Farmington, March 30, 2023 (GLOBE NEWSWIRE) -- The Global Data Analysis Market Was Valued At US$ 41.39 Billion In 2022, And Is Projected To Reach US$ 346.33 Billion By 2030, Growing at a CAGR Of 30.41% From 2023 To 2030. The global market for data analysis is made up of businesses and technologies that offer ways to process and analyse large amounts of data. In the past few years, this market has grown a lot. This is because more industries are making decisions based on data, big data and the Internet of Things (IoT) are becoming more popular, and more advanced analytical tools are now available.
Request Sample Copy of Report “Data Analysis Market Size, Share & Trends Estimation Report By Type Outlook (Big Data Analytics. Business Analytics, Customer Analytics, Risk Analytics & Statistical Analysis) By Deployment Outlook (On-premise & Cloud) By End Use Outlook (Medical Use, Cancer & Chronic Pain) By Region, And Segment Forecasts, 2022 - 2030”, published by Contrive Datum Insights.
Segmentation Overview:
Deployment Insights:
On-premises deployment means installing data analysis software on the servers and infrastructure of a company. This method of deployment gives organizations full control over their data and infrastructure, which is important for businesses that deal with sensitive information.
At the moment, deployment in the cloud is growing faster than deployment on-premises. This is because organizations in all fields are using cloud technology more and more. This has led to a rise in demand for cloud-based data analysis solutions. Also, cloud-based deployment makes things easier to get to and lets people work and work together from a distance, which has become an important need during the COVID-19 pandemic.
End User Insights:
Since a long time ago, the BFSI sector has used data analysis tools in a big way. With more competition and the need to improve customer experiences, BFSI companies are relying more on data analysis to get insights from customer data, find fraud, analyse risk, and make investment decisions.
The government is using data analysis tools more and more to improve public services and make better policies. These tools are used to look at crime, get people involved, and measure the effectiveness of policies. Other industries, like telecommunications, energy, transportation, and the media, are also using data analysis tools to improve their operations and decision-making.
Regional Outlook:
North America has been the largest market for data analysis tools because it has a lot of big companies and a lot of people who use technology. Cloud-based data analysis tools are being used by more and more people in the region, especially in the United States.
Europe is another big market for data analysis tools because people there use technology a lot and there are a lot of key players there. In areas like healthcare, retail, and manufacturing, there is a big rise in demand for data analysis tools in the region.
Asia-Pacific is the fastest-growing market for data analysis tools. This is because more people are using computers, more people want advanced analytics, and more people are using cloud-based solutions. Countries like China, India, Japan, and Australia are growing very quickly in the area.
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Scope of Report:
| Report Attributes | Details |
| Growth Rate | CAGR of 30.41% from 2023 to 2030. |
| Revenue Forecast by 2030 | USD 346.33 Billion |
| By Type | Big Data Analytics, Business Analytics, Customer Analytics, Risk Analytics, Statistical Analysis, Other |
| By Deployment | On-premise, Cloud, Other |
| By Enterprise Size | Large Enterprises, Small & Medium Enterprises (SMEs), Other |
| By End-use | BFSI, Government, Healthcare, IT & Telecom, Military & Defense, Other |
| By Companies | Altair Engineering, Inc., Fair Isaac Corporation (FICO), International Business Machines Corporation, KNIME, Microsoft Corporation, Oracle Corporation, RapidMiner, Inc., SAP SE, SAS Institute Inc., Trianz |
| Regions and Countries Covered |
|
| Base Year | 2022 |
| Historical Year | 2017 to 2022 |
| Forecast Year | 2023 to 2030 |
Market Dynamics:
Driving Factors:
Growing adoption of cloud computing: With cloud computing, businesses can get to their data and analyze it from anywhere, at any time. Compared to traditional on-premises tools, cloud-based data analysis tools are also more cost-effective and scalable.
Emergence of artificial intelligence and machine learning: Artificial intelligence and machine learning algorithms are being used more and more, which is driving the need for advanced data analysis tools that can use these technologies to get insights from data.
Need for better customer engagement: Companies are using tools for data analysis to learn more about how customers act, what they like, and what they need. This helps them give customers more personalized experiences and keep them more interested.
Restraining Factors:
High cost of implementation: For small and medium-sized businesses, especially, the cost of putting in place advanced data analysis tools can be high. This can make it hard for some businesses to make the necessary investments.
Integration challenges: It can be hard and take a long time to connect data analysis tools to existing systems and workflows. This can cause delays and make the whole process more expensive.
Lack of standardization: The market for data analysis is not standardized, so there are many different tools and technologies to choose from. This can make it hard for businesses to figure out which solution is best for them.
Opportunity Factors:
Development of cloud-based solutions: Cloud computing is becoming more popular, and there is a growing need for cloud-based data analysis tools. This gives data analysis companies a chance to make cloud-based solutions that are easier to use and less expensive than traditional solutions that are installed on-site.
Need for real-time analytics: Businesses are looking for more and more ways to get insights from data as it is being created. This gives data analysis companies a chance to come up with real-time analytics solutions that can give insights right away.
Challenges Factors:
Personalization of customer interactions: As the need for personalized interactions with customers grows, businesses have a chance to set themselves apart from their competitors. Contact centers can use data analytics and AI technologies to give customers personalized help, which makes customers happier and more loyal.
Outsourcing of contact center operations: Businesses can give their contact center operations to third-party service providers so they can focus on their core business operations. Outsourcing can also save money, give access to specialized knowledge, and allow operations to grow or shrink as needed.
Key Segments Covered:
Top Market Players:
Altair Engineering, Inc., Fair Isaac Corporation (FICO), International Business Machines Corporation, KNIME, Microsoft Corporation, Oracle Corporation, RapidMiner, Inc., SAP SE, SAS Institute Inc., Trianz, and others.
By Type
- Big Data Analytics
- Business Analytics
- Customer Analytics
- Risk Analytics
- Statistical Analysis
- Others (Predictive Analytics, Text Analytics, and Prescriptive Analytics)
By Deployment
- On-premise
- Cloud
By Enterprise Size
- Large Enterprises
- Small & Medium Enterprises (SMEs)
By End-use
- BFSI
- Government
- Healthcare
- IT & Telecom
- Military & Defense
- Others
Regions and Countries Covered
- North America: (US, Canada, Mexico, Rest of North America)
- Europe: (Germany, France, Italy, Spain, UK, Nordic Countries, Benelux Union, Rest of Europe)
- Asia-Pacific: (Japan, China, India, Australia, South Korea, Southeast Asia, Rest of Asia-Pacific)
- The Middle East & Africa: (Saudi Arabia, UAE, Egypt, South Africa, Rest of the Middle East & Africa)
- Latin America: (Brazil, Argentina, Rest of Latin America)
- Rest Of the World
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