HOME Top Market Reports 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

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

By: marketsandmarkets.com
Publishing Date: April 2017
Report Code: TC 5178

Discount on Reports  

  Speak to Analyst Enquiry Before Buying Webinar
purchase report
download pdf  request for customisation


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% from 2017 to 2022. The report segments the market into components, deployment models, organization sizes, applications, verticals, and regions. The major growth drivers of the market include digital transformation using real-time analytics, technological advancement in computing power, and growing trend of self-service Business Intelligence (BI) tools.

Objectives of the Study

The main objective of this report is to define, describe, and forecast the global in-memory analytics market on the basis of components, deployment models, organization sizes, applications, verticals, and regions. The report provides a detailed information regarding the major factors influencing the growth of the market (drivers, restraints, opportunities, and industry-specific challenges). The report aims to strategically analyze micro-markets with respect to individual growth trends, future prospects, and contribution to the total market. The report attempts to forecast the market size with respect to five main regions, namely, North America, Europe, Asia-Pacific (APAC), the Middle East & Africa (MEA), and Latin America. The report strategically profiles key players and comprehensively analyzes their core competencies. This report also tracks and analyzes competitive developments, such as partnerships, collaborations & agreements, mergers & acquisitions, new product developments, and Research & Development (R&D) activities in the market.

The research methodology used to estimate and forecast the in-memory analytics market begun with capturing data on key vendor’s revenues through secondary research, which included directories and databases (Hoovers, Bloomberg, Businessweek, Factiva, and OneSource). The vendor offerings were also taken into consideration to determine the market segmentation. The bottom-up procedure was employed to arrive at the overall market size of the global market from the revenue of the key players in the market. After arriving at the overall market size, the total market was split into several segments and sub-segments, which were then verified through primary research by conducting extensive interviews with key people, such as CEOs, VPs, directors, and executives. The data triangulation and market breakdown procedures were employed to complete the overall market engineering process and to arrive at the exact statistics for all segments and sub-segments. The breakdown of profiles of primary is depicted in the below figure:

In-Memory Analytics Market

To know about the assumptions considered for the study, download the pdf brochure

The in-memory analytics ecosystem comprises vendors, such as SAP SE (Germany), Oracle Corporation (U.S.), Kognitio (England), MicroStrategy Inc. (U.S.), SAS Institute, Inc. (U.S.), ActiveViam (UK), IBM Corporation (U.S.), Information Builders, Inc. (U.S.), Hitachi Group Company (Japan), Software AG (Germany), Amazon Web Services (U.S.), Qlik Technologies Inc. (U.S.), ADVIZOR Solutions, Inc. (U.S.), and Exasol (Germany). Other stakeholders of the in-memory analytics market includes system integrators, Value-Added Resellers (VARs), service providers & distributors, cloud BI platform vendors, Information Technology (IT) service providers, consulting service providers, managed service providers, market research & consulting firms, and cloud service providers.

Target Audience

  • Service providers and distributors
  • In-memory analytics application builders
  • Independent Software Vendors (ISVs)
  • Analytics consulting companies
  • Enterprises
  • End-users

“The study answers several questions for the stakeholders, primarily which market segments to focus in the next two to five years for prioritizing the efforts and investments.”

Scope of the In-Memory Analytics Market Research Report

The research report categorizes the market to forecast the revenues and analyze the trends in each of the following sub-segments:

In-Memory Analytics Market by Component

  • Software
  • Service
    • Managed service
    • Professional service
      • Support and maintenance
      • Consulting service

In-Memory Analytics Market by Application

  • Risk management and fraud detection
  • Sales and marketing optimization
  • Financial management
  • Supply chain optimization
  • Predictive asset management
  • Product and process management
  • Others (network management and workforce management)

By Deployment Model

  • On-premises
  • Cloud

By Organization Size

  • Small and Medium-Sized Businesses (SMBs)
  • Large enterprises

By Industry Vertical

  • Banking, Financial Services, and Insurance (BFSI)
  • Telecommunications and IT
  • Retail and eCommerce
  • Healthcare and life sciences
  • Manufacturing
  • Government and defense
  • Energy and utilities
  • Media and entertainment
  • Transportation and logistics
  • Others (education, travel & hospitality, research and outsourcing services)

By Region

  • North America
  • Europe
  • APAC
  • MEA
  • Latin America

Available Customizations

With the given market data, MarketsandMarkets offers customizations as per the company’s specific needs. The following customization options are available for the report:

Product Analysis

  • Product matrix gives a detailed comparison of product portfolio of each company

Geographic Analysis

  • Further breakdown of the North American in-memory analytics market
  • Further breakdown of the European market
  • Further breakdown of the APAC market
  • Further breakdown of the MEA market
  • Further breakdown of the Latin American market

Company Information

  • Detailed analysis and profiling of additional market players

Technological advancements in computing power and growing inclinations towards self-service BI to drive the global in-memory analytics market

In-memory analytics is referred to as an analytical platform in which users run queries and interact with the data stored in the main memory instead of the hard disk. This approach facilitates faster query response, high performance, reduced operational costs, and encourages self-service analytics. It helps reduce the latency of data, thus enabling real-time data analysis with faster extraction of data. In-memory analytics uses the main memory of computing devices instead of the hard disk to retrieve and store data.

Various industries such as BFSI, IT & Telecom, and retail require advanced computing technologies to achieve operational efficiency and serve their customers in a better manner. Analyzing global trends in cloud computing, including their services, reveals the growth of other fields such as parallel processing, advanced software engineering, image processing, and security solutions. The growth in these fields is subsequently driving the growth of computer hardware, internet, mobile technologies, storage, and security markets. For instance, the increased availability of RAM for data storage and analysis has improved flexibility and performance of the in-memory analytics system. Moreover, the introduction of Hybrid Transactional and Analytical Processing (HTAP) enables users to analyze market trends in the minimum possible time. Retailers can track customer trends about product reviews and sales quickly.

Drastic reduction in memory prices and improved scalability and security with cloud-based solutions are major opportunities in the market

In-memory analytics is gaining traction across verticals as organizations have realized that to make timely decisions, the computation time required using traditional analytical tools needs to be reduced. In-memory analytics offers crucial benefits to enterprises such as performance improvements as well as a cost-effective alternative to data warehouses. Opportunities in the in-memory analytics market include the reduction of main memory hardware costs, improved scalability and security with cloud-based in-memory analytics, and high adoption by SMBs that is expected to boost market growth.

Declining memory prices and the adoption of 64-bit computing would increase the adoption of in-memory analytics. IBM, MicroStrategy, Qlik Technologies, SAP, and TIBCO are incorporating in-memory analytics as a key component in their BI platforms. Many organizations that are still using traditional approaches such as summary tables are also moving towards in-memory technology due to the declining prices of hardware and the advent of real-time analytics. The combination of scalable, faster in-memory and flash-based systems, coupled with falling memory prices, has improved the price/performance ratio of in-memory and flash-based analytic solutions, thus helping these architectures emerge as practical, cost-effective alternatives to disk-based database systems.

In-Memory Analytics Market Dynamics



In-Memory Analytics Market

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 In-Memory Analytics Market 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 Market
    4.2 Market Share, By Regions
    4.3 Market By Vertical and Region
    4.4 Life Cycle Analysis, By Region, 2017

5 In-Memory Analytics 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

6 In-Memory Analytics Market Analysis, By Component (Page No. - 45)
    6.1 Introduction
    6.2 Software
    6.3 Services
           6.3.1 Managed Services
           6.3.2 Professional Services
                    6.3.2.1 Support and Maintenance
                    6.3.2.2 Consulting

7 Market Analysis, By Application (Page No. - 54)
    7.1 Introduction
    7.2 Risk Management and Fraud Detection
    7.3 Sales and Marketing Optimization
    7.4 Financial Management
    7.5 Supply Chain Optimization
    7.6 Predictive Asset Management
    7.7 Product and Process Management
    7.8 Other Applications

8 In-Memory Analytics Market Analysis, By Deployment Model (Page No. - 63)
    8.1 Introduction
    8.2 On-Premises
    8.3 Cloud

9 Market Analysis, By Organization Size (Page No. - 67)
    9.1 Introduction
    9.2 Small and Medium Businesses
    9.3 Large Enterprises

10 In-Memory Analytics Market Analysis, By Vertical (Page No. - 71)
     10.1 Introduction
     10.2 BFSI
     10.3 Retail & E-Commerce
     10.4 Government & Defense
     10.5 Healthcare & Life Sciences
     10.6 Manufacturing
     10.7 Telecommunications & IT
     10.8 Energy & Utilities
     10.9 Media & Entertainment
     10.10 Transportation & Logistics
     10.11 Others

11 Geographic Analysis (Page No. - 82)
     11.1 Introduction
     11.2 North America
     11.3 Europe
     11.4 Asia-Pacific
     11.5 Middle East & Africa
     11.6 Latin America

12 In-Memory Analytics Market Competitive Landscape (Page No. - 101)
     12.1 Introduction
             12.1.1 Vanguards
             12.1.2 Innovators
             12.1.3 Dynamic
             12.1.4 Emerging
     12.2 Microquadrant
     12.3 Product Offering
     12.4 Business Strategy

13 Company Profiles (Page No. - 105)
(Business Overview, Products & Services, Key Insights, Recent Developments, SWOT Analysis, MnM View)*
     13.1 SAP SE
     13.2 Microstrategy Incorporated
     13.3 Kognitio Ltd
     13.4 SAS Institute, Inc.
     13.5 Hitachi Group Company
     13.6 Activeviam
     13.7 Oracle Corporation
     13.8 IBM Corporation
     13.9 Information Builders, Inc.
     13.10 Software AG
     13.11 Amazon Web Services
     13.12 Qlik Technologies, Inc.
     13.13 Advizor Solutions, Inc.
     13.14 Exasol

*Details on Business Overview, Products & Services, Key Insights, Recent Developments, SWOT Analysis, MnM View Might Not Be Captured in Case of Unlisted Companies.

14 Appendix (Page No. - 145)
     14.1 Key Insights of Industry Experts
     14.2 Discussion Guide
     14.3 Knowledge Store: Marketsandmarkets’ Subscription Portal
     14.4 Introducing RT: Real-Time Market Intelligence
     14.5 Available Customization
     14.6 Related Reports
     14.7 Author Details

List of Tables (72 Tables)

Table 1 Us Dollar Exchange Rate, 2014-2016
Table 2 In-Memory Analytics Market Size and Growth, 2015–2022 (USD Billion, Y-O-Y %)
Table 3 Market Size, By Component, 2015–2022 (USD Million)
Table 4 Software: Market Size, By Region, 2015–2022 (USD Million)
Table 5 Services: In-Memory Analytics Market Size, By Region, 2015–2022 (USD Million)
Table 6 Services: Market Size, By Type, 2015–2022 (USD Million)
Table 7 Managed Services:  Market Size, By Region, 2015–2022 (USD Million)
Table 8 Professional Services: Market Size, By Region, 2015–2022 (USD Million)
Table 9 Professional Services: Market Size, By Type, 2015-2022 (USD Million)
Table 10 Support and Maintenance Services: Market Size, By Region, 2015–2022 (USD Million)
Table 11 Consulting Services: Market Size, By Region, 2015–2022 (USD Million)
Table 12 In-Memory Analytics Market Size, By Application, 2015-2022 (USD Million)
Table 13 Risk Management and Fraud Detection: Market Size, By Region, 2015-2022 (USD Million)
Table 14 Sales and Marketing Optimization: Market Size, By Region, 2015-2022 (USD Million)
Table 15 Financial Management:  Market Size, By Region, 2015-2022 (USD Million)
Table 16 Supply Chain Optimization: Market Size, By Region, 2015-2022 (USD Million)
Table 17 Predictive Asset Management: Market Size, By Region, 2015-2022 (USD Million)
Table 18 Product and Process Management: Market Size, By Region, 2015-2022 (USD Million)
Table 19 Other Applications: Market Size, By Region, 2015-2022 (USD Million)
Table 20 In-Memory Analytics Market Size, By Deployment Model, 2015-2022 (USD Million)
Table 21 On-Premises: Market Size, By Region, 2015-2022 (USD Million)
Table 22 Cloud: Market Size, By Region, 2015-2022 (USD Million)
Table 23 Market Size, By Organization Size, 2015–2022 (USD Million)
Table 24 Small and Medium Businesses: Market Size, By Region, 2015–2022 (USD Million)
Table 25 Large Enterprises: Market Size, By Region, 2015–2022 (USD Million)
Table 26 In-Memory Analytics Market Size, By Vertical, 2015–2022 (USD Million)
Table 27 BFSI: Market Size, By Region, 2015–2022 (USD Million)
Table 28 Retail & E-Commerce: Market Size, By Region, 2015–2022 (USD Million)
Table 29 Government & Defense: Market Size, By Region, 2015–2022 (USD Million)
Table 30 Healthcare & Life Sciences:  Market Size, By Region, 2015–2022 (USD Million)
Table 31 Manufacturing: Market Size, By Region, 2015–2022 (USD Million)
Table 32 Telecommunications & It: Market Size, By Region, 2015–2022 (USD Million)
Table 33 Energy & Utilities: Market Size, By Region, 2015–2022 (USD Million)
Table 34 Media & Entertainment: Market Size, By Region, 2015–2022 (USD Million)
Table 35 Transportation & Logistics: Market Size, By Region, 2015–2022 (USD Million)
Table 36 Others: Market Size, By Region, 2015–2022 (USD Million)
Table 37 In-Memory Analytics Market Size, By Region, 2015-2022 (USD Million)
Table 38 North America: Market Size, By Component, 2015-2022 (USD Million)
Table 39 North America: Market Size, By Service, 2015-2022 (USD Million)
Table 40 North America: Market Size, By Professional Services, 2015-2022 (USD Million)
Table 41 North America:  Market Size, By Deployment Model, 2015-2022 (USD Million)
Table 42 North America: Market Size, By Vertical, 2015-2022 (USD Million)
Table 43 North America: Market Size, By Application, 2015-2022 (USD Million)
Table 44 North America: Market Size, By Organization Size, 2015-2022 (USD Million)
Table 45 Europe: In-Memory Analytics Market Size, By Component 2015-2022 (USD Million)
Table 46 Europe: Market Size, By Service, 2015-2022 (USD Million)
Table 47 Europe: Market Size, By Professional Service, 2015-2022 (USD Million)
Table 48 Europe:  Market Size, By Deployment Model, 2015-2022 (USD Million)
Table 49 Europe: Market Size, By Vertical, 2015-2022 (USD Million)
Table 50 Europe: Market Size, By Application, 2015-2022 (USD Million)
Table 51 Europe: Market Size, By Organization Size, 2015-2022 (USD Million)
Table 52 Asia-Pacific: In-Memory Analytics Market Size, By Component, 2015-2022 (USD Million)
Table 53 Asia-Pacific: Market Size, By Service, 2015-2022 (USD Million)
Table 54 Asia-Pacific: Market Size, By Professional Service, 2015-2022 (USD Million)
Table 55 Asia-Pacific:  Market Size, By Deployment Model, 2015-2022 (USD Million)
Table 56 Asia-Pacific: Market Size, By Vertical, 2015-2022 (USD Million)
Table 57 Asia-Pacific: Market Size, By Application, 2015-2022 (USD Million)
Table 58 Asia-Pacific: Market Size, By Organization Size, 2015-2022 (USD Million)
Table 59 Middle East & Africa: In-Memory Analytics Market Size, By Component, 2015-2022 (USD Million)
Table 60 Middle East & Africa: Market Size, By Service, 2015-2022 (USD Million)
Table 61 Middle East & Africa: Market Size, By Professional Service, 2015-2022 (USD Million)
Table 62 Middle East & Africa:  Market Size, By Deployment Model, 2015-2022 (USD Million)
Table 63 Middle East & Africa: Market Size, By Vertical, 2015-2022 (USD Million)
Table 64 Middle East & Africa: Market Size, By Application, 2015-2022 (USD Million)
Table 65 Middle East & Africa: Market Size, By Organization Size, 2015-2022 (USD Million)
Table 66 Latin America: In-Memory Analytics Market Size, By Component, 2015-2022 (USD Million)
Table 67 Latin America: Market Size, By Service, 2015-2022 (USD Million)
Table 68 Latin America: Market Size, By Professional Service, 2015-2022 (USD Million)
Table 69 Latin America: Market Size, By Deployment Model, 2015-2022 (USD Million)
Table 70 Latin America: Market Size, By Vertical, 2015-2022 (USD Million)
Table 71 Latin America: Market Size, By Application, 2015-2022 (USD Million)
Table 72 Latin America: Market Size, By Organization Size, 2015-2022 (USD Million)

List of Figures (40 Figures)

Figure 1 In-Memory Analytics Market: Market Segmentation
Figure 2 Research Design
Figure 3 Research Methodology
Figure 4 Breakdown of Primary Interviews: By Company, Designation, and Region
Figure 5 Data Triangulation
Figure 6 Market Size Estimation Methodology: Bottom-Up Approach
Figure 7 Market Size Estimation Methodology: Top-Down Approach
Figure 8 Global In-Memory Analytics Market is Expected to Grow at A Rapid Pace During the Forecast Period
Figure 9 Market Snapshot By Component (2017 Vs 2022)
Figure 10 Market Snapshot By Service (2017–2022)
Figure 11 In-Memory Analytics Market Snapshot By Professional Service (2017–2022)
Figure 12 Market Snapshot By Organization Size (2017 Vs 2022)
Figure 13 Market Snapshot By Application (2017–2022)
Figure 14  Market Snapshot By Deployment Model (2017–2022)
Figure 15 Market Snapshot By Vertical (2017 Vs 2022)
Figure 16 Market is Driven By the Drastic Reduction in Memory Prices and Improved Scalability and Security With Cloud-Based Solutions
Figure 17 North America Commands the In-Memory Analytics Market With Covering the Largest Market Size in 2017
Figure 18 BFSI Vertical and North America are Expected to Have the Largest Market Size in 2017
Figure 19 Asia-Pacific to Have Exponential Growth During 2017–2022
Figure 20 In-Memory Analytics Market: Drivers, Restraints, Opportunities, and Challenges
Figure 21 In-Memory Analytics Architecture
Figure 22 Service Segment is Expected to Grow at A Higher CAGR During the Forecast Period
Figure 23 Managed Services Sub segment is Expected to Grow at A Higher CAGR During the Forecast Period
Figure 24 Support and Maintenance Services Sub segment is Expected to Grow at A Higher CAGR During the Forecast Period
Figure 25 Predictive Asset Management In-Memory Analytics Application is Expected to Grow at the Highest CAGR During the Forecast Period
Figure 26 Cloud Based In-Memory Analytics Deployment Model is Expected to Grow at A Higher CAGR During the Forecast Period
Figure 27 Small and Medium Businesses Segment is Expected to Grow at A Higher CAGR During the Forecast Period
Figure 28 Retail & E-Commerce Vertical is Projected to Grow at the Highest CAGR During the Forecast Period
Figure 29 Geographic Snapshot: Asia-Pacific is Estimated to Have the Highest CAGR in the In-Memory Analytics Market
Figure 30 North America In-Memory Analytics Market Snapshot
Figure 31 Asia-Pacific Market Snapshot
Figure 32 SAP SE: Company Snapshot
Figure 33 Microstrategy Incorporated: Company Snapshot
Figure 34 SAS Institute, Inc.: Company Snapshot
Figure 35 Hitachi, Ltd.: Company Snapshot
Figure 36 Oracle Corporation: Company Snapshot
Figure 37 IBM Corporation: Company Snapshot
Figure 38 Software AG: Company Snapshot
Figure 39 Amazon Web Services: Company Snapshot
Figure 40 Qlik Technologies, Inc.: Company Snapshot

The in-memory analytics market is expected to grow from USD 1.26 Billion in 2017 to USD 3.85 Billion by 2022, at a remarkable Compound Annual Growth Rate (CAGR) 25.1% during the forecast period. Factors, such as digital transformation using real-time analytics, technological advancements in computing power, and growing trend of self-service Business Intelligence (BI) tools are expected to drive the market growth.

The report provides detailed insights into the global in-memory analytics market, which is segmented by component, application, deployment model, organization size, vertical, and region. In the component segment, the in-memory analytics software is expected to have the largest market share during the forecast period. Among applications, risk management and fraud detection is expected to continue to its dominance during the forecast period. The use of in-memory analytics is increasing among businesses to enhance their risk intelligence capabilities and proactively avoid major operational & financial risks. The on-premises deployment model has exhibited a higher adoption, compared to the cloud deployment model. The need to protect sensitive business data has fostered the adoption of on-premises solutions. However, the cloud deployment model would grow at higher a CAGR owing to improving scalability and security with cloud-based in-memory analytics solutions.

The Banking, Financial Services, and Insurance (BFSI) segment constitutes the largest market share and is expected to continue to lead the In-Memory Analytics market by 2022. The need to generate insights from the data gathered from financial transactions and customer feedback & to develop better business models would foster the demand in this vertical. The retail and eCommerce segment in expected to grow at the highest CAGR during the forecast period, owing to growing prevalence of in-memory analytics to build effective sales and marketing campaigns with proper risk assessment as per the emerging market trends. Large enterprises dominate the market in terms of revenue generation with widespread adoption of in-memory analytics for various applications, such as risk management & fraud detection, supply chain optimizations and predictive asset management. However, SMBs are expected to exhibit the highest CAGR owing to easy availability and scalability with cloud-based deployments.

The report covers all the major aspects of the in-memory analytics market and provides an in-depth analysis across the regions of North America, Europe, Asia-Pacific (APAC), Middle East & Africa (MEA), and Latin America. North America, owing to early adoption of new and emerging technologies and presence of major industry players, is expected continue to dominate the market throughout the forecast period. The APAC region is expected to grow at the highest CAGR during the forecast period owing to the growing adoption of cost-effective in-memory analytics software and services among small & medium businesses.

The in-memory analytics market faces challenges, such as management and maintenance of data quality and lack of end-user & developer skills to deploy BI applications. Lack of awareness across industries about the benefits of in-memory analytics solutions would restrain the market growth.

In-Memory Analytics Market

Major vendors that offer in-memory analytics solutions include SAP SE (Walldorf, Germany), MicroStrategy Incorporated (Virginia, U.S.), Kognitio (Berkshire, England), SAS Institute, Inc. (North Carolina, U.S.), Hitachi Group Company (Tokyo, Japan), ActiveViam (London, UK), Oracle Corporation (California, U.S.), IBM Corporation (New York, U.S.), Information Builders (New York, U.S.), Software AG (Darmstadt, Germany), Amazon Web Services (Washington, U.S.), Qlik Technologies (Pennsylvania, U.S.), ADVIZOR Solutions (Illinois, U.S.), and EXASOL (Nuremberg, Germany). These vendors have adopted different types of organic and inorganic growth strategies, such as new product launches, partnerships & collaborations, and mergers & acquisitions, to expand their offerings in the in-memory analytics market.

To speak to our analyst for a discussion on the above findings, click Speak to Analyst

Apart from established players in the industry, the new entrants in the market are introducing new in-memory analytics solutions to lure customers across multiple applications

In-Memory Analytics Market

Risk Management & Fraud Detection

Risk management and fraud detection mainly cover the enterprise risk associated with financial risk, operations risk, or risk associated with an organization’s network efficiency, and preventing company from both internal fraud activities and external fraud activities. Organizations use the risk management and fraud detection application to enhance their risk intelligence capabilities to fight risk exposures. By using advanced analytical frameworks, companies can avoid, address or quickly recover from major risk events. Risk management, along with fraud detection, has become a necessity for seamless business functioning. Taking timely inputs from the incident and risk register; analyzing, identifying, monitoring, and controlling the risk; implementing risk impact analysis; and prioritizing the risks to the enterprises, are some of the major functionalities of the risk management software.

Sales & Marketing Optimization

In-memory analytics software implemented sales and marketing optimization application assists companies in optimizing marketing spend, not in the traditional sense of applying a marketing mix model, but in delivering optimization through strategy and efficiency at the marketing process level. Additionally, the sales and marketing optimization application also incorporates the project management process and information technology management in designing and delivering tailored marketing services. This approach helps companies with quick delivery and tailored solutions which are scalable across different regions, business segments, and functions.

Financial Management

The financial management application implemented in in-memory analytics software assists companies of all sizes in the automation and transformation of their financial planning, reporting, and analysis processes. The financial management application also enables companies to anticipate performance difference, analyze root cause, assess alternatives, and enable more effective decision making and execution. On implementing in-memory analytics software along with the financial management application, companies would be able to bridge the gap between their financial performance and operational performance drivers.

Supply Chain Optimization

Supply chain is a complete arrangement of organizations, individuals, resources, information, data, and assets necessary for moving products and services from providers to the end users. Activities in the supply chain transform raw materials into finished products and finally deliver these to customers. Traditional supply chain includes elements such as suppliers, manufacturers, wholesalers, retailers, and finally, customers. The analytics application for supply chain planning and optimization offers data administration and visualization capacities for the supply chain industry. The implementation of analytics in the supply chain is gaining traction because it holds huge potential for innovations and provides a competitive advantage.

Predictive Asset Management

Assets produce a wide range of operational data which if analyzed properly can lend insight into lifecycle, efficiency, and performance. The asset management integrated platform assists users in managing physical assets and tracking equipment performance. It also provides service assurance by enabling real-time alerts and providing automated corrective actions. The key advantage of this application includes stopping unnecessary emails, telephone calls, and long spreadsheets identified with asset optimization. These factors promote the adoption of the in-memory analytics applications platform for predictive asset management. In-memory analytics solutions are finding increased usage for predictive asset management to proactively manage risks. Organizations that introduce sensors in equipment, and then use diagnostic models to learn how the sensor data is connected with product problems or failures, can then create predictive models that recommend the possibility of failure and ways to prevent it.

Product & Process Management

In-memory analytics plays an important role in product and process management. In-memory analytics capabilities, such as real-time data analysis, transactional processing analytics, and visualization tools help users enhance business processes with improvements in overall product and process data quality and analysis. The consolidation of enterprise data such as product, supplier, customers, employee, and location data, among others at a single place facilitates the optimization of business processes with increase in productivity at reduced costs. With combined process agility and trusted data, organizations can improve business efficiency & effectiveness with improved data quality.

Key questions

  • Which are the substitute products and how big is the threat from them?
  • Which are the top use cases where in-memory analytics can be implemented for revenue generation through new advancements such as artificial intelligence, IoT, and cloud computing?
  • What are the potential opportunities in the adjacent markets, such as in-memory database and streaming analytics?
  • What should be your go-to-market strategy to expand the reach into developing countries across APAC, MEA, and Latin America?

Custom Market Research Services

We will customize the research for you, in case the report listed above does not meet with your exact requirements. Our custom research will comprehensively cover the business information you require to help you arrive at strategic and profitable business decisions.

Please visit https://www.marketsandmarkets.com/knowledge-process-outsourcing-services.asp to specify your custom Research Requirement


-
Request for FREE Sample of this report Send Request