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Jun 29, 2018
Many enterprises begin their journey toward the data warehouse of the future by offloading their ETL processes into Hadoop, resulting in significant cost savings. Once they have a Hadoop cluster up and running, the next logical steps are to expand their use of Hadoop by first creating an active archive and then a data repository.
Most organizations have structured data they rarely access, but do not want to delete. Moving this cold data into Hadoop for active archive keeps the data available for analytics and search while lowering costs. In fact, according to one study, storing data in Hadoop instead of a legacy data warehouse saved organizations $15 million on hardware costs.
After that, enterprises can create a data repository by moving siloed and unstructured data to Hadoop. This makes more data available for advanced analytics, which helps companies increase profits, reduce fraud, decrease reporting costs and boost productivity. It also sets them up for the final step in the journey: Lambda Architecture with In-Memory Technology.
This white paper details the reasons for and benefits of using Hadoop for creating an active archive and a data repository and includes helpful tips for expanding your use of Hadoop.