Kenneth Research, in its repository of market research reports, has recently added a report on In-Memory Analytics Market that emphasizes the latest trends, key opportunities, drivers, and challenges associated with the growth of the market during the forecast period, i.e., 2022 – 2031. The In-Memory Analytics Market is anticipated to grow primarily on account of the growing trade of ICT goods and services worldwide. According to the statistics by the World Bank, the exports of ICT goods globally increased from 11.164% of total goods exports in 2017 to 11.53% of total goods exports in 2019.
The U.S. Market recovers fast; In a release on May 4th, 2021, the U.S. Bureau and Economic Analysis and U.S. Census Bureau mention the recovery in the U.S. International trade in March 2021. Exports in the country reached $200 billion, up by $12.4 billion in Feb 2021. Following the continuous incremental trend, imports tallied at $274.5 billion, picked up by $16.4 billion in Feb 2021. However, as COVID19 still haunts the economies across the globe, year-over-year (y-o-y) average exports in the U.S. declined by $7.0 billion from March 2020 till March 2021 whilst imports increased by $20.7 billion during the same time. This definitely shows how the market is trying to recover back and this will have a direct impact on the Healthcare/ICT/Chemical industries, creating a huge demand for In-Memory Analytics Market products.
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The Global In-Memory Analytics Market was valued at USD 1.08 billion in 2016 and is projected to reach USD 8.2 billion by 2025, growing at a CAGR of 25.35% from 2017 to 2025.
In-memory analytics is enterprise architecture framework solution used to enhance business intelligence reporting by querying data from system memory. It works by increasing the speed, performance and reliability when querying data. With the evolution of BI and RAM hardware technology, more BI platforms are available and affordable, including in-memory analytics tools used to facilitate enterprise decision making. Benefits of In-memory analytics include â€“ high performance speed, cost efficient, and reduces the dependence on IT expert.
1. Market Drivers
1.1 Rising adoption by small and medium businesses
1.2 Improved security and scalability with cloud-based In-memory analytics
1.3 Low costs for main memory hardware
1.4 Increasing volume of data
1.5 Rising trend for self-service BI tools
1.6 Adoption of digital transformation using real-time data analytics
2. Market Restraints
2.1 Issues with management and maintenance of data quality
2.2 Lack of technical expertise to deploy BI applications
2.3 Poor knowledge about the technology across industries
The Global In-Memory Analytics Market is segmented on the application, organization size, component, deployment model, vertical, and region.
1.1 Product and process management
1.2 Risk management and fraud detection
1.3 Sales and marketing optimization
1.4 Supply chain optimization
1.5 Financial management
1.6 Network management
1.7 Workforce management
1.8 Predictive asset management
2. Organization Size:
2.1 Large Enterprises
2.2 Small and Medium Organizations
3. By Component:
3.2.1 Managed services
3.2.2 Professional services
188.8.131.52 Support and maintenance services
184.108.40.206 Consulting services
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4. By Deployment Mode:
5. By Vertical:
5.2 Government and Defense
5.3 IT and Telecom
5.4 Banking, Financial Services, and Insurance (BFSI)
5.5 Transportation and Logistics
5.6 Retail and e-commerce
6. By Region:
6.1 North America (U.S., Canada, Mexico)
6.2 Europe (Germany, UK, France, Rest of Europe)
6.3 Asia Pacific (China, India, Japan, Rest of Asia Pacific)
6.4 Latin America (Brazil, Argentina, Rest of Latin America)
6.5 Middle East & Africa
The major players in the market are as follows:
1. IBM Corporation
2. SAP SE
3. Software AG
4. Information Builders, Inc.
5. Advizor Solutions, Inc.
7. SAS Institute, Inc.
8. Amazon Web Services
9. Kognitio Ltd
10. Qlik Technologies, Inc.
11. Oracle Corporation
13. Hitachi Group Company
14. Microstrategy Incorporated
These major players have adopted various organic as well as inorganic growth strategies such as mergers & acquisitions, new product launches, expansions, agreements, joint ventures, partnerships, and others to strengthen their position in this market.
RESEARCH METHODOLOGY OF VERIFIED MARKET RESEARCH:
Research study on the Global In-Memory Analytics Market was performed in five phases which include Secondary research, Primary research, subject matter expert advice, quality check and final review.
The market data was analyzed and forecasted using market statistical and coherent models. Also market shares and key trends were taken into consideration while making the report. Apart from this, other data models include Vendor Positioning Grid, Market Time Line Analysis, Market Overview and Guide, Company Positioning Grid, Company Market Share Analysis, Standards of Measurement, Top to Bottom Analysis and Vendor Share Analysis.
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