TCS Aims to Shift Data Warehouses on to AWS Cloud


Tata Consultancy Services (TCS) has launched Enterprise Data Lake (EDL) for Advanced Analytics on Amazon Web Services (AWS) to improve data warehousing.

Building and managing a data warehouse used to be a simple enough proposition for many IT organizations to pursue on their own. But as the amount and types of data that need to be analyzed to generate actionable insights in real-time the complexity associated with building and maintaining a modern data warehouse has increased exponentially.

To fill that void Tata Consultancy Services (TCS) has launched Enterprise Data Lake (EDL) for Advanced Analytics on Amazon Web Services (AWS), a reference architecture through which the building of data warehouses that employ AWS services such as Lambda, Kinesis Streams, Kinesis Firehose, S3 Dynamo DB, and Redshift can be accelerated.

Because of the massive amount of data now being collected a public cloud service such as AWS now makes the most sense when it comes to deploying a modern data warehouse, says Raman Venkatraman, vice president and global head of the Alliances and Technology Unit for TCS.

See also: Data warehouse wars will escalate in 2018

In effect, the forces of data gravity coupled with all the external sources feeding data in the warehouse are forcing the cloud decision, adds Venkatraman. Today there are more data residing on-premise than in the cloud. But the rate at which data is being generated in the cloud makes it clear that the center of data gravity in most organizations is quickly shifting to the cloud.

“Organizations are now dealing with huge sets of data,” says Venkatraman.

The reference architecture is based on TCS EDL for Advanced Analytics solution for AWS that creates a single persistent data store to house structured, semi-structured and unstructured data in its native format. TCS on top of that base is leveraging AWS machine learning algorithms to identify behavior, preferences, needs, and sentiments. Armed with that context, the data warehouse is then able to surface actionable insights in real time, says Venkatraman.

Obviously, an IT organization could still build their own reference architecture. But finding the IT staff with the expertise required to master all the capabilities that AWS exposes is problematic. Even if the organization could hire or train the required IT personnel, their ability to retain that talent represents a major challenge. Not only are competitors continually trying to poach talent, most IT services provider such as TCS are willing to pay more to attract the best IT talent available anywhere in the world.

TCS is not the only IT services provider making the case for a reference architecture for building a modern data warehouse. The issue that many IT organizations now need to come to terms with is the degree to which they want to build and manage a data warehouse versus focusing their time and effort on the analytics applications that tap into the warehouse. End users want to be able to interrogate data in real time and then employ algorithms to build models without any intervention on the part of the internal IT organization required. The days when end users had the patience to wait for IT departments to deliver a canned report are now long over.

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