In memory analytics may be defined as a method to querying data at the time it is present in Random Access Memory (RAM) of computer with contrast to querying of data which gets stored in physical disks. This in turn aims at shortening query response times and allowing analytic applications and business intelligence (BI) with an objective to support quick and fast business decisions. Trend shows that analytics and various reporting has changed considerably as previously information was used to extract from mainframe systems and thereby transferred to spreadsheets for further analysis. With the maturing of technology, beginning of service-based architecture has become important and emerged as business intelligence (BI). However, with the advent of in-memory analytics, expectation of organizations from BI solutions has also increased .In addition, in-memory analysis delivers rapid access to various interactive dashboards that user tends to easily modify and build simply as it helps in quering the data stored in RAM (random access memory).
Global In Memory Analytics market is segmented into component, application and end use industry. Component segment is further bifurcated into software and services. Based on application, the market is further segmented into risk management and fraud detection, financial management, predictive asset management, sales and marketing optimization and product and process management among others. In terms of end user industry the market is segmented into BFSI, defense, healthcare, telecommunications, energy and transportation among others. The major driving factors responsible for the growth of global In Memory Analytics market include technological advancements in computation of power, growing trend for self-service BI Tools, digital transformation using real-time data analytics and growth in volume of data. The application of in-memory analytics is growing at a rapid pace among businesses owing to proactively avoid major financial and operational risks and enhanced risk intelligence capabilities. In addition there has been higher adoption of on-premises deployment model owing to the need to protect sensitive business data in comparison to the cloud deployment model. However, lack of awareness regarding the concept of in memory analytics is restraining the growth of global In Memory Analytics market. In addition lack of developer skills and end user to deploy business intelligence applications is also hampering the growth of this market. In addition, improved security and scalability with cloud-based in-memory analytics followed by higher adoption rate by SMBS serves as opportunities for the global In Memory Analytics Market.
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Globally, on the basis of geography, In Memory Analytics market has been segmented into North America, Asia Pacific, Europe, Latin America and Middle- East and Africa (MEA). In 2016, North America held the largest share of the In Memory Analytics market owing to the early adoption of new technologies in this region. In addition, presence of large number of in-memory analytics vendors in North America also aims at consolidating the majority of revenues in the In Memory Analytics market. Europe followed North America in the global In Memory Analytics market in terms of revenue. Asia Pacific is expected to grow at fastest rate during the forecast period. Demand for cost-effective analytical software and services among Small and Medium-Sized Businesses (SMBs) followed by growing technology expenditures in countries such as China & India is acting as a driving factor in the growth of global In Memory Analytics market All these factors are expected to increase the demand of In Memory Analytics market during the forecast period from 2017- 2025.
The major players operating in the global In Memory Analytics market includes SAP SE (Germany), Kognitio ( England), Hitachi Group Company (Japan), Oracle Corporation (The U.S.), Information Builders (The U.S.), Amazon Web Services (The U.S.), ADVIZOR Solutions (The U.S.), Micro Strategy Incorporated (The U.S.) and IBM Corporation (The U.S.) among others .
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