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The global big data technology market is expected to grow at a CAGR of 17.1% during the period 2024-2032. The market is expected to be driven by organizations’ need to gather and analyse huge amounts of data to gain insights and make intelligent decisions. North America, Europe and Asia are expected to be key markets.
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Big data describes the vast collection of data that is great in size and exponentially increasing with time. It denotes the massive amount of data difficult to stock, investigate, and transform with conventional tools of management. Big data technologies refer to the utilized software that incorporates data mining, data storage, data sharing, and data visualization; the inclusive term embraces data, data framework including tools and techniques used to examine and transform data. In greater terms of range in technology, it is widely linked with other technologies such as Machine Learning, Deep Learning, Artificial Intelligence, and IoT that are amplified on a larger scale. Big data technologies can be split into two categories – operational and analytical.
Operational big data technologies indicate the generated quantity of data on a daily basis through online transactions, social media, or any kind of data from a particular firm used for analysis through big data technologies-based software; it acts as raw data to feed analytical big data technologies. Some examples outlining operational big data technologies include executives’ details in an MNC, online trading and purchasing from platforms like Amazon, Flipkart, Walmart, etc, online ticket booking for flights, movies, railways, etc.
Analytical big data technologies refer to advanced adaptation of big data technologies; these are relatively complex than operational big data. These involve the investigation of the massive amounts of data crucial for business decisions. Examples include stock marketing, weather forecasting, time series analysis, medical-health records, etc.
The global big data technology market is likely to be driven by leading big data technologies including Apache Hadoop, Apache Spark, MongoDB, Apache Cassandra, Apache Kafka, QlikView, Qlik Sense, Tableau, Apache Storm, Apache Hive, Apache Pig, Presto, Apache Flink, Apache Sqoop, Rapidminer, KNIME (Konstanz Information Miner), and Elasticsearch.
Big data technologies are widely used in product development, predictive maintenance, to enhance customer experience and operational efficiency, fraud and compliance, machine learning, and to drive innovation.
Companies such as Netflix and Procter & Gamble employ big data to predict customer demand. The companies construct predictive models for novel products and services by categorizing main characteristics of past and current products or services and modelling the association between those features and the commercial success of the offerings. P&G also utilizes data and analytics from focus groups, social media, test markets, and early store rollouts to plan, produce, and launch new products. Such applications are expected to drive the global big data technology market. Factors capable of predicting mechanical failures may be rooted in structured as well as unstructured data. By analysing such data for indications of possible issues before problems occur, organizations can deploy maintenance more efficiently and maximize parts and equipment uptime.
Big data enables a clearer view of customer experience through collection of information from social media, web visits, call logs, and other sources; such information helps enhance interaction experience and maximize value delivered, and enables companies to deliver tailored offers, decrease customer churn, and manage issues proactively. Big data helps identify patterns in data that signify fraud and aggregate large volumes of information to quicken regulatory reporting.
Big data helps analyse and evaluate production, customer feedback and returns, and other aspects to decrease outages and predict future demands. Big data may also be used to enhance decision-making in line with current market demand.
The global big data technology market is expected to be driven by big data technologies that can drive innovation by enabling the study of interdependencies among humans, institutions, entities, and process, and identification of new ways to use those understandings.
Organizations are increasingly leveraging big data to extract value and insights from data. With the exponential increase of data, distributed storage and compute solutions such as Hadoop offer the framework for storing, processing, and analysing big data.
Microsoft Azure offers several options to run big data workloads in the cloud.
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By offering, the market is segmented into:
By deployment, the market is divided into:
By application, the market is classified into:
By organization size, the market is segmented into:
By end use, the market is divided into:
By region, the market is divided into:
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The report presents a detailed analysis of the following key players in the global big data technology market, looking into their capacity, and latest developments like capacity expansions, plant turnarounds, and mergers and acquisitions:
The EMR report gives an in-depth insight into the industry by providing a SWOT analysis as well as an analysis of Porter’s Five Forces model.
REPORT FEATURES | DETAILS |
Base Year | 2023 |
Historical Period | 2018-2023 |
Forecast Period | 2024-2032 |
Scope of the Report |
Historical and Forecast Trends, Industry Drivers and Constraints, Historical and Forecast Market Analysis by Segment:
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Breakup by Deployment |
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Breakup by End Use |
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Breakup by Region |
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Market Dynamics |
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Report Price and Purchase Option | Explore our purchase options that are best suited to your resources and industry needs. |
Delivery Format | Delivered as an attached PDF and Excel through email, with an option of receiving an editable PPT, according to the purchase option. |
*While we strive to always give you current and accurate information, the numbers depicted on the website are indicative and may differ from the actual numbers in the main report. At Expert Market Research, we aim to bring you the latest insights and trends in the market. Using our analyses and forecasts, stakeholders can understand the market dynamics, navigate challenges, and capitalize on opportunities to make data-driven strategic decisions.*
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The global big data technology market is projected to grow at a CAGR of 17.1% between 2024 and 2032.
The major drivers of the market include the increasing internet penetration across the world, growing adoption of cloud-based platforms, presence of several large-scale big data technology companies, and increasing smartphone penetration.
The increasing integration of AI and machine learning and organisations’ need to gather and analyse huge amounts of data are the key industry trends propelling the market's growth.
The major regions in the industry are North America, Latin America, the Middle East and Africa, Europe, and the Asia Pacific.
The various offerings provided by the market are solution and services. Solution is further broken down into big data analytics, data discovery, data visualisation, and data management, while services are divided into managed services and professional services.
Based on deployment, the market is divided into cloud, on-premises, and hybrid.
The technology finds wide applications in customer analytics, operational analytics, fraud detection and compliance, enterprise data warehouse optimisation, and data analytics.
On the basis of organisation size, the market is segmented into small and medium size enterprises and large enterprises.
The technology finds end-uses in BFSI, retail, manufacturing, IT and telecom, government, healthcare, utility, and education, among others.
The major players in the industry are IBM Corporation, Microsoft Corporation, Infosys Limited, Oracle Corporation, and Cloudera, Inc., among others.
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