Data Lake enable companies to capture, store and refine huge amounts of raw data without the cost of modeling everything up front so they can be explored in much greater detail by business analysts and other “downstream” users on demand. It’s not about dumping data into huge repositories because Hadoop makes it possible to do so cheaply; rather, it’s about joining disparate raw data and interrogating data in new ways – querying what was previously “un-query-able.”
In this way, you can get a better picture of all the interactions (customer, supplier, partner, fraudulent actor and more) with your business. Analytics on all types of data in your data lake can help you make better sense of the world around you and find new avenues of advantage over competitors.
We have also helped several industries to capture petabytes of data to perform proactive analytics on thousands of devices instead of searching for data for reactive analysis. The result is improved customer satisfaction, time to market and reduced costs for scrap waste.
Eworks is the leader in data lake implementations we have successfully implemented multiple data lake solution for various industries. A full set of technology best practices, and pre-built solution frameworks components to work with a variety of platforms and tools that accelerate time to value.
Eworks data lake services include:
- Data lake architectures: centers of competency and organizational models; governance models; metadata and data management; security, authentication and auditing; recommendations for data access and provisioning; cluster, configuration and performance optimization.
- Data lake foundations: ingest, metadata and lifecycle pilots; security models; trusted data treatments and publishing, secure export and transport to Hadoop analytics zone or external platforms.
- Data lake analytics: modeling, materialization and preparation for analytic and BI tools; event-based OLAP analytics and discovery and exploratory analytics within data labs.