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Data lakes are more manageable and secure with Teradata Loom

Thursday, June 11, 2015

Teradata Loom enhances data lake security, speeds data access, and enables better integration with the customer's analytical ecosystem

To help make data lakes more accessible and governable, Teradata, the big data analytics and marketing applications company, introduced Teradata Loom® 2.5, a complete solution for data lake management. Teradata Loom enables a wider range of users to more easily find, access, and analyse data in data lakes. This helps generate new business insights, which can be integrated with the existing analytical ecosystem to drive higher levels of productivity.

'Data lakes are growing because of their scalability and low cost, and they provide organisations access to diverse data. However, many organisations fail to gain business value from their Hadoop investments,' said Dan Harrington, executive vice president, Global Consulting and Support Services, Teradata 'The game-changing technology in our latest release of Teradata Loom makes data lakes more secure, easier to manage, faster to access, and better integrated with the customers' analytical ecosystem.'

Technical enhancements in Teradata Loom 2.5 offer users market-leading manageability and security:
Fine grain security model to access Hadoop data: Enterprise security is a key requirement for today's data lake deployments. Teradata Loom now offers automatic authentication and authorisation for users with permission to view and edit specific metadata. The enhancements readily integrate with authentication and authorisation protocols like Lightweight Directory Access Protocol (LDAP) and Kerberos.

Faster data discovery through personalisation: Teradata Loom 2.5 adds support for user personalisation, which allows users to flag data that is important and add documentation and comments. This results in a better-organised data lake that is easier to search.

Flexible and extensible 'measurement' model: Teradata Loom 2.5 adds more flexible ways to profile and manage data by adding statistical capabilities. The enhancements enable external applications and technologies to register and add their own measurements on Hadoop files. For example, Teradata Loom can measure and validate the previously calculated totals of files, the number of records loaded, and the time that loading started and stopped. These measurement capabilities ensure data integrity.



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