Big Data Analytics Market Size, Share & Trends Analysis Report By Component (Solution, Service), By Applications (Customer Analytics, Risk & Fraud Analytics, IoT, Others), By End User (BFSI, Healthcare & Life Science, IT & Telecommunication, Transportation & Supply Chain Management, Others), By Enterprise Type (Large Enterprise, SMEs) and By Region(North America, Europe, APAC, Middle East and Africa, LATAM) Forecasts, 2024-2032

Market Overview

The global big data analytics market size was valued at USD 289.48 billion in 2023 and USD 329.14 billion in 2024. It is projected to reach USD 919.31 billion by 2032, growing at a CAGR of 13.7% during the forecast period (2022–2032). Factors such as significant growth in data volume and improved data connectivity using cloud computing, significantly drives the demand for big data analytics market by 2032.

Big data is an enormous volume of unstructured, raw data from numerous sources that requires a lot of computing power to collect and analyze due to its size and veracity. At the same time, data analytics aims to provide operational business insights to address challenging business issues. This technology enables higher scales and new types of analytics to manage performance and control costs by supporting modern enterprise platform requirements for storing discrete and massive data. Additionally, the growing extensive data ecosystem is primarily used to support advanced analytics projects involving learning applications, predictive analysis, and data mining. As a result, it provides greater flexibility for data collection, processing, and analysis than traditional database systems like relational databases and data warehouses.

These data analytics tools and methods provide ways to examine and draw conclusions from data sets, aiding organizations in developing better business decision-making techniques. Big data analytics play a significant role in businesses because they enable them to manage, process, and streamline sizable datasets in real-time while enhancing their decision-making capacity. A key goal of big data and business analytics is to assist organizations in improving their marketing campaigns by better understanding their target audiences and customers. Various industries are also using big data and business analytics to analyze the enormous amounts of data produced by offline and online trading.

Market Dynamics

What are the driving factors for big data analytics?

Significant growth in data volume

Due to the growth of social media, the Internet of Things (IoT), and multimedia, which have generated an overwhelming flow of data in either structured or unstructured formats, the amount of data that organizations collect is constantly rising. Almost 90% of the world's data has been produced in the last two years. The growth rate of machine-based and human-generated data is generally ten times greater than traditional business data. For instance, the growth rate of machine data is exponential and 50 times faster. Big data is primarily consumer-driven and -oriented; most global data is produced by consumers who are "always on." The average person spends 4 to 6 hours daily generating and consuming data via various devices and (social) applications. Every time you click, swipe, or send a message, new information is added to a database somewhere in the world. Because everyone now carries a smartphone, enormous amounts of data are being created.

Improved data connectivity using cloud computing

Cloud computing has increased data connectivity, and top-level strategies now include digital transformation. Falling technology costs, the development of open-source big data software frameworks, data connectivity through hybrid and multi-cloud environments, and the incorporation of digital transformation into top-level strategies are all expected to impact the adoption of big data solutions and services. A significant amount of structured and unstructured data is eventually produced due to the rising volume of business data, quickening technological advancements, and dropping average selling prices of intelligent devices. More than 80% of businesses gather the information that is not stored in a typical relational database. It is instead buried in unstructured documents, posts on social media, machine logs, pictures, and other sources.

What are the challenges for big data analytics market?

Data security issues and strict data security laws

On big data platforms, users store their private information and business-related data. However, managing and storing the documents can present several potential liabilities and vulnerabilities. The security worries about data breaches, unforeseen emergencies, application vulnerabilities, and information loss are growing along with the product's rising popularity. Some industries may decline revenue due to information security and privacy concerns, including academia, research, federal government agencies, and financial services. This could seriously harm the companies' reputations and eventually undermine the confidence of those in charge of the operations. Criminal penalties and even legal liability may result from this, in turn. Sensitive data and information are frequently kept in databases and the cloud, giving cybercriminals access to crucial business data and the ability to engage in illegal activity.

What are the future opportunities for big data analytics?

An increase in technology adoption and big data analytics

The extensive data technology landscape is changing due to the increasing adoption of technologies like AI, ML, IoT, blockchain, and data analytics. By integrating such technologies visualization, organizations can improve their visualization capabilities and make complex data more usable and accessible through visual representation. ML tools use business intelligence tools to analyze both structured and unstructured data. End users can analyze the data and derive insights about the prize, sales, and quantity to reach the target customers using ML and data analytics combined with big data technology. End users can use this to predict future conditions and effectively manage the supply chain and transportation systems. Enterprises can enhance network security, accelerate digital businesses, and give customers a better experience thanks to the Al solution's real-time insights. Al's integration with big data platforms enhances customer experience, decision-making speed, and business operations. The market's major players are concentrating on concluding joint ventures to introduce cutting-edge solutions built on fundamental technologies like Al and others.

Regional Analysis

North america dominates the global market.

The global big data analytics market share is bifurcated into four regions: North America, Europe, Asia-Pacific, and LAMEA.

North America is the most significant shareholder in the global market and is expected to grow at a CAGR of 13.1% during the forecast period. North America's extensive data analytics market analysis includes the U.S. and Canada. This can be attributed to the increasing use of big data solutions by well-known IT firms like IBM, Google, Oracle, and Microsoft, among others. In addition, it is expanding R&D projects to boost productivity and modernize business processes to fuel market expansion. Furthermore, the market for big data analytics indicates a paradigm shift toward big data by creating integrated solutions that provide improved benefits derived from the enormous amounts of data generated from various sources. The local population's rapid uptake of wearables, intelligent connected devices, and smartphones and the presence of experienced technology providers and developers contribute to this trend.

Asia Pacific is expected to grow at the fastest CAGR of 14.4% during the forecast period. China, India, Japan, Australia, and the rest of Asia-Pacific are all included in the Asia-Pacific big data analytics market analysis. Big data analytics market growth is significantly impacted by factors like the region's rising social media access and mobile device penetration. Opportunities in the various market segments for big data analytics are expanding significantly due to rising technological advancements. The region's sharp rise in social media users will spur further market expansion. It is caused by the growing amount of data produced by rapid digitalization and the increased use of electronic devices and smart networks by businesses in the area.

Segmental Analysis

The global big data analytics market share is segmented by component, application, and end user.

Based on components, the global big data analytics market is bifurcated into solutions and services.

The solution segment is the highest contributor to the market and is expected to grow at a CAGR of 13.4% during the forecast period. It results from businesses' growing demand for cost-effective big data solutions. Organizations will benefit from an increased demand for data analytical solutions to manage and analyze large datasets in real time. Extensive data analysis methods that are improved at the corporate level to track real-time data, store, evaluate, and extract information for achieving the desired goal will help to improve the business models that maximize the income of solution providers.

Based on application, the global market for big data analytics is bifurcated into customer analytics, risk & fraud analytics, IoT, and others.

The customer analytics segment is the highest contributor to the market and is expected to grow at a CAGR of 13.82% during the forecast period. Rising trends in the study and examination of human behavior through social media and internet search engines also help to influence the market's development. Additionally, the telecommunications industry's growing demand for consumer analytics and risk & fraud analytics is fueling the market's expansion in the segment. The quick expansion of access to social media platforms like Twitter, Facebook, Instagram, and others is one of the major factors driving the growth of the big data analytics market.

Based on end users, the global market for big data analytics is bifurcated into BFSI, healthcare & life science, IT & telecommunication, transportation & supply chain management, and others.

The IT & telecommunication segment is the highest contributor to the market and is expected to grow at a CAGR of 13.56% during the forecast period. The demand for the retail sector in the market is driven by businesses' engagement with customers through various social media platforms, linking their products to e-commerce websites, and learning about customer behavior. The big data analytics market in this sector is driven by SMEs and online retailers' increased use of analytical tools for predictive analysis, which helps businesses segment their products and services. Additionally, the market will grow favorably due to rising demand in the transportation and SCM sectors, which integrate social media platforms and internet traffic to produce various end products.

Based on Enterprise Type, the global market for big data analytics is bifurcated into Large Enterprise and SMEs.
Based on the studies the solutions are consumed by large enterprises and small & medium enterprises. Large enterprises will continue to dominate the market during the forecast period as some of the large enterprises have initially adopted the solutions. Moreover, small & medium enterprises are expected to exhibit a higher growth rate during the forecast period due to the rising number of SMEs from developing regions such as Middle East & Africa, South America, and Asia Pacific.

Recent Developments

• September 2022, according to a study by Genpact, a global professional services company focused on delivering digital transformation, businesses miss a significant opportunity for substantial progress toward increasing diversity, equity, and inclusion (DEI) if they fail to use data-led analytics that produces deep insights into their organizational cultures.

• May 2022, Salesforce introduced Tableau Cloud as the quickest and simplest way for customers to access the full potential of Tableau at an enterprise level. The service, the next iteration of what was formerly known as Tableau Online, offers innovations to increase productivity by providing intuitive, potent, and easy-to-use analytical tools that anyone can use to find insights and make decisions supported by data.