Teradata® QueryGrid™ lets users benefit from all data in a unified architecture and beyond, regardless of where it’s stored.
As the role of analytics within organizations continues to grow, along with the number and types of data sources and processing requirements, companies face increasing IT complexity. Much of the complexity arises from the proliferation of non-integrated systems from different vendors, each of which is designed for a specific analytic task.
This challenge is best addressed by the Teradata® Unified Data Architecture™, which enables businesses to take advantage of new data sources, data types and processing requirements across the Teradata Database, Teradata Aster Database and open-source Apache™ Hadoop®. Teradata QueryGrid™ optimizes and simplifies access to the systems and data within the Unified Data Architecture and beyond to other source systems; delivering seamless multi-system analytics to end-users.
This enabling solution orchestrates processing to present a unified analytical environment to the business. It also provides fast, intelligent links between the systems to enhance processing and data movement while leveraging the unique capabilities of each platform. Teradata Database 15.0 brings new capabilities to enable this virtual computing, building on existing features and laying the groundwork for future enhancements.
One System With Seamless Operations
Teradata QueryGrid delivers transparent data access and local processing across the systems within the Unified Data Architecture. (See figure.) It takes advantage of each system’s specialized engines by sending parts of queries—and even data if necessary—to the other platforms for execution. Data placement and movement are optimized and intelligent query processing is automated for best overall results. This allows organizations to reap the most value from their unified architecture by easily and transparently pushing analytics to the data or moving the data to the right analytic platform, all without IT intervention and by allowing users to send their query to only one system; either the Teradata Database or the Teradata Aster Database.
For example, a user will submit a single request to the Teradata Database and receive a completed result back, but some of the work may be performed on one of the other platforms. Other systems get involved because they have the needed data or can perform a function that the Teradata Database cannot.
Once this multi-system analytics vision is fully implemented, Teradata QueryGrid will act as an orchestration layer to utilize the resources of multiple heterogeneous processing engines to complete a query sent to the Teradata Database or the Teradata Aster Database. Each database will be able to push analytics to the data on another platform by requesting a piece of the query be executed there, and it can get data from or send data to the other platform for use in the query. This allows the specialized functions available only in the target system to operate on the data. Each system can be used for its specialized processing capabilities and the data it holds.
Multi-system analytics powered by Teradata QueryGrid delivers functions that help organizations become more effective and efficient. For instance, analysts may want to retrieve data that resides in Hadoop for use in a Teradata Database query. Hadoop offers a useful data platform for holding large volumes of data that have not yet been proven valuable to store in the data warehouse. An analyst can issue a query to the Teradata Database and request to use data stored in Hadoop.
A growing trend in the auto insurance business is the use of telematics in which a driver’s behavior is monitored directly and the information is transmitted to an insurance company. The company assesses the risk the driver poses and charges premiums accordingly. This massive collection of raw telematics data can be stored in Hadoop. An analyst can use the Teradata Aster Database to perform a path analysis on the telematics data to determine which driving behaviors are most likely to lead to an accident, such as frequent hard breaking followed by sudden lane changes. Once identified, those patterns can be loaded into the Teradata Database for analysis. The analyst can then write a query to the Teradata Database that moves a filtered set of telematics data from Hadoop into the data warehouse for analysis against the patterns to identify drivers with the highest risk. The risk information is cross-referenced with customer data in the warehouse to determine whether a driver is a high- or low-value customer, and the analyst can then make recommendations on insurance premium adjustments.
As this virtual computing continues to grow in functionality, even more advanced capabilities will be enabled, such as executing advanced processing across systems. For example, customer retention agent may be dealing with an unhappy customer at risk of defecting may already have information about the value of the customer. However, the agent won’t know whether this is a highly influential customer who can positively or negatively affect the beliefs and behavior of others within his or her social network.
The call center agent can run a query to determine the social influence of the customer. The query will be submitted to the Teradata Database and in the background, customer data is sent to the Teradata Aster Database where a graph analysis determines the user’s sphere of influence. Results are returned to the Teradata Database for a quantitative measure of the customer’s value based on social influence. The agent then has the data needed to make an informed decision.
The Bar is Raised
Teradata QueryGrid is a powerful enabler of technologies within and beyond the Unified Data Architecture that delivers seamless data access and localized processing. It empowers users to immediately and automatically access and benefit from all their data along with a wide range of processing capabilities, all without IT intervention. This solution raises the bar for enterprise analytics and gives companies a clear competitive advantage.
Imad Birouty is a marketing manager for Teradata’s high-availability solutions and total cost of ownership program.