Data Warehousing as a Service Market - Global Industry Trends and Forecast 2017 - 2025


Data warehousing is a type of system used for data analysis and reporting. It is deliberated as an important component of business intelligence. They are the central repositories of combined data from more than one distinct sources. Data warehousing system stores historical and current data at one single place that are used for generating analytical reports for knowledge workers throughout the enterprise. The data that are stored in the system is uploaded from the operational system. The data passes through an operational data store and requires data cleansing for extra operations to confirm the quality of the data prior to use for reporting in data warehousing. 

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The global data warehousing as a service market is primarily driven by the systematic and efficient arrangement of data. This feature considerably reduces the computing cost along with combining data in one place, thereby boosting the market growth during the forecast period. Increasing demand of big data trend is leading to the increasing demand for analytics which is also an important factor bolstering the demand of data warehousing as a service market globally. Rising demand for low latency and high speed analytics simultaneously with the escalating role of business intelligence in an enterprise management is also an important factor boosting the global data warehousing as a service market. Moreover, increasing use of mobile, social media traffic along with networked sensors is creating increasing stream of data that requires additional capabilities which is driving the market globally during the forecast period. Moreover, ongoing demand for next generation business intelligence along with the rising amount of data generation by an organization is likely to emphasize data warehousing market growth during and over the forecast period. 

Problems in managing and enhancing data quality is one of the major restraining factors in the global a data warehousing as a service market. In a data warehousing system, data is received from various disparate sources from all aspects of an organization. When a data warehouse attempts to combine the data from distinct sources, it encounters errors. 

Technological advancement is likely to be one of the major opportunity in the global market. It is likely to play an important role in addressing extreme data and real time data warehousing needs which requires advanced change detection capabilities. Evolution of programming techniques like Hadoop and MapReduce coupled with advancement in core technology, memory and storage is expected to bid an attractive market opportunity during the forecast period. 

On the basis of types, the global data warehousing as a system market is bifurcated into information processing, analytical processing and data mining. On the basis of data warehousing model, the market is bifurcated into virtual warehouse, enterprise warehouse and data mart. Based on application the market is bifurcated into consumer goods, retail, banking sectors, manufacturing sectors among others. The geographical split of the market encompasses North America, Europe, Asia Pacific, Middle East and Africa and Latin America. North America is expected to have the largest market revenue followed by Asia Pacific and Europe. Technologically advanced infrastructure is one of the important driving factor boosting the North America market. U.S. and Canada are the major countries in U.S. responsible for the market growth. 

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Some of the major players in the data warehousing as a service market encompasses International Business Machines Corporation (U.S.), Oracle Corporation (U.S.), Microsoft Corporation (U.S.), Teradata Corporation (U.S.). Other prominent players embraces Actian Corporation (U.S.), EMC Corporation (U.S.), 1010data Inc. (U.S.), InfiniDB, Inc. (U.S.), Exasol AG (Germany), Infobright Inc. (Canada), HP Co. (U.S.)., ParAccel Inc. (U.S.)., SAP AG (Germany) and Kognitio Ltd. (U.K.)among others. Key Players are assigning important and suitable importance on the validation of professional services to support data warehouse delivery.



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