The IoT and IIoT need embedded analytics to make sense of all this multidisciplinary data
Embedded analytics aims to provide higher accessibility of business intelligence and analysis of data to the various users of an organization. Traditional business analytics or intelligence is aimed at extracting 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’re capable of analyzing huge quantities of multi-domain data and extracting business specific data.
Embedded analytics are now being integrated into many business applications, such as customer relationship management (CRM) and enterprise resource planning (ERP). Business intelligence is an aggregate of independent systems, such as people, processes, and technologies among others, which provide a central view on the multi-domain data gathered and analyzed. Such systems are primarily used to perform data analysis and involve different application types.
Embedded analytics, on the other hand, are a part of modern business applications and 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. Integrating embedded analytics within business applications, such as accounting software and ERP, lets users generate visualization tools and specific analytical data immediately, which in turn has been promoting the growth of this market.
In addition, the huge growth in demand for IoT, Industrial IoT, and big data has led to huge amounts of multidisciplinary data. Analysis of such data, for offering customized solutions to customers and achieving a competitive edge over rivals, has become of prime importance for businesses. In turn, it is boosting the growth of embedded analytics market. This market is also generating huge amounts of multidisciplinary data, which is of specific interest to various companies. This, in turn, further promotes the growth of the global embedded analytics market. A key trend in this market, as scene in a recent study, 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, commercial and non-commercial. Commercial was the largest segment in 2015 and is expected to remain that way. The large market share can be attributed to the higher use of commercial business intelligence applications having built-in embedded analytics.
In the “end-user” industry, the market has been segmented into seven types: banking, financial services and insurance (BFSI); retail; manufacturing; consumer goods; healthcare; education; and others, like construction and government among others. BFSI was the largest segment in 2015. And the market is segmented into five regions: North America, Europe, Asia Pacific (APAC), South America, and Middle-East and Africa (MEA). North America was the largest segment in 2015, but is expected to lose significant share to APAC during the next forecast period.
The key vendors of the embedded analytics market globally are Sisense, Pentaho (Hitachi Data Systems), Yellowfin Business Intelligence, MicroStrategy, Tableau Software, Birst, Logi Analytics, Tibco Software, BellaDati, and GoodData.