that question following its recent $162m acquisition of DataMirror. But wait a sec. Didn't IBM buy Ascential to cover all the data integration bases? Apparently not it seems. One area where Ascential lacked was in real-time data replication and change data capture, areas that DataMirror excels in. DataMirror's core Transformation Server software does a lot more than just move high volumes of data directly between relational databases, message queues, and other data stores. It also detects changes in data sources (additions, updates or deletions) and manages the replication, thereby enabling the changed information to be delivered at the actual moment when the change has been made. Being able to track data changes as they occur and respond accordingly is becoming important for dynamic data warehouses, particularly those operating in high volume, quick-sale retail environments. DataMirror also hands IBM a robust offering complete with heterogeneous data support in real-time. Of course that plays nicely to IBM's "On Demand" computing vision -- that of enabling the operational real-time, event-aware enterprise. Data replication, by its very nature, works well in real-time and the technology has its roots in high-availability database applications for reporting, backup, migrations and consolidation as well as disaster recovery, all of which require mirrored copies of every database transaction to be maintained in real-time, so that the mirror can ensure uninterrupted operation in the event of a server outage. Given that diversity of its user base, it's understandable why IBM plans to continue to offer DataMirror's data integration, auditing, high availability, and data replication software as stand-alone products. But over time they will also become absorbed into its flagship Information Server, which is fast becoming a homestead for IBM's broad portfolio of homegrown and acquired data integration software. IBM has yet to detail its specific plans about integration. But there are several technical considerations to take into account: One of the main strengths of DataMirror is its database support. Hence, IBM should make sure that DataMirror's neutrality is maintained, even though it has a vested interested in promoting its own DB2 database system. DataMirror already has close partnerships with Teradata, Netezza, and Oracle. Interestingly DataMirror was quick to pledge support for Oracle's new 11g database less than a week after the acquisition was announced. IBM also intends to continue DataMirror's partnerships with other vendors, notably BEA Systems, Business Objects, Microsoft, and Oracle. Keeping such relationships alive are critical to ensuring that IBM can continue to offer a heterogeneous data integration. Given the sheer breadth of IBM's product portfolio and technology acquisition is bound to result in some degree of overlap. That's also the case with DataMirror, but not to an extent that creates a significant amount of redundancy. A quick look at IBM integration portfolio shows some overlap with IBM's Q Replication and Data Propagator products as well as the rudimentary replication capabilities built into DB2. But DataMirror's technology is functionally superior and more broadly applicable to the diverse range of real-time data processing environments envisaged by IBM's Information On Demand strategy. DataMirror seems a good fit with IBM's broader vision for real-time integration. For example, there are obvious links between DataMirror's real-time software and IBM's own real- and batch-oriented ETL, business intelligence, enterprise service bus, and MQSeries message queue integration technologies. Besides the technology intellectual property that IBM gains, the company also brings on board DataMirror's considerable technical and marketing expertise. So far IBM has not imposed a hiring freeze on its DataMirror division that suggests the company is still thinking about growing the business. Historically IBM has not had a great track record in shepherding acquired skills. But its recent acquisition of customer data integration firm DWL seems to have gone smoothly from an organizational perspective. So by acquiring DataMirror IBM gets its paws on a very mature and advanced change data capture and replication tool that is still modestly priced against some of its competitors. The move shouldn't really come as a surprise as IBM had partnered closely with DataMirror to provide its own data integration customers with those core competencies. But over time it has become clear that IBM needed to own this kind of technology as more and more of its data integration customers demanded it. A big chunk of DataMirror's 2,200 customer base part of that has come from IBM referrals. But IBM didn't make the purchase to buy-in customers. It was more interested in DataMirror's technology to shore up a functional weakness in its own data integration platform. Competitively DataMirror now positions IBM more strongly against Acsential's arch-nemesis Informatica, particularly in the real-time ETL space for enabling operational BI and even event-aware analytics. It's more than likely that DataMirror's software will eventually find a permanent resting place in IBM's new Information Server, a platform it is investing heavily in right now. And because IBM has laid out grand plans for Information Server that extends beyond data replication, it probably isn't done buying smaller software firms and technologies to round out the platform. IBM's customer base is quite diverse and it's likely that it will need multiple products even of the same type, including replication. From a birds-eye view, the acquisition of DataMirror is also part of a general push by IBM to expand its software holdings and revenue. It could well be a precursor to many more similar types of technology-focused acquisitions that IBM does in the second half of this year. IBM has already spent around $1bn on acquisitions this year alone. It still has roughly $4bn to spend before it meets its stated objective of keeping up with the 13 companies it acquired in 2006. DataMirror is just the type of acquisition that reflects a shift away from lower-margin computer hardware to more profitable software sales. In a nutshell software is making most of IBM's money right now. Posted by madansheina in Business Intelligence | Permalink | Comments (0) | TrackBacks (0) August 17, 2007By the way... 
I have begun a multi-entry discourse/diatribe about getting back to basics and first principles as the foundation of a truly effective strategy for business process management (BPM). I believe this argument applies equally well, if not more so, to BI efforts. So I humbly yet eagerly encourage you to visit the "BPM in Action" blog, and check out my entries on "BPM Back to Basics." And feel free to comment liberally! Posted by mdortch in BI • Business Intelligence | Permalink | Comments (0) | TrackBacks (0) August 06, 2007To SaaS or Not to SaaS? That is the Question for BI Vendors
Speaking at the recent Pacific Northwest BI Summit, Claudia Imhoff weighed the advantages and disadvantages of delivering business intelligence through the Software as a Service model. (Podcast available here as an audio download.) Claudia observes that in most cases at present, BI over SaaS is mainly operational versus strategic, and the growth of SaaS-delivered BI in a strategic sense is an open question. She states that there are four primary advantages to BI vendors (and ultimately to end-user customers) in going the SaaS route: For one, the vendor has to support one platform and one version of their software, versus multiple OSes, paltforms, and versions. "That’s a pretty impactful thing in a software business," Claudia says. "The decrease in development costs can be significant." In addition, SaaS deployments provides the vendor "real insight into how customers are using their software. "What features are they actually using, and which ones do they never touch? They get to see every move, every feature, every function that is being used by their customers.… ...any vendor would kill to have that kind of information." In addition, Claudia continues, the software can remain light and agile. "Vendors don’t get trapped into this feature-bloat thing," she observes. "In a traditional model, a software vendor has to keep coming up with new features and new functionality so they can sell another version." Posted by joemckendrick in Business Intelligence | Permalink | Comments (0) | TrackBacks (0) August 02, 2007BI as a Service: An Idea Whose Time Has Come?
Hamilton Beach-Proctor Silex, a major consumer appliance manufacturer, facilitates its market research through SaaS-delivered applications provided by statistical tools vendor SPSS. A couple of months ago, I had the opportunity to speak with Tracy Trawick, consumer insights manager for Hamilton Beach, who talked about her company's mixed use of SaaS and on-site business intelligence tools. Hamilton-Beach's market research department primarily relies on on-site software, but began tapping into SPSS's SaaS-based platform to cover a growing workload that end-users simply don't have time to sort through. "All the data manipulation on the back end is supported by SPSS," Trawick said. "We're using it for very template-based iterative projects so we don't use up a lot of programming time. I don't have the time to learn the logic and the programming tools." Trawick uses the SPSS SaaS platform to create and launch consumer market research surveys, and manipulate the data as it comes in. However, she still employs SPSS on-site software for more complicated projects. Does the BI as a service trend have legs? Our blogmate here at BI in Action, Madan Sheina, recently took a hard look at the trend. Can it work? Or, as Madan put it, is it wheat or chaff? While SaaS is still a nascent trend in BI, it is gaining in popularity, especially among small to medium-size businesses, Madan said. However, BI SaaS vendors face Microsoft in the market. Plus, Madan said, "moving to SaaS is not as easy as simply having your BI software hosted." Data security is a huge issue, he notes. Customization is another. "Vendors offering their BI solutions as SaaS must also overcome the significant hurdles of data privacy, reliability of service, working out commissions for channel partners, and grappling with a new sales model." Another ebizQ colleague, James Taylor, also talked out BI and analytics delivered via SaaS in a recent post. Posted by joemckendrick in Business Intelligence | Permalink | Comments (0) | TrackBacks (0) Oracle 11g -- Not "The BI Release" You Were Hoping For
So Oracle has announced its next generation database platform Oracle 11g that packs in nearly 500 enhancements and new features, promising improved performance, accelerated change management, higher scalability, easier administration and reduced cost. But what's in it for business intelligence and data warehousing? Well basically there are three areas that might put a smile on the faces of Oracle data warehousing gurus: SQL-Flavored OLAP Put simply; Oracle has embedded an OLAP engine into 11g to store and efficiently manage millions of these materialized views. So why are materialized views important? One reason performance. Materialized views are sort of pre-fetching used to speed multidimensional queries -- for example to calculate sales across products, regions or customers -- by presenting logically pre-aggregated data sets to users. Oracle uses an OLAP cube to store millions of materialized views so that they can be managed more quickly and efficiently. First it uses OLAP cubes as a transparent performance accelerator inside the relational database system itself. Then it offers the core manageability features of 11g to track data changes in the underlying data sources so that those changes are incrementally refreshed (usually daily or nightly) to the materialized views stored in the cubes. But performance and manageability aren't the only benefit to users. The ability to use standard SQL tools and applications to access and slice-and-dice multidimensional OLAP cubes, without users knowing they are using OLAP, is also key. The Oracle 10g database allowed users to access OLAP cues. But they had to write specific SQL to specific views. 11g lets users do this more transparently using the SQL syntax they know and love. In other words, call it Oracle's attempt to push OLAP from a specialized market to a much broader constituency of SQL-savvy users. Interestingly the underlying OLAP engine used to drive these materialized views is neither Essbase, the marketing leading OLAP server that oracle gained from its recent acquisition of Hyperion Solutions, nor Express, its legacy product that acquired from IRI Software over a decade ago. Rather it’s a separate OLAP server that was designed by Express engineers to be more embedded into the database. The feature is deemed important by Oracle as it claims over 60% of its data warehousing customers use materialized views in their implementations today. Oracle hopes its new embedded support will grow this figure, with the stated aim of pushing OLAP into everyone of its data warehouse implementations. Advanced Partitioning Oracle calls 11g "its most significant partitioning update" over the last six major database releases and says that almost all of its data warehousing customers use the partitioning capabilities. It notes that partitioning plays a key role in the base enterprise data warehouse foundation scheme, where data is typically held in a granular 3NF schema and where the largest tables, joins and data loading reside. Accelerated Query Performance Oracle claims that 11g's cache implementation is far more sophisticated than a standard cache that simply stores query results and is consulted every time a query is resubmitted. It goes further in two ways: • Users can make intelligent decisions on which results to put in the cache based in criteria like query format, how long the query took to run, how big the results set is, etc. Oracle expects its Cache to absorb more sophisticated layers of functionality like: dependency tracking (to make sure the cache is up to date); invalidation logic (to determine if the results are out of synch with underlying data changes); and automatic updates (to keep pace with data changes). Wrap-Up The most pertinent upgrade for BI is 11g's OLAP-cube based management of materialized data views. But users shouldn't overplay then significance of that technology. A materialized view is useful for what. But it is only an enabling technology. By itself it won't deliver a new generation of end-user analytics. By the same token, the performance-enhancing query cache will put a smile on the faces of performance-pressured DBAs. But it won't necessarily transform BI. The real BI story in 11g is really a combination of OLAP technology that is accessed transparently by SQL-based applications. In other words OLAP cubes are used as a query performance accelerator inside the relational database without SQL applications and tools knowing they are accessing those cubes. But wait a sec: isn't that really a way of Oracle saying that traditional OLAP slice-and-dice, drill-up/down and pivot analysis has been too expensive, slow and complex to achieve among its own data warehousing customer base up to now? If so then the materialized views feature now attempts to fix a sub-optimal workaround that oracle had previously offered. However there is another rub. The reliance on materialized views certainly harks back to a need for massive pre-aggregation of data that traditional multidimensional OLAP (MOLAP) engines used to be attacked for. Think data explosion. Nevertheless the new BI features in 11g do represent another big step in the commoditization of BI. In the case of materialized views, Oracle is offering OLAP as a core function of the relational database platform. Of course that's an area where Oracle is playing catch-up to Microsoft which has spread BI to the masses through SQL Server’s OLAP Services. What's notable however is that Essbase isn't being tapped in 11g. But as a market leading OLAP server that is arguably more robust that Oracle's own offerings, it is only a matter of time before it is pushed closer to the core relational database kernel. Posted by madansheina in Business Intelligence | Permalink | Comments (2) | TrackBacks (0) July 25, 2007Breaking BI Bread, or Mixing Livestock Fodder?
Vendors and analysts continue to talk up various trends in business intelligence. But what's real and what's hype? That got me thinking about bread…yes the kind you toast and butter. Bread is made from wheat, which is first separated from the chaff by a thresher-like machine. Wheat is useful. Chaff is, well, chaff. So I thought I'd apply my own mental thresher to some of the hyped up trends that vendors and analysts are talking up today. Will they become bread or livestock fodder? Data Warehouse Appliances Wheat or Chaff? Love them or hate them, data warehouse appliances are not a passing fad and are here to stay. Driven by the relentless growth in transactions and data volumes, and riding on the back of Moore's technology cost curve, scalable and performance-optimized data warehouse appliances have the potential to add value to existing EDW initiatives without expensive upgrades. Appliances hitting the market today are unrecognizable from the proprietary and expensive appliances of yesteryear. A new generation of turnkey appliances built on commodity hardware and open source software components is starting to flood the data-warehousing market. Start-ups like Netezza and Datallegro have worked hard to make appliances a viable product category. Interest in appliances from big vendors like IBM, Hewlett-Packard, and Sun, has more or less validated the market. The next challenge is to create a critical mass of customers. Some big wins are expected in 2007. Most of these will be as an adjunct to enterprise data warehouses, but perhaps some will take business from market incumbents like Teradata, IBM, and Oracle. There will also be some failures. Getting the appliance model right is tricky, and several promising appliance start-ups have already dropped out after trying to plug in appliances built on proprietary platforms. Open Source BI Wheat or Chaff? It is hard to tell. Open source BI is aimed at lower-end of the market, namely basic reporting and the Java development community (as is the case with Actuate), rather than complex analysis or large enterprise-scale BI deployments. It's true that JasperSoft and Pentaho are assembling more ambitious BI suites, but they still tend to be feature-limited, and are unlikely to overtake and replace Business Objects or Cognos installations anytime soon. The question is whether this is something that customers will be prepared to wait for? Complex and enterprise-scale BI and analytics will traditionally remain licensed software for the next five years at least. Mobile BI But isn't this deja vu? Remember portable, wireless, mobile, or whatever you might wish to call it, BI was all the rage five years ago at the height of WAP-mania and the start of the PDA device boom. Back then software vendors scrambled to recreate their desktop interfaces on mobile devices, without giving much thought to the value and usefulness of doing so. But the idea has persisted and seems to have a second wind with Cognos, Business Objects, and MicroStrategy all launching fresh mobility features that plug into their core BI platforms in the hope of making BI more pervasive. Wheat or Chaff? Mobile BI has promised to go anywhere, but so far it hasn't. What stopped it doing so in the past was less about the technology (the bandwidth and rendering issues are being fixed) and more about presenting a compelling business case for the investment. That still holds true today. Only a few specialized functions really benefit from mobile BI, notably field sales and support optimization, territory analysis, and customer communications/management. Unless someone comes up with a killer app for mobile BI then it will simply be another bell and whistle function of your BI platform. On-Demand BI They have a strong case. Established BI software providers like SAS Institute, Business Objects, and Cognos, as well as new entrants like Oco Software, Seatab, Host Analytics, and LucidEra, have all recently made SaaS BI plays. And Informatica, in partnership with SaaS poster child Salesforce.com, is also pioneering the delivery of hosted integration services to systems integrators and business process outsourcers. Wheat or Chaff? SaaS, like open source BI, is still a nascent trend in BI. It is gaining in popularity, particularly at the lower end of the market where cash-strapped and IT resource-challenged SMBs are looking for painless entry into BI. In many ways SaaS represents a significant paradigm shift in how enterprise software is deployed and managed. It is a direct response to customer demand for less expensive software licensing, simpler implementation, and more widespread adoption. BI fits the bill well since it has traditionally been expensive and complex to deploy and has yet to penetrate broader business user audiences. It is too early to gauge the impact of this software delivery model. The newer start-ups need to acquire a critical mass of customers in the SMB segment. But these vendors are also up against a formidable and entrenched competitor in the SMB space, namely Microsoft and its SQL Server 2005-based BI system. At face value, SaaS offers a much cheaper and easier alternative than on-premise software. But moving to SaaS is not as easy as simply having your BI software hosted. Companies should carefully consider several issues, not least security implications that are more pronounced in BI given the sensitive nature of the data, managing organizations' access to the data and applications through multiple client tenancy arrangements, and how a vendor's SaaS architecture fits with their IT standards and its impact on interoperability with their own internal systems, especially enterprise BI systems already in place. Vendors offering their BI solutions as SaaS must also overcome the significant hurdles of data privacy, reliability of service, working out commissions for channel partners, and grappling with a new sales model. Moreover, the majority of SaaS deployments continue to be focused on individual departmental initiatives. No provider yet offers the functionality or end-to end process management awareness of on-premise software to support the analysis of cross-departmental business flows. Finally, there is the issue of customizability, which has always been the bugbear of SaaS applications, and one reason why most SaaS BI offerings today are best suited for "commoditized" BI tasks like query and reporting. But BI delivered as SaaS is also likely to get uptake from larger enterprises that have prior experience with on-demand CRM solutions. Posted by madansheina in Business Intelligence | Permalink | Comments (2) | TrackBacks (0) |