Embedded analytics aims at providing higher accessibility of business intelligence and analysis of data to the various users of an organization. Traditional business analytics or intelligence is aimed at extraction of data and performing basic level of analysis. However, such applications are seldom capable of solving high level analytic problems. Embedded analytics aids in solving such problems as they are capable of analyzing huge quantities of multi domain data and extracting business specific data from the same. Embedded analytics are now being provided as an in-built part of most business applications such as customer relationship management (CRM) and enterprise resource planning (ERP) among others. Business intelligence is an aggregate of independent systems, such as people processes and technologies among others, which provides a central view point on the multi domain data gathered and analyzed. Such systems are primarily utilized for performing data analysis and involve many different types of applications. Embedded analytics, on the other hand, are a part of modern business applications and are aimed to provide specific information for supporting specific business actions or decisions. Currently, business intelligence vendors, such as Tableau Software and Sisense among others, develop embedded analytic tools, which is then integrated into business applications by the application developers and provided to the end-users.
The market for embedded analytics is primarily being driven by the increased integration of such capabilities under commonly available business applications, compared to traditionally available business intelligence platforms. The integration of embedded analytics within business applications, such as accounting software and ERP, has enabled the users to generate visualization tools and specific analytical data immediately, which in turn has been promoting the growth of the market. Additionally, the huge growth in demand for internet of things (IOT), industrial internet of things (IIOT) and big data has led to generation of huge amount of multidisciplinary data. Analysis of such data, for offering customized solutions to customers and achieving competitive edge over rivals, has become of prime importance for business entities. It in turn has been boosting the growth of embedded analytics market. Furthermore, there is a strong growing demand for smart phones and connected electronic devices. It has also been generating huge amount of multidisciplinary data, of specific interest to various companies, which has been further promoting the growth of the embedded analytics market globally. A key trend in this market, mostly involving enterprises, is the development of in-house embedded analytics solutions, which can be customized by the end user.
On the basis of applications, the embedded analytics market has been segmented into two types, namely commercial and non-commercial. Commercial applications segment was the largest segment in 2015 and is expected to remain the same during the forecast period. Such large market share can be attributed to the higher usage of commercial business intelligence applications having in built embedded analytics. On the basis of end-use industry, the market has been segmented into seven types. They are banking, financial services & insurance (BFSI), retail, manufacturing, consumer goods, healthcare, education and others. Others segment include construction and government among others. BFSI was the largest segment in 2015. The global embedded analytics market has again being segmented into five regions, namely North America, Europe, Asia Pacific (APAC), South America and Middle-East & Africa (MEA). North America was the largest segment, by region in 2015 and is expected to lose significant amount of its share to APAC during the forecast period.
The major companies of the embedded analytics market globally are Sisense, Inc. (U.S.), Pentaho Corporation [Hitachi Data Systems]. (U.S.), Yellowfin Business Intelligence (Australia), MicroStrategy, Inc. (U.S.), Tableau Software (U.S.), Birst, Inc. (U.S.), Logi Analytics, Inc. (U.S.), TIBCO Software, Inc. (U.S.), BellaDati (U.S.) and GoodData Corporation (U.S.), among various other companies.
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