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In simpler terms, imagine a world where factories and industries are getting smarter. This is happening with the help of something called IIoT and Industry 4.0. These technologies connect different parts of the industry, like sensors and machines, so they can talk to each other. This creates a smart system where equipment is easy to control, can be monitored from afar, and can even schedule its own maintenance. The big challenge for industries, though, is dealing with the huge amount of data all these connected systems generate. This is where Hadoop big data analytics comes in.
Hadoop is like a super smart system for handling big data. It can store massive amounts of data in different formats and can grow or shrink as needed. It organizes the data in a way that makes it easy to work with. So, when you have all this data coming from sensors, machines, and processes, Hadoop can analyze it. It helps make better decisions, like predicting when something might go wrong, scheduling maintenance when it's needed, and spotting problems in the system. This means less time when machines are not working, more productivity, and lower costs.
The reason why more and more industries are interested in using Hadoop big data analytics is that they want to improve how their operations work with IIoT. They see the potential of making their processes smarter and more efficient, and Hadoop is a key player in helping them make sense of all the data these smart systems generate.
To sum it up, industries are going through a big change, getting smarter with IIoT and Industry 4.0. Making machines and processes smarter means they can communicate better. But with all this communication comes a lot of data. That's where Hadoop big data analytics comes in handy. It's like a super-smart system that can handle and make sense of all this data. It helps industries predict problems, schedule maintenance, and keep everything running smoothly. So, the demand for making industries smarter with IIoT is also making Hadoop big data analytics more popular.
Covered Aspects:
| Report Attribute/Metric | Details |
|---|---|
| Segment Outlook | component, technology, organization size, development, End User and Region |
Big Data Market Highlights:
Big Data Market Overview
Big data Size was valued at USD 100.4 billion in 2021. The big data industry is projected to grow from USD 114.9 Billion in 2022 to USD 297.0 billion by 2030, exhibiting a compound annual growth rate (CAGR) of 14.5% during the forecast period (2024 - 2030). Increased internet penetration and increased government investments to upgrade digital technologies and expand access are the key market drivers enhancing the market growth.
Figure 1: Big Data Market Size, 2024-2030 (USD Billion)
Source: Secondary Research, Primary Research, MRFR Database and Analyst Review
Big data Trends
Increasing Database Adoption Across Industries to Support market growth
Data is significantly growing as a result of the expanding use of digital solutions globally in industries like banking, healthcare, BFSI, retail, agriculture, and telecommunications and media. For instance, the use of artificial intelligence in agriculture has a significant impact on pest control, precision farming, and risk management.
The amount of data produced by smart machines, soil sensors, and GPS-equipped tractors is enormous. Big data analytics is being used in agriculture to analyse enormous data sets, including advanced risk assessment, supply tracks, natural trends, ideal crops, and more.
Similar to how businesses are using bots to modernise and automate working processes. Additionally, virtual assistants like Apple's Siri, Google Assistants, and Amazon Alexa produce a tonne of data.
For instance, the number of digital voice assistants is predicted to reach 8.2 billion, according to a Statista report released in January 2021. social media usage has increased as a result of improvements in smartphone technology and network connectivity. Facebook, WhatsApp chats, YouTube videos, Instagram, Snapchat, and other platforms generate enormous amounts of data. Therefore, it is anticipated that the industrial revolution will result in enormous databases thanks to advanced technologies in the industries, growing smart application adoption, and emerging social media platforms. Therefore, it is predicted that growing databases across industries will drive the market for big data analytics.
Big Data Segment Insights
Big Data component Insights
The big data segmentation, based on component, includes hardware, software, service The software segment has the highest revenue share and is expected to grow at the highest AGR during the forecast period, owing to its diverse solution offerings such as credit risk management, business intelligence solutions, CRM analytics, compliance analytics, workforce analytics, and others. Organizations migrating to digital platforms are implementing business intelligence solutions, customer relationship management, and workforce analytics. These solutions provide businesses with real-time insights, foresight, and visualisation, as well as advanced decision-making capabilities.
Big Data Technology Insights
The big data segmentation, based on technology, includes Predictive Analytics, Machines Learning, Hadoop. During the projected period, the machine learning sector will dominate the market. This will be followed by a discussion of Hadoop.
Big Data Organization Size Insights
The big data market , The organization size is divided between SMEs and large companies. Over the forecast period, the SME sector will lead the market, followed by the large enterprise.
Figure 2: Big Data Market, by organization size, 2021 & 2030 (USD Billion)
Source: Secondary Research, Primary Research, MRFR Database and Analyst Review
Big Data Development Insights
Based on development, the big data industry has been segmented into on-premise and on-cloud. The on-cloud segment will command the largest share in the market over the forecast period for its functional efficiency and cost benefits.
Big Data End User Insights
The big data segmentation, based on end user,. This segment divided into four categories: BFSI, Manufacturing, IT, Government. The BFSI segment is expected to have the highest revenue share in the industry vertical due to its rapidly growing customer base. Implementing big data analytics is assisting the BFS industry in efficiently acquiring, developing, and retaining customers. For example, to serve more than 47 million customers in 30 countries, financial services provider BBVA implemented a social media analytic tool to gain product and brand image insights. Similarly, Singapore-based Citibank offers retailing discounts based on transaction patterns in order to retain customers.
Big Data Regional Insights
By Region, the study provides the market insights into North America, Europe, Asia-Pacific and Rest of the World. During the projection period, North America will lead the market. It is expected to grow CAGR. Rapid adoption of advanced information technologies, increased focus on this technology application in Canada and the United States, the presence of some top market players, and increasing adoption of internet of things devices by various businesses are all contributing to the region's big data market growth.
Further, the major countries studiedin the market reportare: The U.S, Canada, Germany, France, UK, Italy, Spain, China, Japan, India, Australia, South Korea, and Brazil.
Figure 3: BIG DATA MARKET SHARE BY REGION 2021 (%)
Source: Secondary Research, Primary Research, MRFR Database and Analyst Review
Europe big data accounts for the second-largest market share because of the widespread use of cutting-edge communication, networking technologies, electronic devices, social media, connected devices, and more. The region's rapidly expanding data is likely to drive up demand for analytics tools. According to a report by the European Parliament, data analytics practises in Europe should increase industry productivity. Further, the Germany Big Data Market held the largest market share, and the UK big data was the fastest growing market in the European region
The Asia-Pacific big data is expected to grow at the fastest CAGR from 2022 to 2030. This is due to the growth of BFSI, retail, healthcare, the automotive industry, and other sectors. Additionally The market share of big data analytics is likely to increase as a result of the expanding social media ecosystem, widespread smartphone and internet use, improvements in communication technologies, and digitalization. Moreover, China big data held the largest market share, and the India big data was the fastest growing market in the Asia-Pacific region
Big Data Key Market Players & Competitive Insights
Major industry players are investing heavily in R&D to expand their product lines, allowing the big data market to expand even further. Key market developments include new product releases, contractual agreements, mergers and acquisitions, increased investments, and collaboration with other companies. To expand and thrive in a more competitive and rising market climate, competitors in the big data industry must offer cost-effective merchandise.
Manufacturing locally to minimize operational costs is one of the key business tactics used by manufacturers in the big data industry to benefit customers and develop the market sector. In recent years, the worldwide big data industry has offered some of the most significant advantages to medicine. Major big data players such as Hewlett Packard Enterprise Company, Tableau Software, SAP SE, Hitachi Ltd, Oracle Corporation, Dell Technologies, IBM Corporation and others.
Oracle Corporation is a multinational computer technology company based in Austin, Texas. Oracle was the world's third-largest software firm by sales and market capitalization in 2020. Database software and technology (particularly its own brands), cloud engineered systems, and enterprise software products such as enterprise resource planning (ERP) software, human capital management (HCM) software, customer relationship management (CRM) software (also known as customer experience), enterprise performance management (EPM) software, and supply chain management (SCM) software are all sold by the company. In December 2021, The digital information systems company Cerner, which supplies systems used in hospitals and health systems, was purchased by Oracle Corporation. To process and store the patient's data, Cerner employs big data analytics. Additionally, this acquisition will make it possible for healthcare providers to provide communities and individual patients with better care.
Salesforce.com is a cloud-based software corporation situated in San Francisco, California. It offers CRM software and apps for sales, customer support, marketing automation, analytics, and application development. In February 2021, Salesforce purchased Acumen Solutions, a provider of industry solutions based in the United States, in order to boost sales, customer engagement, and employee productivity. The company hopes to accelerate and deliver innovations through its Customer 360 Platform through this acquisition.
Key Companies in the big data includes
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Fair Isaac Corporation
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Accenture PLC
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Cloudera Inc.
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Teradata Corporation
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Microsoft Corporation
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Splunk Inc.
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Amazon Web Services
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Cisco Systems Inc.
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Hewlett Packard Enterprise Company
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Tableau Software
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SAP SE
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Hitachi Ltd.
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Dell Technologies
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Big Data Industry Developments
In December 2021, The Azure Data Lake Storage soft delete for blobs feature was introduced by Microsoft. This function prevented accidental deletion of files and folders by temporarily storing lost data in the system. Throughout the retention period, users could go back and restore a softly deleted object, like a file or directory, to its prior state. After the retention period has expired, the item would be permanently deleted.
In December 2021, Snowflake will be supported as a data source in Azure Purview, enabling users to use automated data discovery to build a detailed map of the data environment. Users could quickly import information from Snowflake databases through a quick scan into the Azure Purview data map, then manage and control the Snowflake data in Azure.
In January 2022, With a fresh new look, more space, and typefaces appropriate for dense data, Oracle's new redwood design experience will help users identify, display, and act on crucial insights when it updates Oracle Analytics Cloud
Big Data Market Segmentation
big data component Outlook
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Hardware
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Software
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Service
big data technology Outlook
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Predictive Analytics
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Machines Learning
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Hadoop
big data organization size Outlook
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Large Enterprise
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SMEs
big data development Outlook
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On-Premise
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Cloud
big data End User Outlook
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BFSI
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Manufacturing
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IT
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Government
big data Regional Outlook
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North America
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US
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Canada
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Europe
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Germany
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France
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UK
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Italy
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Spain
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Rest of Europe
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Asia-Pacific
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China
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Japan
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India
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Australia
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South Korea
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Australia
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Rest of Asia-Pacific
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Rest of the World
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Middle East
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Africa
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Latin America
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