Enterprise databases, such as DB2, may not be "king of the mountain" any more, but they continue to be vital to business strategies. There are plenty of opportunities to exploit the power of an enterprise database, such as DB2, that most enterprises have not yet implemented.
Here is a list of my top 10 trends affecting DB2: A list for the business strategist smart enough to focus on information as a key source of business angst and business value. Over the next few months, we will take a look at each of these in more detail, seeing the opportunities for the savvy DB2 user and the implementation difficulties that lie ahead.
Now, let me explain briefly the meaning of each item and its relevance to DB2.
Master data management
IBM defines master data management as a solution including infrastructure software, business-process support, and applications that supports an organization in identifying, managing, providing a consistent view of, and leveraging key data across disparate environments. IBM has begun a major marketing push in MDM. DB2 can play a major role in MDM, both as a source of master data and as a repository.
Virtual Operational Store
A virtual operational store (VOS) is a relatively small amount of fast-access operational data that allows the system to deliver, on average, 90% of the speed of an "ideal" on-demand cross-enterprise database. By creating a VOS, IT avoids major problems with implementing a "real-time enterprise" that delivers information on demand. The technologies that offer real promise of solving upcoming RTE problems are EII tools and operational data stores -- that is, an EII solution and an ODS specifically designed to handle a wide range of operational data, to scale, and to add new data sources and types semi-automatically. DB2 can act as an ODS to complement Information Integrator's EII capabilities.
The main reason that a metadata repository is needed, and will be around for the long term, is that no large enterprise can put all of its data, now and in the future, into one gigantic database that responds in real time. In other words, no organization can realistically plan on becoming a "real-time enterprise" by putting all of its data in one data store. Enterprise Information Integration (EII ), a technology that creates a "veneer" or "faÇade" in front of multiple data sources with multiple data types, combined with a metadata repository gives the organization a "second best solution" -- the ability to let data stores of all types grow unhindered, while giving users as far as possible rapid access to the data and identification of relationships between the data in different data stores. Metadata repositories are springing up already, not only with EII but also for master data management. DB2 can act not only as one of the key back-end data stores for a metadata repository, but also as the metadata repository itself.
RFID Software Infrastructure
Real-world RFID implementations are tending toward a "three-level" overall architecture, with a lowest "buffer" level, a middle "local" level, and a top "organization" or "enterprise" level. The database architecture is often "double three-tier," in which three client/application/database-server tiers operate at both the local and enterprise level. In the long term, RFID infrastructure — including an RFID database — can deliver positive bottom-line impact. RFID infrastructure allows greater control over the supply chain, and therefore greater optimization for bottom-line expense-cutting. RFID infrastructure ensures that RFID delivers a large amount of new actionable information to the corporate decision-maker, potentially both at the retail level (how does product placement on the shelves relate to buying behavior?) and at the production and distribution levels (are we forcing product on a vendor further down the chain?).
In fact, RFID data, when enhanced by RFID-infrastructure "semantics", can provide a source of customer satisfaction, allowing buyers to monitor shipment more closely across the supply chain. To achieve this, RFID users should emphasize the analytic capabilities of their RFID database, either via BI tools or OLAP. DB2 can play a key role as the enterprise database paired with IBM's BI and OLAP tools.
Speed to Value
The same tools that speed development also cut application cost of ownership (which is a significant corporate cost), and reduce the risks that the application will fail (which is a major factor in business continuity). Because most value-add applications involve databases, and database programming often takes a major proportion of the developer's time (35-40 %, by some estimates), a good database can help shrink development time while cutting database administration costs — and these are the largest category of costs in many of today's TCO analyses. DB2 plus IBM's Rational RAD (Rapid Application Development) tools can therefore potentially deliver major improvements in application TCO and ROI.
Strategic Information Management
The key barrier to achieving competitive advantage by leveraging proprietary information is that this information is scattered across a wide range of data sources. Therefore a BI (business intelligence) tool or in-house-developed querying tool cannot realistically support identification of key competitive-advantage insights. Instead, IT needs to implement a broad strategy of (a) placing information where it is rapidly accessible, and (b) ensuring that the relationships between the data are better identified-- strategic information management, or information integration. Information integration involves identifying the enterprise's key information resources, managing them so they are in the right data stores at the right time, supporting users' efforts to leverage them, and enabling users to add to their information resources.
"Low IT" Data Management
Small-to-medium-sized SMB applications are often deployed in one of two architectures: One central copy of the application and embedded infrastructure/platform, invoked by up to hundreds of desktop and mobile client devices; and multiple distributed copies of the application and database, each invoked locally by fewer desktop and mobile client devices.
Both of these situations often demand administration by local office workers — untrained personnel. As a result, "Low IT" databases offer automated administration and a high degree of robustness. Case studies indicate that IBM's DB2 Express is as capable as "embedded" databases such as Pervasive when it comes to supporting "Low IT" operation.
Information Lifecycle Management
In order to provide an effective ILM solution, an enterprise must concern itself not only with managing data throughout its lifecycle (hence systems management), but also with supporting unstructured data and with understanding the importance of each datum to the enterprise. In other words, the enterprise must deal with data not merely at the level of storage, but at the level of information.
In most major enterprises, this "data about data" is locked up in the "data dictionaries" of enterprise databases like DB2. By linking these data dictionaries with SANs' (storage area networks') ILM metadata stores, not only can an enterprise achieve better ILM and therefore more cost-effective performance, but also speed up applications by ensuring that databases and SANs are storing data in a coordinated way for maximum performance and scalability.
XQuery, a standard analogous to SQL for transactions on unstructured and semi-structured data stored as XML data, is now a de-facto standard for EII tools. A DB2/Information Integrator pairing that supports XQuery therefore ensures effective use of unstructured and semi-structured data in master data management, ILM, information integration, information on demand, and RFID.
A good OLAP (online analytical processing) solution — essentially a database, plus special indexes and operations for in-depth querying — enables rapid, in-depth analysis and forecasting involving difficult-to-anticipate ad-hoc queries for both immediate tactical and longer-term strategic decision-making. OLAP also differentiates itself by its ability to analyze data across more than two or three dimensions. An architecture involving a separate data store can complicate and increase IT infrastructure, administrative costs and security problems; introduce data quality and latency issues associated with data movement; slow down analysis when data is not in the "right" database; inevitably result in inconsistent data and business rules between systems, reducing users' ability to make sound judgments; and force constant reconciliation and synchronization between OLAP and source data. Thus, users are increasingly seeking to do OLAP "inside" enterprise databases such as DB2.
About the author:Wayne Kernochan is president of Infostructure Associates, LLC, a Lexington, Mass.-based analyst firm.
About Infostructure Associates
Infostructure Associates is an affiliate of Valley View Ventures that aims to provide thought leadership and sound advice to both vendors and users of information technology. This document is the result of Infostructure Associates sponsored research. Infostructure Associates believes that its findings are objective and represent the best analysis available at the time of publication.