Transparency Market Research
In computing, extract, transform, and load (ETL) signifies extraction of data from large database management processes and is primarily used in data warehousing. Extract, transform, and load is abbreviated as ETL. ETL is a combination of three database processes into one tool. The tool data functions support the extraction of data from one data source and its placement into another database. In the ETL process, extract is the first and vital part of ETL functions. Extract involves gathering data from multiple and various types of data source systems. The data extracted from the ETL extract process sets the stage for subsequent processes. The extract stage decides how subsequent processes will go. Transform is the second phase of the ETL process. It is the process of altering the extracted data from its earlier data format into the required dedicated format so that it can be arranged with another database. Before converting the data, the transform process applies a series of guidelines to the extracted data in order to obtain the data for loading into the converted database. Load is the third and last phase of the ETL process. It is the process of writing the data into the end target database, which is usually a data warehouse. ETL is one of the important database functions used in business intelligence (BI). It is an information technology (IT) process through which data from multiple and different sources can be arranged in one place in order to enable the discovery of business insights through the analysis of data programmatically. ETL has been popular since 1970, the year when organizations started using various data repositories to store diversified business information. ETL solutions have gained significant traction in recent times, and the Extract, Transform, Load (ETL) Market is anticipated expand at a rapid pace between 2018 and 2026.
The global Extract, Transform, Load (ETL) Market for database extraction, transformation, and load is anticipated to expand at a significant pace. An increase in the volume of enterprise data and Big Data and the trend of Internet of things (IoT) are expected to boost demand for ETL software solutions, thus driving the Extract, Transform, Load (ETL) Market globally. ETL is being used across various organizations to store different types of business information. The adoption of cloud computing across enterprises is projected to drive demand for ETL solutions.
However, the complexity of the ETL architecture and configuration challenges are expected to hamper the Extract, Transform, Load (ETL) Market in the near future. The information technology (IT) sector is significantly adopting unconventional technologies at a remarkable pace so as to gain important business perceptions from data. This, in turn, is creating lucrative market opportunities for vendors active in the Extract, Transform, Load (ETL) Market.
The global Extract, Transform, Load (ETL) Market can be segmented based on deployment, organization size, end-use industry, and region. Based on deployment, the market can be divided into on-premise and cloud. The cloud segment can be further divided into public and private cloud. In terms of organization size, the global market can be categorized into small and medium enterprises and large enterprises. Based on end-use industry, the market can be segmented into BFSI, health care, IT and telecom, government, and others. In terms of region, the global Extract, Transform, Load (ETL) Market can be categorized into Europe, North America, Middle East & Africa, Asia Pacific, and South America. The global Extract, Transform, Load (ETL) Market analysis includes country level analysis across the U.S., Canada, the U.K., Germany, France, China, India, Australia, Japan, GCC Countries, South Africa, and Brazil. North America dominated the global Extract, Transform, Load (ETL) Market in 2017. The market in Asia Pacific is expected to expand at a rapid pace during the forecast period.
Major companies operating in the Extract, Transform, Load (ETL) Market include Informatica, IBM Corporation, Oracle Corporation, and SAP SE, Ab Initio Software, Ab Initio Software, Pervasive Software, Microsoft Corporation, and iWay Software Co.
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