Hadoop Big Data

Today’s world is generating vast amount of data at a velocity that we never expected few years back. The traditional processing systems had their own drawbacks while processing  massive volumes of variety data at a velocity .  How to handle this situation?  the simple answer is Hadoop.

The complexity of modern analytics needs is outstripping the available computing power of legacy systems. With its distributed processing, Hadoop can handle large volumes of structured and unstructured data more efficiently than the traditional enterprise data warehouse. Because Hadoop is open source and can run on commodity hardware, the initial cost savings are dramatic and continue to grow as your organizational data grows. Additionally, Hadoop has a robust Apache community behind it that continues to contribute to its advancement. Hadoop is not a database, but rather an open source software framework specifically built to handle large volumes of structure and semi-structured data.

Now hadoop is more powerful as spark can integrate with hadoop, an in memory processing engine.

Our consultants are responsible for Hadoop development and implementation. Loading from disparate data sets. Pre-processing using Hive and Pig. Designing, building, installing, configuring and supporting Hadoop.Translate complex functional and technical requirements into detailed design. Perform analysis of vast data stores and uncover insights. Maintain security and data privacy. Create scalable and high-performance web services for data tracking. High-speed querying. Managing and deploying HBase. Being a part of a POC effort to help build new Hadoop clusters. Test prototypes and oversee handover to operational teams. Propose best practices/standards.