Data technology is much in demand due to various factors such as higher acceptance of Internet of Things (IoT), increased need for business agility and accessibility, and the increasing volume and variety of business data.

Albany, NY -- (SBWire) -- 03/02/2017 --A data lake is a data storage and management platform that holds a considerably large amount of raw data in its natural format until needed. A data lake uses a flat architecture to store data and with its assistance, it becomes much easier for data scientists, developers, and analysts to store data of any shape or size, and speed, and do all types of analytics and processing across all kinds of languages and platforms

On the basis of type, the global data lakes market may be segmented into software and service. Based on business function, the market can be classified into operations, marketing, sales, finance, and human Resources. The market can be further segmented into government, BFSI, retail & ecommerce, healthcare & life sciences, telecommunication & IT, manufacturing, energy & utilities, media & entertainment, and others – based on industry vertical.

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In the report, TMR Research provides a detailed analysis of the drivers and restraints influencing the global data lakes market. It also offers insight into factors impacting the market's trajectory across various segments and regions.

Global Data Lakes Market: Key Trends

Data technology is much in demand due to various factors such as higher acceptance of Internet of Things (IoT), increased need for business agility and accessibility, and the increasing volume and variety of business data. In addition, switching from outdated data management techniques for storage to advanced techniques and huge flow of unstructured and structured data are positively impacting the market growth. On the contrary, companies operating in the industrial sectors have found that data lakes are inefficient to handle massive scale and complicated industrial data. In order to make quick, critical operational decisions, data lakes are unable to provide the real-time analysis and situational awareness that operators and engineers require, thereby limiting the market growth.

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Based on type, services form the key contributor to the global data lakes market, and the segment is expected to grow during the said period. The demand for services is high due to increased requirement for data lake software solutions across organizations. Operations are anticipated to witness a growth in the applications segment because of the rising demand of IoT-enabled technologies. These technologies are mainly used for operations in manufacturing and IT organizations. On the basis of industry vertical, BFSI is projected to account for a large share in the market. Financial service institutes as well as several financial transactions in banks are managed by IT systems, invariably increasing the volume and variety of data, hence driving the growth of global data lakes market.

Global Data Lakes Market: Regional Analysis

The global data lakes market is segmented on the basis of geography into North America, Europe, the Middle East and Africa, Asia Pacific, and Latin America. Due to early adoption of data management systems and technological advancements, North America has emerged as the chief contributor to the revenue generated by the market for global data lakes, and it is predicted that this region will further grow in the forecast period. Another market that looks promising is Asia Pacific. High adoption of technology and huge opportunities mainly across industry verticals are driving the growth of the market.

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Global Data Lakes Market: Key Players

The report profiles some of the prominent competitors functioning in the global data lakes market. It also offers insights into the threats and opportunities that the companies are expected to witness in the coming years. The global market for global data lakes is highly fragmented. Some of the key players are Microsoft Corporation, Capgemini, Informatica Corporation, Teradata, EMC Corporation, Oracle Corporation, SAP SE, Hitachi, Atos, and SAS Institute.

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