Teradata DBA Training in Pune

Advantages Of Teradata

The increased data block size allows storing more rows per data block. As a result, with each I/O operation, a larger amount of rows can be written and read. Larger rows lead to performance advantages:

• Firstly, the performance of queries which use large spool tables can be improved. Typically, these are queries doing full table scans, such as queries related to strategic workload.
• Full table scan performance improvement is not restricted to read operations but includes updates and insert…select statements.
• The performance of TPT jobs with an update, insert and delete steps can be improved.
• Depending on the nature of the data, big data blocks can improve the compressionfactor of block level compression (BLC). With each data block holding a larger amount of rows, the algorithms used for block-level compression may be able to achieve better results when scanning the rows for common patterns being compressed.
• The performance of tables containing wide rows will be improved. As an example: When using 127.5 KB sized data blocks, only one 64KB row fits into each data block. The system needs one I/O to read each row. By increasing the data block size, I/O operations will become more efficient.
• The performance of sort operations can be faster than with smaller data blocks as each sorted buffer can hold and work more rows at the same time.

In-Memory Optimization

• Teradata Database 15.10 includes engineering advancements that deliver analytic performance and system efficiency through memory and CPU optimizations, which enable customers to seamlessly and automatically achieve new levels of analytic performance.
• More specifically, Teradata Intelligent Memory has been enhanced to better leverage memory and CPU with a reduced load on memory bandwidth, improved CPU efficiency, reduced I/O traffic to disk, and improved overall system efficiency.

Faster Performance with JSON Data

• Teradata is the first to allow customers to natively store three JSON data formats in a single database providing faster querying performance for JSON data along with other operational and historical business data.
• The enhancements allow users to take full business advantage of JSON data from web applications, sensors, and Internet of Things (IoT)-connected machines. The choice of three formats includes BSON, UBJSON, and the previously available JSON format.
• Customers can seamlessly mix and match the three JSON storage formats based on business needs and data attributes to drive faster query performance.

World's Most Advanced Hybrid Row/Column Database

• Teradata's hybrid row/column capability enhancements provide quicker access to data stored in columnar tables, which drive faster query performance for more agile business decisions.
• Other relational database management systems store data in rows or columns, and each method offers unique benefits, depending on the application and type of data. However, they have been mutually exclusive.
• Teradata's hybrid row and column capabilities allow the best of both worlds. The enhancements in Teradata 15.10 provide even faster and more precise access to the specific data needed for a query, improving performance and query concurrency.

Software-Defined Warehouse

• The Software-Defined Warehouseenables organizations to consolidate multiple data warehouses into one system with simpler data warehouse management, consistent performance, security, as well as the cost-savings of maintaining a single system.
• Many organizations maintain multiple, separate data warehouses to meet unique business unit requirements or to comply with data privacy regulations across countries.
• In addition, the Teradata Database includes Secure Zones, which separates data and groups of users for each entity, with secure boundaries between them.
• This enables compliance with security and privacy laws that prohibit co-location of data from multiple business entities.

Data Fabric Orchestrates Powerful Ecosystem –

• Teradata® QueryGrid™software enables the data fabric that turns multiple best-of-breed solutions into an orchestrated analytical ecosystem.
• The new Teradata Database 15.10 incremental planning optimization feature now works with Teradata® QueryGrid™ to execute queries faster when using data from other systems.
• For example, Hadoop data can be pulled seamlessly into the Teradata Database from a business intelligence tool. Teradata QueryGrid allows companies to overcome the limitations of using many different technologies for operational and analytical systems, which are sourced from different vendors.
• The data fabric weaves together multiple analytics, diverse data repositories, and disparate systems to provide business users a cohesive and uninterrupted analytic ecosystem. The data fabric puts the focus on getting answers to business questions, and not on the underlying IT process or infrastructure.