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Partners 2013 LinkedIn Use Cases for Teradata Connectors for Hadoop
1. LINKEDIN USE CASES FOR
TERADATA CONNECTORS
FOR HADOOP
Eric Sun:
Jason Chen:
esun@LinkedIn.com
www.linkedin.com/in/ericsun
jason.chen@Teradata.com
www.linkedin.com/in/jason8chen
Then, through the lens of big data = “complexity” rather than “volume” – we’re seeing technology evolve that supports:new types of programming at scale such as MapReduce and graph processing engines.Better/different ways of dealing with unstructured dataLess schema dependence – have the flexibility to load data quickly, store cheaply, and process later as needed
Then, through the lens of big data = “complexity” rather than “volume” – we’re seeing technology evolve that supports:new types of programming at scale such as MapReduce and graph processing engines.Better/different ways of dealing with unstructured dataLess schema dependence – have the flexibility to load data quickly, store cheaply, and process later as needed
Then, through the lens of big data = “complexity” rather than “volume” – we’re seeing technology evolve that supports:new types of programming at scale such as MapReduce and graph processing engines.Better/different ways of dealing with unstructured dataLess schema dependence – have the flexibility to load data quickly, store cheaply, and process later as needed
Release of a SQL-H solution for the Teradata database with Teradata Database 14.10.Teradata SQL-H provides dynamic SQL access to Hadoop data in Teradata. With TeradataSQL-H, users can join Hadoop data with Teradata tables.Teradata SQL-H is important to customers because it enables analysis of Hadoop data in Teradata. It also allows standard ANSI SQL access to Hadoop data, leverages existing BI tool investments, as well as lowers costs by making data analysts self-sufficient.