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(Wireless-NewsWire.Com, June 25, 2018 ) According to a new market research report ""In-Memory Analytics Market by Component (Software, Services), Application (Risk Management & Fraud Detection, Sales & Marketing Optimization, and Financial Management), Deployment, Organization Size, Vertical, Region - Global Forecast to 2022", The in-memory analytics market size is expected to grow from USD 1.26 Billion in 2017 to USD 3.85 Billion by 2022, at a Compound Annual Growth Rate (CAGR) of 25.1%. The key forces driving the in-memory analytics market include the digital transformation using real-time analytics, technological advancement in computing power, growing data volume, and demand for self-service Business Intelligence (BI) tools.
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Risk management and fraud detection application segment is expected to constitute the highest market share during the forecast period
The organizations implement in-memory analytics solutions to enhance risk intelligence capabilities to fight with operational and financial risks. The companies are using advanced analytical tools to avoid, address, and quickly recover from major risk events. The risk management and fraud detection solution helps identify, monitor, analyze, and control risks.
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In-memory analytics software component is expected to contribute the largest market share in 2017
Among components, the in-memory analytics software is expected to continue its dominance throughout the forecast period. In-memory analytics solution empowers the user to perform quick data analysis and achieve real-time insights from the stored data. The falling Random Access Memory (RAM) prices and technological advancements in computing power have propelled the adoption of in-memory analytics software among end-users.
Table of Contents
1 Introduction (Page No. - 15)
1.1 Objectives of the Study
1.2 Market Definition
1.3 Market Scope
1.4 Years Considered for the Study
1.5 Currency
1.6 Stakeholders
2 Research Methodology (Page No. - 19)
2.1 Research Data
2.1.1 Secondary Data
2.1.2 Primary Data
2.1.2.1 Breakdown of Primaries
2.1.2.2 Key Industry Insights
2.2 Market Size Estimation
2.3 Research Assumptions and Limitations
2.3.1 Assumptions
2.3.2 Limitations
3 Executive Summary (Page No. - 27)
4 Premium Insights (Page No. - 32)
4.1 Attractive Opportunities in the In-Memory Analytics Market
4.2 Market Share, By Regions
4.3 Market By Vertical and Region
4.4 Life Cycle Analysis, By Region, 2017
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5 Market Overview (Page No. - 36)
5.1 Market Overview
5.1.1 Introduction
5.1.2 Market Dynamics
5.1.2.1 Drivers
5.1.2.1.1 Digital Transformation Using Real-Time Data Analytics
5.1.2.1.2 Technological Advancements in Computing Power
5.1.2.1.3 Growing Volume of Data
5.1.2.1.4 Growing Trend for Self-Service BI Tools
5.1.2.2 Restraints
5.1.2.2.1 Lack of Awareness Across Industries
5.1.2.3 Opportunities
5.1.2.3.1 Reduction of Main Memory Hardware Costs
5.1.2.3.2 Improved Scalability and Security With Cloud-Based In-Memory Analytics
5.1.2.3.3 Higher Adoption By SMBS
5.1.2.4 Challenges
5.1.2.4.1 Management and Maintenance of Data Quality
5.1.2.4.2 Lack of End User and Developer Skills to Deploy BI Applications
5.2 Industry Trends
5.2.1 Introduction
5.2.2 In-Memory Analytics Use Cases
5.2.2.1 Introduction
5.2.2.2 Use Case 1: Kognitio (Telecommunications Sector)
5.2.2.3 Use Case 2: Activeviam (Financial Services—Risk Management)
5.2.2.4 Use Case 3: Advizor Solutions Inc. (Healthcare Sector— Sudbury Regional Hospital)
5.2.3 In-Memory Analytics Architecture
5.2.3.1 In-Memory Architecture
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