Hadoop Big Data Analytics Market Scope
The Hadoop Big Data Analytics Market growth can possibly achieve a striking CAGR of 27.41% between 2022 and 2032 confirms Market Research Future (MRFR). The market can stand at a valuation of over USD 80.60 billion by 2032-end, reveals MRFR.
Primary Drivers and Main Barriers
MRFR anticipates a brisk growth of the hadoop big data analytics market in the near future, thanks to the tsunami of data being generated across various industry verticals, which is only expected to surge further in the coming years. Big data analytics are projected to be used by leading market contenders to facilitate growth, productivity as well as innovation. Careful operational scrutiny by these players to precisely track everyday operations has boosted big data. These efforts are some of the most effective strategies that are used by companies to achieve a better position in the global market. Data experts view this as a significant trend that can lead considerable expansion of the Hadoop big data analytics market in the following years.
The investments being made by market participants in next generation solutions has increased tremendously over the years, which are also anticipated to induce industry growth. Companies are increasingly churning out highly advanced integrated solutions with superior features to expand their customer base in the market. End-users are doing everything in their capacity to bring down the hardware costs, which not only strengthens their market position but also boosts the demand for Hadoop big data analytics.
The emerging trend of visualization-backed data discovery tools is being continuously explored by organizations to reap more benefits from Big Data. This trend is also picking up speed in the market on the back of increasing availability of mobile devices. Organizations largely dependent on centralized development of reports usually conducted by highly skilled experts are now opting for the quicker and more cost-effective business intelligence model that leverages the dynamic combination of mobile workforce and Big Data.
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Significant Competitors
Significant competitors in the Hadoop big data analytics industry are MapR Technologies (U.S.), Tableau Software, Inc. (U.S.), Karmasphere, Inc. (U.S.), Microsoft Corporation (U.S.), Cloudera, Inc. (U.S.), Teradata Corporation (U.S.), Pentaho Corporation (U.S.), Datameer, Inc. (U.S.), IBM Corporation (U.S.), Amazon Web Services (U.S.), to list a few.
Some current trends and predictions in the Hadoop Big Data Analytics market include:
Cloud-based solutions: The shift towards cloud-based big data analytics solutions is expected to continue, with many organizations opting for cloud deployment models due to their flexibility and scalability.
Emergence of AI and machine learning capabilities: Hadoop Big Data Analytics is expected to increasingly incorporate Artificial Intelligence (AI) and Machine Learning (ML) capabilities to help analysts extract insights and make data-driven decisions.
Focus on real-time analytics: Currently, the focus is shifting towards real-time analytics, with the capability to process data in real-time to provide insights to businesses.
Increase in the use of streaming technologies such as Spark streaming and Flink.
Increasing demand for data privacy and security in the wake of rising cyber threats.
Continuous innovation in data processing techniques to extract insights from complex data sets.
Growth in demand for data visualization and self-service analytics.
Overall, Hadoop Big Data Analytics is a rapidly evolving field , and it will be interesting to see how these trends continue to shape the market in the coming years.
Market Segmentation
Component, application and end-user are the primary segments depending on which the study of the market has been carried out in the MRFR report.
Component-dependent market segmentation comprises Software as well as Services (which include Managed Services, Training Support and Consulting Development,). In the year 2017, the largest share of 71.05% was claimed by the software segment, which is presumed to advance at a pace of 35.69% in the ensuing period.
Applications of Hadoop big data analytics are Internet of Things (IoT), Risk Fraud Analytics, Security Intelligence, Merchandising Supply Chain Analytics, Customer Analytics, Merchandising Coordination Service, Distributed Coordination Service, and others. In 2017, risk fraud analytics emerged as the leading segment with a share of 27.75% at a value of USD 2.40 Billion. In addition, the segmental progression has been estimated to be at a rate of 37.30%, because of the rising focus on risk and fraud analysis in businesses across the world.
The primary end-users in the market are Healthcare, Transportation Logistics, Government Defense, IT Telecommunication, BFSI, Manufacturing, and Others. In 2017, BFSI was ahead of other end-users in the market with the biggest share. The segment also exhibits the potential to procure a growth rate of 35.25% during the conjectured period.
Regional Study
The regional study of the market for Hadoop big data analytics comprises North America, Europe Asia Pacific or APAC and the Rest of the World or RoW.
In 2017, studies revealed North America as the most profitable market with a share of 54.44% at a value of USD 4.71 billion. The North American market is all set to gain high traction globally, at a rate of 34.90% over the forthcoming period. Countries like the United States (U.S.) along with Canada, is quite advanced, with respect to technology. This means faster adoption of state of the art technologies and a massive foothold of Big Data analytics providers. The rapid expansion of business insights in the region also warrants substantial market growth.
Developing countries like India and China in the APAC market are growing rapidly on account of the surge in industrialization as well as urbanization. The government-backed initiatives like smart city concept are emerging quite swiftly in the region, because of which the Hadoop big data analytics market is presumed to perform incredibly in the next few years.
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