The global big data and business analytics (BDA) market was valued at ***** billion U.S. dollars in 2018 and is forecast to grow to ***** billion U.S. dollars by 2021. In 2021, more than half of BDA spending will go towards services. IT services is projected to make up around ** billion U.S. dollars, and business services will account for the remainder. Big data High volume, high velocity and high variety: one or more of these characteristics is used to define big data, the kind of data sets that are too large or too complex for traditional data processing applications. Fast-growing mobile data traffic, cloud computing traffic, as well as the rapid development of technologies such as artificial intelligence (AI) and the Internet of Things (IoT) all contribute to the increasing volume and complexity of data sets. For example, connected IoT devices are projected to generate **** ZBs of data in 2025. Business analytics Advanced analytics tools, such as predictive analytics and data mining, help to extract value from the data and generate business insights. The size of the business intelligence and analytics software application market is forecast to reach around **** billion U.S. dollars in 2022. Growth in this market is driven by a focus on digital transformation, a demand for data visualization dashboards, and an increased adoption of cloud.
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The Data Analytics in Retail Industry is segmented by Application (Merchandising and Supply Chain Analytics, Social Media Analytics, Customer Analytics, Operational Intelligence, Other Applications), by Business Type (Small and Medium Enterprises, Large-scale Organizations), and Geography. The market size and forecasts are provided in terms of value (USD billion) for all the above segments.
This statistic shows the importance of big data analysis and machine learning technologies worldwide as of 2019. Tensorflow was seen as the most important big data analytics and machine learning technology, with ** percent of respondents stating that it was important to critial for their organization.
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In 2023, the global Big Data and Business Analytics market size is estimated to be valued at approximately $274 billion, and with a projected compound annual growth rate (CAGR) of 12.4%, it is anticipated to reach around $693 billion by 2032. This significant growth is driven by the escalating demand for data-driven decision-making processes across various industries, which leverage insights derived from vast data sets to enhance business efficiency, optimize operations, and drive innovation. The increasing adoption of Internet of Things (IoT) devices, coupled with the exponential growth of data generated daily, further propels the need for advanced analytics solutions to harness and interpret this information effectively.
A critical growth factor in the Big Data and Business Analytics market is the increasing reliance on data to gain a competitive edge. Organizations are now more than ever looking to uncover hidden patterns, correlations, and insights from the data they collect to make informed decisions. This trend is especially prominent in industries such as retail, where understanding consumer behavior can lead to personalized marketing strategies, and in healthcare, where data analytics can improve patient outcomes through precision medicine. Moreover, the integration of big data analytics with artificial intelligence and machine learning technologies is enabling more accurate predictions and real-time decision-making, further enhancing the value proposition of these analytics solutions.
Another key driver of market growth is the continuous technological advancements and innovations in data analytics tools and platforms. Companies are increasingly investing in advanced analytics capabilities, such as predictive analytics, prescriptive analytics, and real-time analytics, to gain deeper insights into their operations and market environments. The development of user-friendly and self-service analytics tools is also democratizing data access within organizations, empowering employees at all levels to leverage data in their daily decision-making processes. This democratization of data analytics is reducing the reliance on specialized data scientists, thereby accelerating the adoption of big data analytics across various business functions.
The increasing emphasis on regulatory compliance and data privacy is also driving growth in the Big Data and Business Analytics market. Strict regulations, such as the General Data Protection Regulation (GDPR) in Europe and the California Consumer Privacy Act (CCPA) in the United States, require organizations to manage and analyze data responsibly. This is prompting businesses to invest in robust analytics solutions that not only help them comply with these regulations but also ensure data integrity and security. Additionally, as data breaches and cybersecurity threats continue to rise, organizations are turning to analytics solutions to identify potential vulnerabilities and mitigate risks effectively.
Regionally, North America remains a dominant player in the Big Data and Business Analytics market, benefiting from the presence of major technology companies and a high rate of digital adoption. The Asia Pacific region, however, is emerging as a significant growth area, driven by rapid industrialization, urbanization, and increasing investments in digital transformation initiatives. Europe also showcases a robust market, fueled by stringent data protection regulations and a strong focus on innovation. Meanwhile, the markets in Latin America and the Middle East & Africa are gradually gaining momentum as organizations in these regions are increasingly recognizing the value of data analytics in enhancing business outcomes and driving economic growth.
The Big Data and Business Analytics market is segmented by components into software, services, and hardware, each playing a crucial role in the ecosystem. Software components, which include data management and analytics tools, are at the forefront, offering solutions that facilitate the collection, analysis, and visualization of large data sets. The software segment is driven by a demand for scalable solutions that can handle the increasing volume, velocity, and variety of data. As organizations strive to become more data-centric, there is a growing need for advanced analytics software that can provide actionable insights from complex data sets, leading to enhanced decision-making capabilities.
In the services segment, businesses are increasingly seeking consultation, implementation, and support services to effective
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The Hadoop Big Data Analytics Market report segments the industry into Solution (Data Discovery and Visualization (DDV), Advanced Analytics (AA)), End User (BFSI, Retail, IT and Telecom, Healthcare and Life Sciences, Manufacturing, Media and Entertainment, Other End Users), and Geography (North America, Europe, Asia-Pacific, Latin America, Middle-East and Africa).
The statistic shows the problems that organizations face when using big data technologies worldwide as of 2017. Around ** percent of respondents stated that inadequate analytical know-how was a major problem that their organization faced when using big data technologies as of 2017.
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The Supply Chain Big Data Analytics Market Report is Segmented by Component (Solution, Service), End User Industry (Retail, Transportation and Logistics, Manufacturing, Healthcare, Other End-User Industries), Deployment Model (On-Premise, Cloud), and Geography. The Market Forecasts are Provided in Terms of Value (USD).
This statistic shows the results of a survey on data-driven projects, either planned or implemented, among technology magazine readers. In 2015, ** percent of respondents indicated that their companies had already deployed or implemented a data-driven project. Fewer than a third of respondents said their companies had no plans to deploy or implement a data-driven project.
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The global market size for Big Data Analysis Platforms is projected to grow from USD 35.5 billion in 2023 to an impressive USD 110.7 billion by 2032, reflecting a CAGR of 13.5%. This substantial growth can be attributed to the increasing adoption of data-driven decision-making processes across various industries, the rapid proliferation of IoT devices, and the ever-growing volumes of data generated globally.
One of the primary growth factors for the Big Data Analysis Platform market is the escalating need for businesses to derive actionable insights from complex and voluminous datasets. With the advent of technologies such as artificial intelligence and machine learning, organizations are increasingly leveraging big data analytics to enhance their operational efficiency, customer experience, and competitiveness. The ability to process vast amounts of data quickly and accurately is proving to be a game-changer, enabling businesses to make more informed decisions, predict market trends, and optimize their supply chains.
Another significant driver is the rise of digital transformation initiatives across various sectors. Companies are increasingly adopting digital technologies to improve their business processes and meet changing customer expectations. Big Data Analysis Platforms are central to these initiatives, providing the necessary tools to analyze and interpret data from diverse sources, including social media, customer transactions, and sensor data. This trend is particularly pronounced in sectors such as retail, healthcare, and BFSI (banking, financial services, and insurance), where data analytics is crucial for personalizing customer experiences, managing risks, and improving operational efficiencies.
Moreover, the growing adoption of cloud computing is significantly influencing the market. Cloud-based Big Data Analysis Platforms offer several advantages over traditional on-premises solutions, including scalability, flexibility, and cost-effectiveness. Businesses of all sizes are increasingly turning to cloud-based analytics solutions to handle their data processing needs. The ability to scale up or down based on demand, coupled with reduced infrastructure costs, makes cloud-based solutions particularly appealing to small and medium-sized enterprises (SMEs) that may not have the resources to invest in extensive on-premises infrastructure.
Data Science and Machine-Learning Platforms play a pivotal role in the evolution of Big Data Analysis Platforms. These platforms provide the necessary tools and frameworks for processing and analyzing vast datasets, enabling organizations to uncover hidden patterns and insights. By integrating data science techniques with machine learning algorithms, businesses can automate the analysis process, leading to more accurate predictions and efficient decision-making. This integration is particularly beneficial in sectors such as finance and healthcare, where the ability to quickly analyze complex data can lead to significant competitive advantages. As the demand for data-driven insights continues to grow, the role of data science and machine-learning platforms in enhancing big data analytics capabilities is becoming increasingly critical.
From a regional perspective, North America currently holds the largest market share, driven by the presence of major technology companies, high adoption rates of advanced technologies, and substantial investments in data analytics infrastructure. Europe and the Asia Pacific regions are also experiencing significant growth, fueled by increasing digitalization efforts and the rising importance of data analytics in business strategy. The Asia Pacific region, in particular, is expected to witness the highest CAGR during the forecast period, propelled by rapid economic growth, a burgeoning middle class, and increasing internet and smartphone penetration.
The Big Data Analysis Platform market can be broadly categorized into three components: Software, Hardware, and Services. The software segment includes analytics software, data management software, and visualization tools, which are crucial for analyzing and interpreting large datasets. This segment is expected to dominate the market due to the continuous advancements in analytics software and the increasing need for sophisticated data analysis tools. Analytics software enables organizations to process and analyze data from multiple sources,
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The global business big data market is experiencing robust growth, driven by the increasing adoption of cloud-based solutions, the proliferation of connected devices generating massive amounts of data, and the growing need for data-driven decision-making across various industries. The market's expansion is fueled by a surge in demand for advanced analytics, predictive modeling, and real-time data processing capabilities to optimize business operations, enhance customer experiences, and gain a competitive edge. While the exact market size for 2025 is unavailable, considering a plausible CAGR of 15% (a common growth rate for rapidly expanding technology sectors) and a starting point estimated at $150 billion in 2024, the market size in 2025 could reasonably be estimated around $172.5 billion. This growth is anticipated to continue into the forecast period (2025-2033), driven by factors such as increasing digital transformation initiatives across enterprises, the rise of artificial intelligence (AI) and machine learning (ML) applications, and the growing need for regulatory compliance involving data management and analysis. The market is segmented by application (individual users and enterprise users) and type (cloud-based and local-based). The enterprise user segment is currently dominating, owing to the higher data volumes and analytical needs of large organizations. Cloud-based solutions are experiencing faster growth due to their scalability, cost-effectiveness, and accessibility. Geographic distribution shows strong growth across North America and Asia Pacific, fueled by robust technological infrastructure and high levels of digital adoption in regions like the United States and China. However, growth is also expected in emerging economies driven by increasing internet and smartphone penetration and the adoption of big data technologies by a wider range of businesses. While challenges like data security concerns and the need for skilled professionals to manage and analyze big data present restraints, the overall market outlook remains strongly positive due to the transformative potential of big data analytics across various sectors.
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Big Data Analytics in Healthcare Market by Component (Software, Hardware, Services [Descriptive, Prescriptive, Diagnostic]), Deployment (On-premise, Cloud), Application (Clinical, Financial, Operational, Population Health), and End User - Global Forecast to 2032
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The Big Data Analytics in Banking Market is Segmented by Type of Solutions (Data Discovery and Visualization (DDV) and Advanced Analytics (AA)), and Geography (North America, Europe, Asia-Pacific, Latin America, Middle East and Africa). The Market Sizes and Forecasts are Provided in Terms of Value (USD Million) for all the Above Segments.
Pinterest Analytics led the global marketing analytics software industry in 2024 with a market share of over 50 percent, followed by Barometric with a market share of around 8 percent. Marketing analytics software allows businesses to evaluate the success of their various marketing initiatives.
As per our latest research, the global Big Data Analytics in BFSI market size reached USD 22.7 billion in 2024, driven by the increasing digital transformation initiatives and the accelerating adoption of advanced analytics across financial institutions. The market is expected to grow at a robust CAGR of 14.8% during the forecast period, reaching an estimated USD 62.5 billion by 2033. The rapid proliferation of digital banking, heightened focus on fraud detection, and the need for personalized customer experiences are among the primary growth drivers for the Big Data Analytics in BFSI market.
The exponential growth of data generated by financial transactions, customer interactions, and regulatory requirements has created an urgent need for advanced analytics solutions in the BFSI sector. Financial institutions are leveraging Big Data Analytics to gain actionable insights, optimize operations, and enhance decision-making processes. The integration of artificial intelligence and machine learning with Big Data Analytics platforms is enabling BFSI organizations to automate risk assessment, predict customer behavior, and streamline compliance procedures. Furthermore, the surge in digital payment platforms and online banking services has resulted in an unprecedented volume of structured and unstructured data, further necessitating robust analytics solutions to ensure data-driven strategies and operational efficiency.
Another significant growth factor is the increasing threat of cyberattacks and financial fraud. As digital channels become more prevalent, BFSI organizations face sophisticated threats that require advanced analytics for real-time detection and mitigation. Big Data Analytics empowers financial institutions to monitor vast datasets, identify unusual patterns, and respond proactively to potential security breaches. Additionally, regulatory bodies are imposing stringent data management and compliance standards, compelling BFSI firms to adopt analytics solutions that ensure transparency, auditability, and adherence to global regulations. This regulatory push, combined with the competitive need to offer innovative, customer-centric services, is fueling sustained investment in Big Data Analytics across the BFSI landscape.
The growing emphasis on customer-centricity is also propelling the adoption of Big Data Analytics in the BFSI sector. Financial institutions are increasingly utilizing analytics to understand customer preferences, segment markets, and personalize product offerings. This not only enhances customer satisfaction and loyalty but also drives cross-selling and upselling opportunities. The ability to analyze diverse data sources, including social media, transaction histories, and customer feedback, allows BFSI organizations to predict customer needs and deliver targeted solutions. As a result, Big Data Analytics is becoming an indispensable tool for BFSI enterprises aiming to differentiate themselves in an intensely competitive market.
From a regional perspective, North America remains the largest market for Big Data Analytics in BFSI, accounting for over 38% of global revenue in 2024. This dominance is attributed to the presence of major financial institutions, early adoption of advanced technologies, and a mature regulatory environment. However, the Asia Pacific region is witnessing the fastest growth, with a CAGR exceeding 17% during the forecast period, driven by rapid digitization, expanding banking infrastructure, and increasing investments in analytics solutions by emerging economies such as China and India.
The Big Data Analytics in BFSI market is segmented by component into Software and Services. The software segment comprises analytics platforms, data management tools, visualization software, and advanced AI-powered solutions. In 2024, the software segment accounted for the largest share
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Saudi Arabia Big Data Analytics Market was valued at USD 3.58 Billion in 2024 and is expected to reach USD 12.24 Billion by 2030 with a CAGR of 22.74%.
Pages | 70 |
Market Size | 2024: USD 3.58 Billion |
Forecast Market Size | 2030: USD 12.24 Billion |
CAGR | 2025-2030: 22.74% |
Fastest Growing Segment | BFSI |
Largest Market | Northern & Central Saudi Arabia |
Key Players | 1. Saudi Telecom Company 2. Zain Saudi Arabia 3. Elm Company 4. Mozn AI Solutions 5. T SAB IT & Technology Consulting 6. Oracle Corporation 7. Microsoft Corporation 8. SAP SE |
This statistic displays the economic benefits of Big Data analytics in the United Kingdom (UK) from 2015 to 2020, by industry. The report estimated that manufacturing would realize the largest benefits amounting to roughly ***** billion British pounds. Professional services were expected to gain benefits amounting to roughly **** billion British pounds.
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The Big Data Market is projected to grow at a CAGR of around 14.7% during 2023-28, says MarkNtel Advisors. (Top Companies - Accenture PLC, Cloudera Inc., Teradata Corporation, Microsoft Corporation, Splunk Inc., Amazon Web Services, and Cisco Systems Inc)
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Big Data Security Market Size 2025-2029
The big data security market size is forecast to increase by USD 23.9 billion, at a CAGR of 15.7% between 2024 and 2029. Stringent regulations regarding data protection will drive the big data security market.
Major Market Trends & Insights
North America dominated the market and accounted for a 37% growth during the forecast period.
By Deployment - On-premises segment was valued at USD 10.91 billion in 2023
By End-user - Large enterprises segment accounted for the largest market revenue share in 2023
Market Size & Forecast
Market Opportunities: USD 188.34 billion
Market Future Opportunities: USD USD 23.9 billion
CAGR : 15.7%
North America: Largest market in 2023
Market Summary
The market is a dynamic and ever-evolving landscape, with stringent regulations driving the demand for advanced data protection solutions. As businesses increasingly rely on big data to gain insights and drive growth, the focus on securing this valuable information has become a top priority. The core technologies and applications underpinning big data security include encryption, access control, and threat detection, among others. These solutions are essential as the volume and complexity of data continue to grow, posing significant challenges for organizations. The service types and product categories within the market include managed security services, software, and hardware. Major companies, such as IBM, Microsoft, and Cisco, dominate the market with their comprehensive offerings. However, the market is not without challenges, including the high investments required for implementing big data security solutions and the need for continuous updates to keep up with evolving threats. Looking ahead, the forecast timeline indicates steady growth for the market, with adoption rates expected to increase significantly. According to recent estimates, The market is projected to reach a market share of over 50% by 2025. As the market continues to unfold, related markets such as the Cloud Security and Cybersecurity markets will also experience similar trends.
What will be the Size of the Big Data Security Market during the forecast period?
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How is the Big Data Security Market Segmented and what are the key trends of market segmentation?
The big data security industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments. DeploymentOn-premisesCloud-basedEnd-userLarge enterprisesSMEsSolutionSoftwareServicesGeographyNorth AmericaUSCanadaEuropeFranceGermanyItalySpainUKAPACChinaIndiaJapanRest of World (ROW)
By Deployment Insights
The on-premises segment is estimated to witness significant growth during the forecast period.
The market trends encompass various advanced technologies and strategies that businesses employ to safeguard their valuable data. Threat intelligence platforms analyze potential risks and vulnerabilities, enabling proactive threat detection and response. Data encryption methods secure data at rest and in transit, ensuring confidentiality. Security automation tools streamline processes, reducing manual efforts and minimizing human error. Data masking techniques and tokenization processes protect sensitive information by obfuscating or replacing it with non-sensitive data. Vulnerability management tools identify and prioritize risks, enabling remediation. Federated learning security ensures data privacy in collaborative machine learning environments. Real-time threat detection and data breaches prevention employ anomaly detection algorithms and artificial intelligence security to identify and respond to threats. Access control mechanisms and security incident response systems manage and mitigate unauthorized access and data breaches. Security orchestration automation, machine learning security, and big data anonymization techniques enhance security capabilities. Risk assessment methodologies and differential privacy techniques maintain data privacy while enabling data usage. Homomorphic encryption schemes and blockchain security implementations provide advanced data security. Behavioral analytics security monitors user behavior and identifies anomalous activities. Compliance regulations and data privacy regulations mandate adherence to specific security standards. Zero trust architecture and network security monitoring ensure continuous security evaluation and response. Intrusion detection systems and data governance frameworks further strengthen security posture. According to recent studies, the market has experienced a significant 25.6% increase in adoption. Furthermore, industry experts anticipate a 31.8% expansion in the market's size ove
In 2023, around **** percent of companies that used big data analysis and related services in South Korea did so with public data. Following this was the analysis of customer information, at around **** percent.
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Big Data As A Service Market Size 2025-2029
The big data as a service market size is forecast to increase by USD 75.71 billion, at a CAGR of 20.5% between 2024 and 2029.
The Big Data as a Service (BDaaS) market is experiencing significant growth, driven by the increasing volume of data being generated daily. This trend is further fueled by the rising popularity of big data in emerging technologies, such as blockchain, which requires massive amounts of data for optimal functionality. However, this market is not without challenges. Data privacy and security risks pose a significant obstacle, as the handling of large volumes of data increases the potential for breaches and cyberattacks. Edge computing solutions and on-premise data centers facilitate real-time data processing and analysis, while alerting systems and data validation rules maintain data quality.
Companies must navigate these challenges to effectively capitalize on the opportunities presented by the BDaaS market. By implementing robust data security measures and adhering to data privacy regulations, organizations can mitigate risks and build trust with their customers, ensuring long-term success in this dynamic market.
What will be the Size of the Big Data As A Service Market during the forecast period?
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The market continues to evolve, offering a range of solutions that address various data management needs across industries. Hadoop ecosystem services play a crucial role in handling large volumes of data, while ETL process optimization ensures data quality metrics are met. Data transformation services and data pipeline automation streamline data workflows, enabling businesses to derive valuable insights from their data. Nosql database solutions and custom data solutions cater to unique data requirements, with Spark cluster management optimizing performance. Data security protocols, metadata management tools, and data encryption methods protect sensitive information. Cloud data storage, predictive modeling APIs, and real-time data ingestion facilitate agile data processing.
Data anonymization techniques and data governance frameworks ensure compliance with regulations. Machine learning algorithms, access control mechanisms, and data processing pipelines drive automation and efficiency. API integration services, scalable data infrastructure, and distributed computing platforms enable seamless data integration and processing. Data lineage tracking, high-velocity data streams, data visualization dashboards, and data lake formation provide actionable insights for informed decision-making.
For instance, a leading retailer leveraged data warehousing services and predictive modeling APIs to analyze customer buying patterns, resulting in a 15% increase in sales. This success story highlights the potential of big data solutions to drive business growth and innovation.
How is this Big Data As A Service Industry segmented?
The big data as a service industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.
Type
Data Analytics-as-a-service (DAaaS)
Hadoop-as-a-service (HaaS)
Data-as-a-service (DaaS)
Deployment
Public cloud
Hybrid cloud
Private cloud
End-user
Large enterprises
SMEs
Geography
North America
US
Canada
Mexico
Europe
France
Germany
Russia
UK
APAC
China
India
Japan
Rest of World (ROW)
By Type Insights
The Data analytics-as-a-service (DAaas) segment is estimated to witness significant growth during the forecast period. The data analytics-as-a-service (DAaaS) segment experiences significant growth within the market. Currently, over 30% of businesses adopt cloud-based data analytics solutions, reflecting the increasing demand for flexible, cost-effective alternatives to traditional on-premises infrastructure. Furthermore, industry experts anticipate that the DAaaS market will expand by approximately 25% in the upcoming years. This market segment offers organizations of all sizes the opportunity to access advanced analytical tools without the need for substantial capital investment and operational overhead. DAaaS solutions encompass the entire data analytics process, from data ingestion and preparation to advanced modeling and visualization, on a subscription or pay-per-use basis. Data integration tools, data cataloging systems, self-service data discovery, and data version control enhance data accessibility and usability.
The continuous evolution of this market is driven by the increasing volume, variety, and velocity of data, as well as the growing recognition of the business value that can be derived from data insights. Organizations across var
The global big data and business analytics (BDA) market was valued at ***** billion U.S. dollars in 2018 and is forecast to grow to ***** billion U.S. dollars by 2021. In 2021, more than half of BDA spending will go towards services. IT services is projected to make up around ** billion U.S. dollars, and business services will account for the remainder. Big data High volume, high velocity and high variety: one or more of these characteristics is used to define big data, the kind of data sets that are too large or too complex for traditional data processing applications. Fast-growing mobile data traffic, cloud computing traffic, as well as the rapid development of technologies such as artificial intelligence (AI) and the Internet of Things (IoT) all contribute to the increasing volume and complexity of data sets. For example, connected IoT devices are projected to generate **** ZBs of data in 2025. Business analytics Advanced analytics tools, such as predictive analytics and data mining, help to extract value from the data and generate business insights. The size of the business intelligence and analytics software application market is forecast to reach around **** billion U.S. dollars in 2022. Growth in this market is driven by a focus on digital transformation, a demand for data visualization dashboards, and an increased adoption of cloud.