Dynamic Information Management in Hadoop
When an organization decides to deploy Hadoop as data processing and data storage infrastructure to significantly reduce costs in those areas, the problem of information management in Hadoop must be addressed, or the efficient use of data stored in Hadoop by multiple stakeholders in the organization is greatly restricted. The current generation of data processing platforms, the RDBMS, has information management built in, Hadoop doesn’t.
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Automate Your Hadoop Data Management
Hadoop deployments as enterprise infrastructure are BIG, lots of data, lots of different schemas, or no schema, lots of users, lots of operations on the data. The problem of generating all of the information about the files stored in Hadoop is overwhelming if it is done manually, but Hadoop is much less useful if the information is missing. The solution is to generate the information required for data management in Hadoop automatically.
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Save Time, Save Money
We built Loom to automatically create the information (metadata) about files loaded into the Hadoop File System (HDFS), so that stakeholders can use the data efficiently for whatever problem they are trying to solve for the business. If the files are not easy to find and easy to use the cost of operating Hadoop rises dramatically. Much of the cost of operating Hadoop includes the salaries of the people working with the data. If you substantially reduce the time they spend working on the cluster, the ROI of the entire platform increases. Loom provides this ROI.
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Metadata is Required
If the goal of the enterprise and the IT group implementing Hadoop clusters is to provide a new, lower cost, more powerful data processing platform that can be used by multiple enterprise stakeholders, then information management of the data in the clusters is critical to a smoothly running platform. Loom does the job dynamically.