Tag Archives: Teradata

Hadoop Enriches Data Science: Part 2 Of Hadoop Series

Enterprises use Hadoop in data-science applications that improve operational efficiency, grow revenues or reduce risk. Many of these data-intensive applications use Hadoop for log analysis, data mining, machine learning or image processing.

Commercial, open source or internally developed data-science applications have to tackle a lot of semi-structured, unstructured or raw data. They benefit from Hadoop’s combination of storage and processing in each data node spread across a cluster of cost-effective commodity hardware. Hadoop’s lack of fixed-schema works particularly well for answering ad-hoc queries and exploratory “what if” scenarios.

Hadoop-Enabled Data-Science Use Cases

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Posted in Big Data, Operational Efficiency | Tagged , , , , , , , , , , , , , , , , , , | Leave a comment

“Accelerate” and See the Light Sooner

Teradata Accelerate

Informatica and Teradata have worked together over the years to develop unparalleled technology integration and customer success in Enterprise Data Warehousing. We share hundreds of large scale enterprise implementations together and enjoy market leadership positions in our respective markets and a vibrant partnership.

Our latest collaboration, the Teradata “Accelerate” program seeks to replicate our joint customer success for organizations that want to see rapid results from an all in one, incremental solution. This approach makes a lot of sense in the current economic times where spend on large scale projects is harder to justify.

“Accelerate” includes all the technology and jump start kit needed to build a data warehouse. Informatica fits into the picture as the provider of the Data Integration layer of the stack, notably the only vendor for that part of the solution along with an array of BI capabilities from other vendors.

If you’re embarking on a DW project, jump on board and “Accelerate” your way to results!

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Turbocharging Data Warehousing Performance with ELT

Flipping around traditional ETL (Extract-Transform-Load) on its head is not a new practice.  ELT (Extract-Load-Transform), where processing is handled in the database, instead of the ETL server, has been proven to enhance performance in many types of data warehousing deployments.

For example, Oi, a leading telecom provider in Brazil, implemented an enterprise data warehouse (EDW) consolidating information on 36 million customers, speeding response time to customer requests.  The right-time EDW also enabled Oi to rapidly launch a successful new service offering, which made it easier for customers to recharge their pre-paid accounts for telecom service.

By implementing ELT with Informatica’s pushdown optimization capabilities for this Teradata data warehouse, Oi accelerated its data warehousing loading process two-fold.  This has led to even more timely updates of Oi’s customer information, while lowering costs.
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Posted in Data Integration, Data Warehousing, Real-Time | Tagged , , , , | Leave a comment