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October 29, 2007 World's Biggest Time Waster: Reconciliation While at Teradata Partners, I had the chance to catch up with Claudia Imhoff, one of the leading thinkers and voices in the business intelligence and data warehouse space. At a well-attended session at Teradata, Claudia addressed an emerging topic with far greater implications to the enterprise than BI or data warehousing alone -- master data management, or MDM. "Master data management is not a data warehousing project," Claudia emphasized. "However, many master data management projects get started by the BI people." MDM is "bigger than BI" because it "needs to be shared across all business operations," she explained. And it's "bigger than operations, so don't bury it under some application monitor." "Master data management is more than just another data integration project," Claudia continued. "It defines what is a customer? And what is a product?" MDM is defined as "a set of disciplines, applications and technologies for harmonizing and managing the system of record and system of entry for the data and metadata associated with the key business entities of an organization." The good news about MDM, Claudia added, is that while it's by and for the enterprise, it doesn't need to include every piece of data out there. MDM is about capturing selective data -- reference data about the organization's core business entities -- people (customers, employees), things (products, finances), places (regions), and other key entities. "If you set out thinking,'I'm going to integrate all our customer data,'" don't do that," Claudia advised. "You'll never get there." What's the benefit of MDM? Time and productivity, Claudia explains. "Reconciliation is the biggest waste of time out there today. It's the biggest drain on productivity I've ever seen. Two departments heads will have to sit down and bring two sets of data into line -- 'Why don't your numbers match my numbers?'" Worse yet, nobody has ever tried to measure the time loss spent in reconciliation. "Enterprises spend enormous resources -- in time, money, and people -- doing reconciliation because of fractured master data." One challenge to corporate MDM efforts, however, is existing systems of entry (SOE) that have proliferated across the enterprise. "We'll never kill off all the systems of entry -- we have to be able to accept updates from those environments," Claudia said. "There are many reasons why the systems of entry can't be changed for today. They're either very old systems, or they're outsourced. If you use Salesforce.com, for example, you may have to leave the systems where they are." Posted by joemckendrick in Data Management  |  Permalink  | Comments (0)  | TrackBacks (0) October 26, 2007 Survey Finds Open Source Wide, Not Deep, at Data Sites I recently analyzed and wrote up a survey for the Independent Oracle Users Group which sought to drill down on the prevalence of open-source solutions within data management environments. The survey was sponsored by MySQL and administered by Unisphere Research. MySQL was not seeking data on whether their open source database was displacing Oracle; rather, it wanted to get a lay of the land for open source adoption across other parts of the technology stack. A total of 226 companies participated in the survey. Since this survey was conducted among members of the Oracle user group, it involved companies that are typically on the larger side -- in fact, 28% reported that they represented operations of $1 billion or more a year. What we found was that open source is prevalent at many levels of the enterprise, and most organizations intend to increase their use of open source over the coming year. However, adoption does not run deep. The survey found that Web servers, operating systems, application servers and databases are the four most common open sources technologies in use. However, when it comes to support of mission-critical enterprise applications, the reach of open source into the enterprise is wide but not deep. In a majority of cases (52%), fewer than 10% of enterprise application portfolios touch open source systems. Only about 13% of the survey respondents said that a majority of their mission-critical applications are tied into open source systems, up from nine percent in a similar survey conducted last year. Beyond the "utility" parts of the stack that help run IT systems and operations, there is a sizable minority of companies that are also using open-source enterprise applications. For example, 27% said they were running open-source CRM applications, and another 19% were using open-source-based content management software. Another 15% reported they use open-source-based business intelligence software, and another 15% use open-source ERP. Why do these companies like open source? Cost savings is the number one driver. Freedom from vendor lock-in came in second. The leading limitation of open source? Respondents across the board felt that enterprise support was not as robust as what is associated with commercial software. Open source adoption should keep growing over the coming year. A majority of respondents, 52 percent, said their use of open source software will increase over the coming year, versus only two percent that foresee decreased usage. Thirty-seven percent said their current levels of adoption will remain the same. Posted by joemckendrick in Data Management  |  Permalink  | Comments (0)  | TrackBacks (0) October 19, 2007 Real-Time Data Availability? Why Not 'Good Enough' Availability? Listen to the vendors, and you can be forgiven for thinking that just about every business now runs on a real-time, analytical, automated decisioning, neural networked infrastructure. Time for a reality check, and this one was provided by Donald Feinberg, vice president and analyst with Gartner. At last week's Teradata Partners Conference in Las Vegas, I had the opportunity to hear Feinberg talk about what's important, what should not be as important, and what isn't emphasized enough in BI these days. One theme Feinberg emphasized -- reflecting a theme I heard throughout the conference -- was that data needs to be closer to the infrastructure that supports it. A trend Feinberg is seeing is that enterprises are "pushing DBMS code closer to storage, and sometimes into the storage." This is a positive trend, he says, because "the more DBMS code is moved closer to the storage, the less data movement that is required." "You're no longer pushing a basketball through a straw," he added. Another issue that many companies are coming up against is the need to hang on to data -- sometimes a lot longer than necessary, Feinberg says. "You don't need to keep all your data forever," he advises. "Why would you need market basket detail for 10 years? Are you going to send a letter to a customer that bought a Bic pen 10 years ago, and ask them why they haven't bough a new one?" This is a good point, especially in the current environment where everyone is nervous about compliance. I even ran into one company where the IT administrator admitted that their policy is now to hang on to every email they've ever generated, and intend to keep it stored somewhere forever. Another point Feinberg raised is the sense of urgency many businesses feel about making "real time" data available whenever and to whomever wants it. This is an expensive proposition that will deliver little or no added value to the business, he points out. "You don't need instantaneous loading of things unless you're the New York Stock Exchange, and you're looking for fraud in stock trading." "Good enough" data availability may be just enough the fit the bill for most companies, he says. For example, "the time for phone service activation has gone from two weeks to six hours -- and that's 'good enough,'" he points out. Feinberg also talked about the benefits of establishing a business intelligence "center of excellence" within the company to move projects forward. While some may see a center of excellence as another bureaucracy, it has just the opposite effect, he believes. A business intelligence center of excellence "takes the politics out of business intelligence altogether," he points out. "If you put in BI systems, you have to decide which department gets the first one? Every department will get mad because they wanted the system first." A center of excellence can look at the business drivers for BI projects and make the call as to which departments will see the first deployments. Posted by joemckendrick in Management  |  Permalink  | Comments (0)  | TrackBacks (0) Teradata's New Course Up the Stack For years, Teradata was known as that big, big enterprise data warehouse company for big, big companies. And as an independent subsidiary of NCR. Last week, however, when I made my annual pilgrimage to the Teradata Partners' Conference, held in Las Vegas, I saw the signs of an emerging new vendor. Perhaps one that was looking at the medium-size business sector as well. First, in the week preceding the conference, Teradata become its own entity, spun of entirely from NCR's tutelage. As anyone who follows the IT space knows, this is the era of acquisition, of big fish eating slightly less-larger fish. So, right away, Teradata is going against the grain. Mike Koehler, CEO, joined other executives in a Q&A session and talked about the spin-off. Though it was not entirely clear what Teradata would be doing differently now that it was on its own -- and NCR always seemed to keep its hands off the golden goose anyway -- it was clear the company is engaged in a self-directed push to become more than a "data warehouse company." Koehler's motto is that "the companies who operate with the greatest intelligence and speed will win." He predicted that five years from now, "Teradata would be a leader in active enterprise intelligence." Active Enterprise Intelligence is another catchword Teradata is promoting to describe its new direction -- which is, unquestionably, up the stack, to the business intelligence level. The cornerstone announcement of Teradata's coming-out party was a partnership with SAS, the analytics algorithm provider. SAS applications can take advantage of Teradata's high-availability infrastructure, and Teradata customers will have greater access to analytic tools to run against their data. The foundation of the partnership is to enable businesses to run and optimize key aspects of SAS solutions and analytic processes within the Teradata database engine. Teradata customers will be able to leverage SAS capabilities and analytical functions to utilize the core parallel processing inherent in Teradata's architecture. Additionally, the joint road map also calls for selected SAS solutions targeting financial services and retail to be optimized with Teradata. Was the partnership triggered as an alternative to the SAP-Business Objects combo that now is in the offing? Or the Oracle-Hyperion combo? You bet. The data warehouse/analytics market is maturing, and with that maturity comes consolidation and suites. Kohler was asked, in fact, why he didn't consider buying SAS outright, to which he responded that the two companies already have as tight a partnership as you can get, without the legal wrangling and fees. (Here's to loose coupling between companies!) When asked if the SAP-Business Objects buyout would affect Teradata's relationship with B.O., Teradata VP Bob Fair pointed out that such events most often result in a strengthening of the partnerships already established -- he expects that to happen with B.O. One phrase I heard several times -- uttered by both Teradata and SAS executives -- is to "move the processing to the data, rather than moving the data to the processing." This makes a lot of sense in a world where data -- and the ability to leverage data to compete on analytics -- is now the source of competitive advantage. And, one thing is abundantly clear -- Teradata intends to be an aggressive major player in the analytics/BI space, both through partnerships and its own offerings. Posted by joemckendrick in BI Vendor Watch  |  Permalink  | Comments (0)  | TrackBacks (0) October 07, 2007 SAP to Acquire Business Objects: What's the Deal With That? What a weekend for business intelligence. ERP and enterprise software giant SAP has announced it will be acquiring BI leader Business Objects in a $6.78 billion deal. According to a report in ComputerWorld, acquiring Business Objects will allow SAP to move into the BI market in a big way. SAP CEO Henning Kagermann said that the acquisition will enable SAP to offer integrated software, versus solutions arising from a partnership between the two companies. The deal is expected to close in the first quarter of 2008. Enterprise systems and business intelligence tools have been moving closer in alignment in recent years. The thrust of the BI industry into corporate performance management draws directly from a enterprise/ERP foundation, so the synergy has been ripe. In addition, over the years, one of the biggest complaints about ERP software has been its less-than-stellar reporting features. Adding a robust BI capability to the mix may help change that perception. Of course, many leading BI vendors have made a living off filling the reporting gap in ERP systems. It remains to be seen if having Business Objects built into these systems will pose a competitive threat to the bread and butter of BI industry competitors. Plus, since many organizations manage multiple ERP systems, the challenge of consolidating reporting into single views still remains a challenge. Will Business Objects remain "Business Objects," or be absorbed into the SAP mega-machine? According to Business Objects CEO John Schwarz, B.O. will continue to operate separately from its new parent, as "a stand-alone entity within the SAP Group." Ultimately, however, B.O. software will be more tightly aligned with SAP products. The move is also seen as a counter-move to Oracle's recent acquisition of Hyperion. Posted by joemckendrick in BI Vendor Watch  |  Permalink  | Comments (0)  | TrackBacks (0) October 05, 2007 Mortage Mess: Where Was the Business Intelligence? As you probably have seen in my blog postings and everywhere else, the era of Competing on Analytics is upon us. Businesses now have the tools and the drive to look at who, exactly, their customers are, what they want, where they are going, and if they will go amiss at some point in the future. Financial services have been the leading force in adoption of business analytics. However, such business intelligence seemed notably absent from the currently unfolding subprime mortgage debacle. Anyone following the business news over the past few weeks has seen the grisly stories of mortgage companies taking huge losses or going out of business. In addition, financial services firms with stakes in the market are also taking their share of mega-losses. For example, at the time this post was being written, one of the powerhouses of the financial services space, Merrill Lynch, announced $5 billion in losses thanks to investments in debt obligations tied to the floundering subprime mortgage market. Washington Mutual also took a 75% drop in profits as fallout from the Mortgage Meltdown summer. That's big, big money. However, if our business intelligence tools and platforms are so good, why didn't any of them see this coming? Could effective predictive analytical tools have helped steer these companies away from these losses? For example, couldn't these systems have predicted the impact that the current waves of mortgage-rate resets would have on certain markets? Why weren't these systems able to flag risky loan applications that would not be able to bear resets to higher rates? I am reminded of what happened to Cisco Systems during the dot-com and telecom busts in 2000 and 2001. Cisco, with the world's most sophisticated and intelligent supply chains -- able to see customer demand well into the future -- ended up with $2 billion worth of overstock, because it kept on producing and didn't see the market softening ahead. Our analytics systems may be better and better at spotting new opportunities and market anomalies, but they are only as perceptive as the executives that actually make the decisions from the reports they produce. When a mania overpowers markets, it overpowers both rational and programmed decision making. Companies can be cautious, but, at the same time, can't have their lunches eaten by nimbler competitors wiling to take greater risks. We have the systems that can make good tactical calls -- telling decision-makers whether customers are good or bad credit risks, if they will stay on for extended periods of time as customers, and the likelihood that they will respond to certain market promotions. We can tell what items will need to be shipped through a supply chain weeks before demand actually hits. The next challenge is developing systems that are outward-facing, that can take a broader look at the big picture, and the impact these external forces will have on opportunities. And, be able to look at the impact that new players have on the competitive landscape. with that, analytics that not only spit out reports, but make actionable recommendations. Posted by joemckendrick in Predictive Analytics  |  Permalink  | Comments (2)  | TrackBacks (0)