Mr. Schiff: Please recognize that data management is in many cases a very broad term. Initially it was primarily covering structured, well-formatted data. While one could credibly argue that everything in your file cabinet is important information, we limit our focus to data that is stored in, and retrievable from, a computer system. That being said, we also cover technologies that assist in enabling unstructured data such as the contents of a file cabinet, to be coded and stored in computers. My specific areas of coverage are data warehousing and business intelligence. These are based on the realization that as a business operates, it also generates and collects valuable data about its operations, its customers, its vendors, etc., and that the business needs to store and analyze this to help it operate more effectively and more efficiently. I've always thought that operations and analytics were two sides of a business, two sides of the same business coin, which must work together hand in hand. Part of my coverage is focused on the data warehousing/database space, the ability to store data in a database. Consequently we cover all the major database vendors and some of the minor ones as well, but clearly we cover IBM (IBM), Microsoft (MSFT), Oracle (ORCL), NCR (NCR) and its Teradata division, Sybase (SY), etc. However, if you take a look at a data warehouse environment, you'll see there are really three major phases, which can be simplified as: get the data, store the data, and analyze or use the data. However, just because you can put data in a computer, this doesn't necessarily ensure that this data is accurate. And gathering data from multiple sources doesn't necessarily mean it's consistent. For example, if you are pulling inventory data from three different inventory systems, you better make sure your units of measurement are consistent, otherwise you're adding apples and oranges, or ounces to kilograms. There's a whole phase that involves data cleansing, data aggregation, data consolidation, and data transformation; ultimately this data winds up being stored in a database, and then it's, 'Great, what do you do with it?' This brings up the subject of business intelligence or decision support, which encompasses a wide spectrum of technology and tools, ranging from a simple query to predictive data mining. At Current Analysis we cover the entire data warehousing process, from capturing the data to analyzing the data in order to yield information, knowledge, and insight.
Tickers included in this excerpt: IBM, MSFT, NCR, ORCL, SEBL, STX, SY
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