The Data Lake market is estimated to grow with a significant CAGR during the forecast period, i.e., 2021-2029. The increasing demand for repositories for storage of structured and unstructured data along with the need for data processing and analytics are expected to aid the growth of the market. The growth of the market can be attributed to the growing adoption of Internet of Things (IoT) which will proliferate data further. As per IBM, 2.5 Quintillion bytes of data are generated each day. In addition, owing to increase in the usage of smart meters, huge amount of data is being generated which needs the use of Data Lakes. In the United States, a total of 70,823,466 smart meters have been installed according to U.S Energy Information Administration.
The market is segmented based on type into software, and services, out of which, the services segment is anticipated to grab the larger share by the end of 2021 on account of increasing adoption of data lake solutions in the BFSI & IT industry verticals. Moreover, the need for data processing and analytics of big data for IT operation is also projected to contribute to the growth of the segment during the forecast period. The market is further segmented into data discovery, data integration & management, data lake analytics, and data visualization for software and into managed and professional services for the services segment. CLICK TO DOWNLOAD SAMPLE REPORT
On the basis of industry vertical, the Telecommunications & IT segment in the global data lake market is projected to grow with a significant CAGR over the forecast period. The growth of the segment can be attributed to the fact that data lakes aid in the storage as well as the analysis of data which can aid in developing data insights, identify trends, optimize performance and manage organizational data architecture.
Geographically, the market is segmented into North America, Latin America, Europe, Asia Pacific and the Middle East & Africa region. The market in the Asia Pacific is predicted to grow at the highest CAGR over the forecast period owing to the increasing amount of data and the need to develop solutions to store and analyse the same by major technology companies in the region. Furthermore, in 2021, the market in North America is evaluated to occupy the largest share in terms of revenue, owing to the presence of major companies in the region and their rising data volumes across industry verticals. Along with this, the North America also leads in terms of investments and adoption of big data technologies, which is also expected to contribute to the market growth in the region. Alternatively, the market in Europe is also anticipated to occupy a significant share in the data lake market on account of new regulations for data privacy that require enterprises to remove customer data upon request.
The global data lake market is further classified on the basis of region as follows:
Our in-depth analysis of the global data lake market includes the following segments:
FREQUENTLY ASKED QUESTIONS
Increasing amount of raw data produced on a daily basis and the demand for big-data analytics.
The market is anticipated to attain a significant CAGR over the forecast period, i.e., 2021-2029.
High cost of boarding and upkeep, and the need for skilled personnel are estimated to hamper the growth of the market
High cost of boarding and upkeep, and the need for skilled personnel are estimated to hamper the growth of the market.
The major players dominating the data lake market are Microsoft Corporation, Informatica Corporation, Teradata, Capgemini, and IBM among others.
The company profiles are selected on the basis of revenues generated from the product segment, geographical presence of the company which determine the revenue generating capacity as well as the new products being launched into the market by the company.
The market is segmented by type, industry vertical and region.
With respect to application, the telecommunications and IT segment is anticipated to hold the largest market share owing to large amount of data produced by the verticals and the need to store and analyse it.
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