The Making of a Real-Time HeroThe Making of a Real-Time Hero

Born in a batch world, data warehousing has exploited technological advances to become a mission-critical resource for deciphering trends, segmenting markets, and gaining a deeper understanding of past business performance. Thanks to data warehousing, strategic decision-making is no longer confined by human limits. Automated reporting and business intelligence (BI) analysis software delivers information culled from superhuman data stores that will only get bigger and more muscular over time.

Time: There lies the rub — and the greatest challenge to the future of data warehousing. "Information latency" has become Lex Luthor to this data superhero. Time is the nemesis that most threatens its greater success and glory. Business cycles are shrinking; customer demand is fickle; and in some industries, margins are so thin that only knowledge and its immediate application can drive profitability. Meanwhile, BI is expanding beyond its brainy early adopters and heading for the enterprise — and must therefore meet the needs of a widening variety of users, some of whom need a continuous influx of fresh, "real-time" information. The popularity of enterprise dashboards and portals is raising expectations about an "always on" world in which important changes are noted by the BI system and reflected in the interface continuously. Latency must be driven out.

Metrics and monitoring to serve performance management and corporate governance objectives are also changing the nature of what's expected. Ventana Research, in a 2003 Operational Performance Management End User Report, stated that 62 percent of respondents thought measuring and monitoring of business activities and processes was "very important," with "improving efficiency" cited as the chief reason. Quite often, improving business efficiency is the primary reason for building a data warehouse. Thus, it's clear that the data warehouse will be critical to excellence in performance and process management.

As we head deeper into a new century, these influences are sending the entire concept of a data warehouse into transition. Rising alongside traditional "strategic" needs is a new set of demands for data warehouse support for operational, event-driven, and "tactical" activity that involves rapid decision-making to serve a specific process or action.

For some organizations, the urgency goes beyond serving employees and business partners. Customers are now part of the information supply chain. "With strong demand coming directly from customers that ask for fast answers to meet their needs, not a single company can afford to treat customers in a time other than 'immediately,'" says Mauricio Novaes, Loyalty Manager at Claro (SP1). "Our company has to be prepared to answer the customer's questions. It doesn't matter if the customer is on the phone with a call center, searching for information on the Web, or walking through a store. The information has to be the same: timely and correct."

To Noel-Levitz, a service provider that helps more than 1,600 colleges and universities manage enrollment, student recruitment, and retention, real-time BI is about speeding up the delivery of analytics. "Institutions make real-time decisions about the most effective ways to recruit individuals, to intervene with students at risk of dropping out, and to avert student loan default," says Tim Thein, senior vice president of the Littleton, Colorado-based company. "We use SAS analytics to score different populations — and the results must be delivered in real time. Anything less can lead to administrative inefficiencies and to less-than-optimal service for the student — the education institution's number one customer."