Executive Summary
The global big data market size is expected to grow from USD 150.21 billion in 2021 to USD 261.43 billion by 2027 at a CAGR of 9.7%.
Impact of COVID-19 on Global Big Data Market
The COVID-19 crisis has brought years of change in the way companies in all sectors and regions to conduct business. Companies have accelerated the digitalization of their customer interaction with the supply chain and their internal operations by three to four years. And the share of digital or digital-enabled products in their portfolios has grown by an alarming seven years. funding for digital programs has grown more than anything else. Technology has become an important strategic and important part of the business, not just a source of cost-effectiveness. During the epidemic, consumers have flocked to online channels, and companies and industries have also responded.
Driver: Introduction of open source big data software frameworks
Open source big data analysis refers to the use of open-source software and large data analytics tools to gather important and hosted information that an organization can use to further its business objectives. A major player in analyzing open source big data is Apache's Hadoop. It is a software library that is widely used to process large data sets in a computer database using a distributed compliance process. Hadoop is an open-source application of the MapReduce algorithm developed by Google and Yahoo, so it is the basis of many analytics programs today. Many large data analytics tools use open source, including robust data systems such as open MongoDB, a complex and scalable NoSQL website suitable for large data applications, and more.
Restraint: Lack of skilled workforce
Lack of skills is a constant headache for CIOs everywhere, especially if you want to develop high-quality big data, statistics, and AI programs. This has a profound effect on all organizations, as two-thirds of IT leaders say they are preventing them from keeping pace with the pace of change. Companies such as Amazon Web Services (AWS), Google, Microsoft, IBM, and others build voice recognition applications, image classification, face recognition, and more that are available for cloud rental without a long-term commitment. One example is Google AutoML. Google systems automatically create a machine learning model from client-uploaded content. Instead of in-house teams spending a lot of time developing algorithms that require the best solution, this and similar services developed by other organizations can save time and reduce pressure on resources.
Opportunity: Incorporation of AI, IoT, and blockchain with big data
Overall, the need for big data extends to all sectors and businesses. Those who work to understand their customers' business and problems will be able to quickly identify large-scale data solutions that fit their needs and thus gain a more competitive advantage than their competitors. The demand for high-tech jobs is also increasing, especially in the technical, scientific, and technological fields; information Technology; production; finance and insurance; and retail. DevOps has no foundation outside the cloud. IoT needs a cloud to work properly because computer programming requires a well-functioning cloud. AI remained a model until big data came along. Blockchain and distributed ledger technology are disrupting the technology sector.
Challenge: Privacy and data security concerns
Businesses use big data analysis to identify business opportunities, improve performance, and promote decision-making. Many big data tools are open source and not designed for mental security. Significant increases in data usage lead to many data security problems. The consequences of information theft can be even worse if organizations keep sensitive or confidential information such as credit card numbers or customer information. They may face fines for failing to meet basic data security measures to comply with data loss protection and privacy guidelines such as the General Data Protection Regulation (GDPR).
Among solutions, the big data analytics segment to grow with the highest CAGR during the forecast period
Big data analysis is often a complex process of analyzing big data to reveal information, such as hidden patterns, relationships, market trends, and customer preferences that can help organizations make informed business decisions. To a large extent, technology and data analysis techniques provide organizations with a way to analyze data sets and gather new information. Business intelligence (BI) answers basic questions about business performance and performance. Big data analysis is an advanced form of analysis, which includes complex applications with features such as speculative models, mathematical algorithms, and analytics that, if enabled, are analytical systems.
By deployment mode, Cloud segment to grow with higher CAGR than on-premises during the forecast period
While there are benefits to big data, the sheer number of computer services and software services needed to support large-scale data efforts may put pressure on finance and business intelligence even for large businesses. The cloud has made great strides in meeting the demand for big data. It can provide virtually unlimited computer services and services that make big data efforts possible in any business. Big data and cloud computing are two very different ideas, but these two concepts are so closely intertwined.
North America to account for the largest share during the forecast period
Increased adoption of large data analytics software by many organizations, increased demand for large cloud-based data analysis software among SMEs, and the many benefits offered by big data and business statistics solutions drive the growth of North America’s big data market. On the other hand, higher operating costs and a shortage of skilled workers hamper growth. However, emerging trends such as social media analysis are expected to create profitable opportunities in the industry. The tendency to work from home has led to many data analysis opportunities, thus having a positive impact on the North American big data market. This trend is likely to continue even after the epidemic, as organizations have begun implementing business statistics solutions to improve data security and simplify business productivity in a better way.
Key Players
The major players operating in the global big data market are IBM (US), Teradata (US), Microsoft (US), Oracle (US), SAS Institute (US), Google (US), SAP (Germany), Adobe (US), Talend (US), Informatica (US), Qlik (US), TIBCO Software (US), Salesforce (US), Alteryx (US), Sisense (US), Cloudera (US), Palantir Technologies (US), 1010data (US), Hitachi Vantara (US), Fusionex (Malaysia), Splunk (US), Information Builders (US), AWS (US), Micro Focus (UK), HPE (US), MicroStrategy (US), Yellowfin (Australia), and ThoughtSpot (US).
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