How Is The Teradata Database Used?

How Is the Teradata Database Used?

Each Teradata Database implementation can model a company's business. The ability to keep up with rapid changes in today's business environment makes the Teradata Database an ideal foundation for many applications, including:

Enterprise data warehousing:

         Data warehousing is a process for properly assembling and managing data from various servers to answer business-critical questions. The Teradata Database is ideal for enterprise data warehousing, which is commonly characterized by:

• Multiple subject areas
• Many concurrent users
• Many concurrent queries, including ad-hoc queries
• Large quantity of tables
• Hundreds of gigabytes (and terabytes) of detail data
• Historical data stored (months or years)

Without an enterprise data warehouse, a financial institution may be able to identify profitable customers for separate products such as mortgages or credit cards, but not know the overall profitability of each customer. An enterprise data warehouse brings together the different subject areas into a central repository, creating "one single view of the business " for a complete picture of the customer.

An enterprise data warehouse environment built on the Teradata Database simplifies the system maintenance task, resulting in a lower total cost of ownership. In addition, the Teradata Database's ability to handle large-scale, decision-support queries against huge volumes of detail data makes it the obvious choice for companies wanting to start at any level and grow.

·         Active data warehousing:

The active data warehouse extends a company's ability beyond historical data and strategic decisions to bring the decision-making capability to front-line personnel. The tactical decisions such as, "Who should get the empty seat on this airplane?" or "What should I offer this customer to keep her from leaving, based on her history with our company?" can be made more effectively with the right information. Technically, the active data warehouse must deliver performance, scalability, availability, and data freshness:

With an active data warehouse, employees who interact directly with customers and suppliers are empowered with information-based decision making at their fingertips. The Teradata Warehouse supports active data warehousing with:

• Capability to handle thousands of additional users and mixed workloads
• High availability and reliability to support mission-critical applications
• Scalability to accommodate an increase in the amount of data, the number of data sources, and the number of applications supported in the data warehouse environment

·         Customer relationship management:

Customer Relationship Management solutions help companies capture and analyze data to maximize customer acquisition, retention, and profitability. You can use the Teradata Database's detailed data and analysis capabilities to identify and optimize business relationships with the highest potential of profitability and growth. Examples include:

• A telephone company can conduct and refine marketing programs targeted at a certain type of profitable customer.
• A supermarket can create incentives based on specific combinations of products that customers tend to buy together.
• A bank can recognize changes in a customer’s life circumstances, such as a new baby or a college-bound son or daughter, and offer timely services such as a new home loan, mortgage insurance, additional checking account, extra credit card, or student loan.
• A retailer can run a department store credit card sales program and filter out those customers who already have that card.

Teradata's CRM solution, Teradata Relationship Manager, consists of software, professional and customer services, and the Teradata Database to create, maintain, and enhance customer relationships.

  

Internet and E-Business:

The Teradata Database provides a single repository for customer information that helps E-Businesses build and maintain one-to-one customer relationships that are critical to their success on the Internet. The Teradata Database supports the fast-paced style of E-Business by allowing many concurrent users to ask complicated questions as they think of them -- and get quick answers.

The Teradata Database allows E-Businesses to:

• Capture massive amounts of click-stream data.
• Enable multiple users to ask complex questions of the customer' click-stream data with near real-time response.
• Protect customers' privacy with consumer opt-in/opt-out preferences and ability for consumers to check and revise their information stored on the Teradata Database through the Internet or a company call center.

  Data marts:

A data mart is a special purpose subset of a company's enterprise data used by a particular department, function, or application. Often, these single-subject area data marts contain data that was aggregated or transformed in some way to better handle the requests of a specific user community. Vendors implement data marts using different architectures:

• Independent data marts - Created directly from operational systems to an individual data store.
• Dependent data marts - Created from detail data in the data warehouse. It still requires movement and transformation of data, but may provide better performance for some specific user queries.
• Logical data marts - Existing parts of the data warehouse, not separate physical structures. Because in theory the data warehouse contains the detail data of the entire enterprise, a logical data mart would then provide the specific information for a specific user community. With the proper technology, this can be an ideal way to remove the need for massive data loading and transforming.

Independent and dependent data marts are architectures endorsed by other database vendors and tend to be associated with higher maintenance costs for physically moving and maintaining the data, inconsistent data (and resulting inconsistent decisions), and indirect ways to get the complete picture of the data. The Teradata Database is ideal for the logical data mart environment, where different user communities view subsets of a single repository of enterprise data.