New York, NY -- (SBWIRE) -- 11/16/2018 -- Today, due to the increasing awareness of big data analytics and cloud, data has become an integral part of every organization. Everyday massive amount of data is created, distributed and collated to make a business decision. In order to store this data, different technologies, and techniques are used. Enterprise Data Lake is one of such methods where the data is stored in raw native form until a need to analyze data arises. Enterprise Data Lake has a flat architecture to store data where every element is allocated a distinctive identifier and is tagged with a set of extended metadata tags. Whenever any query arises, the storage can be queried for that particular data, and that small data set is then analyzed. Enterprise Data Lakes are storage repositories with an analytics and action purpose. They are designed for big data analytics and are also used to solve the data silo challenge in big data.

In Enterprise Data Lake, multiple rows of data archives are there with emails, spreadsheets, and other contents. The entire reservoir of data is a set where analytics is run. After this, the output data is then processed and analyzed. After this process is done, all the data can be easily accessed to gain insights.

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Enterprise Data Lake: Drivers and Restraints

Every organization creates a vast amount of data, but no every time, all the data is essential or needed. Enterprise Data Lake gives the freedom to store data, analyze and use whenever needed. Also, it allows even petabytes of data or trillions of objects to be stored and also enable users to develop large programs parallel easily. Such factors drive the usage of enterprise Data Lake.

The factors restraining the growth of enterprise Data Lake market are the challenges faced for working with traditional data storage and analytical technologies. Also, to analyze data, the processing power is reduced. Such factors hinder the adoption of technology.

Enterprise Data Lake: Segmentation

Segmentation based on component of Enterprise Data Lake in Market:

Software
Services
Segmentation based on type of deployment in Enterprise Data Lake in Market:

On-Premise
On Cloud
Segmentation based on type of enterprise in Enterprise Data Lake in Market:

Larger enterprise
Medium enterprise
Small enterprise
Enterprise Data Lake: Competitive Landscape

The key players in the market are SAP SE, Microsoft Corporation, Cloudwick Inc., SAS Institute Inc., Informatica Corporation, Teradata Corporation, Oracle Corporation, HVR Software B.V., IBM Corporation, Podium Data, Inc., Zaloni, Inc. and Snowflake Computing Inc.

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Regional Overview

North America is expected to be the largest market for Enterprise Data Lake market. The majority of Enterprise Data Lake vendors such as Microsoft Corporation, Oracle Corporation, and IBM Corporation are based in North America region. This is attributed to increasing volumes and importance of data in an organization. The market is anticipated to grow in Europe region due to the presence of other market vendors like SAP SE and few others in the region.