Why enterprise data warehouse offloading?

The explosive growth of data has forced organizations to use their enterprise data warehouse (EDW) for purposes that it was never intended for — including running extraction, transformation and loading (ETL) workloads and storing large volumes of unused data. New types of data, updated analytics practices and more efficient, cost-effective methods of storing and accessing data have put an additional strain on EDW infrastructures.

One of the most effective modernization approaches is offloading EDW data and ETL workloads to an Apache Hadoop data lake, reducing cost and EDW performance strain.

IBM's complete, proven solution for EDW supports data movement, quality, governance and replication. It provides a scalable, high-performance platform that enables you to leverage your team's existing skills and data integration job assets while realizing all the benefits of data offloading.

IBM has an unmatched modular solution for data warehouse offloading

Move

Extract, move and ingest massive amounts of data with a shared-nothing, parallel platform without limiting your performance.

Get started:

-> IBM InfoSphere® DataStage®

-> IBM BigInsights® BigIntegrate

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Transform and integrate

Build a job once and run it in the enterprise data warehouse, in the extract, transform, load (ETL) grid and in Hadoop without modification, using existing developer skills and ETL assets.

Get started:

-> IBM Infosphere DataStage

-> IBM BigInsights BigIntegrate

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Improve data quality

Eliminate ”garbage in, garbage out” analytics and reporting by implementing comprehensive, fast and scalable data quality processing.

Get started:

-> IBM QualityStage®

-> IBM BigInsights BigQuality

-> IBM InfoSphere Information Analyzer

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Govern your data

Keep your data lake from becoming a data swamp by implementing comprehensive data governance, including end-to-end data lineage for all your business users.

Get started:

-> IBM Information Governance Catalog

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Replication

Optimize resource use and deliver data where and when it's needed, with reduced latency and on-time updating.

Get started:

-> IBM Infosphere Data Replication

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Augment and enrich

Prepare vast amounts of structured and unstructured data for enriched analytics, machine learning and artificial intelligence.

Get started:

-> IBM QualityStage

-> IBM BigInsights BigQuality

-> IBM InfoSphere Information Analyzer

-> IBM Information Governance Catalog

 

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Enterprise data warehouse offloading with IBM DataStage

Learn about traditional ETL processing when loading an enterprise data warehouse, and an enterprise data lake architecture when you implement EDW offloading with Hadoop with IBM DataStage.

IBM DataStage facilitates enterprise data warehouse offloading

Learn how IBM DataStage is helping companies increase the efficiency of their enterprise data warehouses by offloading data and ETL processing to low-cost Hadoop clusters.

Five challenges and opportunities of data offloading

Discover how enterprise data warehouse offloading to Hadoop enables data integration, quality, governance and metadata management of your data lake.