From the Editor
- By James E. Powell
- June 7, 2007
I remember the first time I used a search engine. I was amazed at the number of “hits” returned, but I was even more impressed by the speed with which Yahoo! could find (or at least get close to) what I wanted. Over the years, I learned how to improve the likelihood of finding exactly what I wanted, and which search engines were best at different types of queries.
If only BI search were as easy! As Rado Kotorov and Jake Freivald explain, BI search deployments are limited to a few functional areas, but organizations need to approach enterprise BI search differently than they do Web searches. They explain what questions search must answer, how results must be presented, and how users must be able to manipulate the retrieved data. They also point out that search can serve as the entry point to business intelligence—but as BI professionals, we have our work cut out for us. Just make sure your prototypes don’t become the final project, as Paul Johnson cautions in “Honey, I Deployed the Prototype.”
Harriet Fryman offers a different perspective on finding data. She introduces the concept of information packaging—an approach she says “serves the data needs of operational BI, historical analysis, scorecards, real-time alerts, and predictive analytics.” That’s some recommendation! Fryman says information packaging can deliver a complete and consistent view of data, and she describes four key characteristics of her user-centric approach.
Authors Karen Corral, David Schuff, Gregory Schymik, and Robert St. Louis note the difficulty of finding and retrieving knowledge documents. They propose dimensional document warehouses (in contrast to dimensional data warehouses) as a solution, and explain why traditional tools won’t work.
Whether you focus on search, information packaging, or document warehouses, two things are certain: data volumes are up, and the nature of data is changing. John Nicoli examines five major forces that shape data. John Gill describes how in-memory database technologies can help prevent the flood of data from hampering retrieval and analysis. Data warehouse appliances are an increasingly popular tool for coping with data growth, and they are the subject of our Experts’ Perspective column.
Of course, speed is useless if your data isn’t reliable; our case study of U.K.’s Humberside Police illustrates one success story that addressed data quality.
Tools are great, but as senior editor Hugh Watson notes, the proliferation of BI tools presents challenges for users. He suggests some ways to reduce the number we’re using.
As always, I’m interested in your comments. Please send me your feedback: firstname.lastname@example.org.
This article originally appeared in the issue of Transforming Data with Intelligence.
James E. Powell is the editorial director of the Business Intelligence Journal and BI This Week newsletter.