Data-warehousing projects, when successful, can boost operating efficiency, lower operating costs, and bring companies closer to their customers. Here are four more companies who are winners in this year's Data Warehousing Institute Awards:
Metadata management might seem like something that only a database administrator would care about. But at Toyota Motor Sales USA everyone cares about the performance of the company's customer-service, financial-accounting, parts-inventory, vehicle-tracking, and order-management data warehouse applications.
Despite having access to 1.5 terabytes of data stored in the automaker's multiple data warehouses, applications using that data were taking too long to process queries. "We needed something faster," says John Gonzales, manager of data quality for enterprise data management.
Gonzales' team assembled a central repository in 2000 containing technical and business metadata. Metadata is "data about the data," such as data definitions and indexes that make it easier to locate information spread across multiple systems. Such a repository, for example, provides a consistent definition of a vehicle identification number even if VINs are defined differently in vehicle tracking, auto warranty, and parts inventories within different databases.
To build the repository, Toyota used PowerCenter data-integration software from Informatica Corp., data-profiling software from Evoke Software Corp., and custom-developed data-quality and metadata-management tools. The system won The Data Warehousing Institute's award for best data warehouse in the metadata management category.
The repository does more than improve the performance of Toyota's data warehouses. IT workers and business users can access the metadata to better understand the information that's available for applications to access and for generating reports. It also provides an efficient way to maintain data quality and makes it easier to identify changes in data fields or data mappings. Says Gonzalez: "It's Toyota knowledge being put to its best use across the enterprise."
In the late 1990s Iowa had a tax gap, a polite way of describing companies and individuals who either didn't file state tax returns or under-reported their earnings. To identify noncompliant taxpayers, the Iowa Department of Revenue and Finance relied on a hodgepodge of mainframe applications, file extracts, and some 20 disparate standalone systems (databases, mainframe data, and information on individual spreadsheets, to name a few) that couldn't communicate with each other.
"Typically, when we tried to match data from one system to another, it took a long time," says Rhonda Kirkpatrick, the department's executive officer. What was needed was a central data warehouse to pull together information from all those disparate systems for analysis. But getting funding from the state for such a large-scale project wasn't an option.
So the Iowa Legislature approved a plan to build a data warehouse that would be funded using the additional tax revenue it generated by catching tax scofflaws. This unique performance-based funding approach to paying for a big-ticket government IT project earned the department The Data Warehousing Institute's award for best data warehouse by a government or nonprofit organization.
Development of the data warehouse began in November 1999 and it became operational five months later. Built using NCR Corp.'s Teradata hardware and software, the system combines data from the department's own tax and accounts-receivable systems, tax files shared by the federal Internal Revenue Service, the Iowa Workforce Development Agency, and a number of other sources. Revenue- and finance-department employees analyze the data using reporting software from Business Objects.
In the three years since it went live, the data warehouse has generated $28 million in tax revenue and is expected to generate $10 million each year from now on. The next step, Kirkpatrick says, is to use the data warehouse to better understand why taxpayers might be in noncompliance. That will involve analyzing taxpayer demographics and changes in tax laws and policies.
For large banks, knowing who their customers are can be a problem. While a customer may have a checking account, home mortgage, and financial investments all at one bank, information about those services is frequently maintained in separate databases, making it difficult for the bank to get a complete view of the customer.
BMO Financial Group (formerly the Bank of Montreal) uses a central data warehouse with application-specific data marts to get that 360-degree view of its customers, and to identify which are most profitable, most likely to respond to an offer, or in danger of switching to another bank. The system won the Data Warehouse Institute's best-practice award for use of a data warehouse for customer-relationship management.
BMO's data warehouse, assembled five years ago, uses IBM's DB2 Universal Database software running on an IBM RS/6000 SP server. The system now has 5-to-6 terabytes of customer data (8 terabytes by next year) pulled from 42 operational systems, including retail, investment, commercial, and wealth-management applications. Software from Ab Initio Software Corp. handles the data-transformation chores.
From the data warehouse, the data is moved into data marts for specific analytical tasks. One is used to calculate the profitability of individual customers. "That was one of the most important data marts we ever built," says Ted Mendes, database management services director. "You need that as a base for CRM."
BMO uses software from SAS Institute Inc. to build models that groups customers into 12 categories, such as "empty-nesters" and "young families with children," and analyzes data for customer retention, profitability, and propensity to buy additional services. IBM software is used to attach scores to individual names, such as a customer's likelihood to accept a home-loan offer or leave for another bank. These scores are re-run each month, Mendes says.
The scores are then fed into an application from Unica Corp. that develops recommendations for each customer, such as offering them a new credit card or home loan. Those, in turn, are loaded into applications from Siebel Systems Inc. used by the bank's tellers, call-center works, and other customer-facing employees and systems. The data warehouse is updated to reflect customer responses to the offers. Business-intelligence software from MicroStrategy Inc. is used to analyze customer scores and offers to see what's effective and what isn't.
Mendes' team is developing triggers for the data-warehouse system that can automatically respond to customer actions. A customer making a large deposit that boosts his account 20% or 30% above his regular balance might be offered a certificate of deposit or an investment opportunity, for example.
AT&T Wireless Services operates two data warehouses that together hold about 11 terabytes of customer-billing and call-detail records. The systems are used by some 4,000 employees and managers in customer service, finance, and sales and marketing for everything from fraud detection to calculating sales commissions to reporting the division's financial results.
With so much riding on the accuracy of the data, maintaining data integrity is critical. The processes and policies AT&T Wireless relies on to maintain data integrity earned the division The Data Warehouse Institute's award for data stewardship and data quality.
The data warehouses are an older Wisdom (wireless information system, decision enterprise management), which will be retired next year, and a new-generation EDW (enterprise data warehouse) that was built last year. Both are based on NCR Teradata hardware and software. Users extract data from the warehouse using reporting software from Business Objects SA and Web-based applications developed using Macromedia Inc.'s ColdFusion.
AT&T Wireless' data-integrity program, begun in 1999, emphasizes data stewardship and gives the users of the data warehouse ownership of the data within. Designated representatives in marketing, for example, "own" data that pertains to distribution channels, which makes them responsible for the reference tables that define that data. Finance likewise is responsible for terms such as customer churn.
"Users have to be able to make the best decisions with the best-quality data," says Deanne Larson, data warehouse program-management director. The goal of the data-integrity program is to assure users that the data is meaningful, useful, and provides value to the business, she says.
A rigorous change-control process ensures that changes in data definitions don't negatively affect other data. Proposed changes are simulated using test scripts developed with Teradata utilities to gauge their impact. Data-warehouse managers also conduct extensive audits in conjunction with users when adding a new data source to the system to be sure it will meet data-integrity standards and user needs. And AT&T Wireless has well-defined procedures for users to submit questions and feedback to the data-warehouse management team and processes for investigating those issues.