The Big Data market size is projected to grow from USD 162.6 billion in 2021 to 273.4 USD billion in 2026, at a Compound Annual Growth Rate (CAGR) of 11.0% during the forecast period. The Big Data industry is driven by sharp increase in data volume. However, rise in data connectivity through cloud computing and incorporation of digital transformation in top-level strategies.
Based on the Component, solutions segment to account for a larger market size during the forecast period
The Big Data market has been segmented by two components: solutions and services. The deployment of Big Data has witnessed an increase in adoption, as serves a variety of purposes, such as fraud detection and risk management. The growing adoption of Big Data across all major verticals, such as BFSI, Government and Defense, Healthcare and Life Sciences, Manufacturing, Retail and Consumer Goods, Media and Entertainment, Telecommunications and IT, Transportation and Logistics, Other Verticals( (real estate, energy and utilities, travel and hospitality, and education and research).
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Based on deployment mode, cloud segment to grow at a higher CAGR during the forecast period
Cloud computing refers to the storage, management, and processing of data via networks of remote servers, which are typically accessed via the Internet. According to Statista, cloud computing would generate more than USD 300 billion in revenue in 2020 as a component of IT services. At the same time, PwC shows the COVID-19 crisis has accelerated the cloud transition even further as per data during the first quarter of 2020, cloud spending increased by 37% to USD 29 billion. The increasing generation of data leads to various challenges for several organizations. These challenges include storage, privacy, and affordability.
Unique Features in the Big Data Market
Volume (huge amounts of data), variety (diversity of data types and sources), and velocity (rapid data generation and processing) are the three Vs that define big data datasets. One unique quality is the ability to manage and analyse data at this scale and complexity.
To effectively handle enormous volumes of data, big data systems frequently make use of distributed and parallel processing frameworks. Computer clusters can do distributed computing thanks to tools like Apache Spark and Hadoop.
Large data sets are often diverse and unstructured, which could provide challenges for traditional relational databases. NoSQL databases are widely utilised in the Big Data ecosystem to manage a variety of data formats because of its scalability and flexibility architecture.
Data lakes are repositories that store raw, unstructured, and structured data at scale and are frequently used in big data applications. Large volumes of data can be stored in data lakes and processed and analysed later.
Given the sensitivity and regulatory requirements involved with huge datasets, Big Data systems must have effective data governance and security elements. This covers compliance checks, encryption, and access controls.
Major Highlights of the Big Data Market
The growing appreciation of data analytics’s usefulness across industries has propelled the Big Data market’s steady expansion. To obtain a competitive advantage and gather insights, organisations are investing in Big Data solutions.
A significant focus within the Big Data ecosystem has been on real-time analytics capabilities. For quicker decision-making, businesses are looking for solutions that let them analyse and act on data almost instantly.
Big Data workloads are increasingly being moved to the cloud. Organisations may access resources on-demand without significant upfront commitments thanks to the scalability, flexibility, and affordability of cloud-based Big Data solutions.
Big Data and edge computing integration is becoming more and more popular. By enabling data processing closer to the data source, edge analytics lowers latency and supports edge AI, autonomous systems, and Internet of Things applications.
Within the Big Data sector, there has been an increased emphasis on data security due to the growing volume and significance of data. To safeguard confidential data, solutions have developed to include strong security protocols, encryption, and compliance tools.
Top Key Companies in the Big Data Market
Major Big Data companies include IBM(US), Google(US), Oracle(US), Microsoft(US), SAS(US), SAP(Germany), Alteryx(US), TIBCO(US), Cloudera(US), Teradata(US), AWS(US), Informatica(US), Sisense(US), Salesforce(US), HPE(US), Qlik(US), Splunk(US), VMware(US), Accenture(Ireland), Ataccama(Canada), COGITO(US), Centerfield(US), RIB datapine(Berlin), Fusionex(Malaysia), BigPanda(US), Bigeye(US), Imply(US), Rivery(US), YugabyteDB (US), Airbyte(US), Cardagraph(US), Firebolt(US), Syncari(US).These market players have adopted various growth strategies, such as partnerships, collaborations, and new product launches, to expand have been the most adopted strategies by major players from 2018 to 2022, which helped companies innovate their offerings and broaden their customer base.
IBM is a multinational technology and consulting corporation offering infrastructure hosting and consulting services. The company operates through five major business segments: cloud and cognitive software, global business services, global technology services, systems, and global financing. IBM Cloud has emerged as a preferable platform for all business applications, as it is AI compatible. It is a unifying platform that integrates IBM’s capabilities with a single architecture and spans over public and private platforms. With this powerful cloud platform, the company can cater to the requirements of different businesses across the globe. IBM caters to various verticals, including aerospace & defense, education, healthcare, oil & gas, automotive, electronics, insurance, retail & consumer products, banking & finance, energy & utility, life science, telecommunication, media & entertainment, chemical, government, manufacturing, travel & transportation, construction, and metals & mining. The company has a strong presence in the Americas, Europe, the Middle East, Africa, and APAC and has clients in more than 175 countries. IBM is one of the major players in the big data market. In the past two years, it has shifted its focus from the hardware segment to the digital segment, with increased investments toward big data, AI, and ML.
In the big data market, IBM offers various solutions, including IBM BigIntegrate, IBM Db2 Big SQL, IBM Big Replicate, IBM BigQuality, IBM InfoSphere Data Replication, IBM Master Data Management, and Predictive Analytics. These solutions help businesses visualize, analyze, and share insights about their performance. The company offers managed and professional services in cloud environments.
Google is a global technology company. Its primary business areas include web-based search, desktop and mobile operating systems, display advertising and tools, enterprise solutions, hardware products, consumer content platform, advertising platform, and cloud computing platform. The company generates revenues by delivering relevant, cost-effective online advertising, cloud-based solutions that provide customers with platforms, collaboration tools and services, and sales of other products and services, such as apps and in-app purchases, digital content, and subscriptions for digital content, and hardware. Its search engine maintains a list of websites and online content for Google network members, advertisers, and content providers. The company’s core products include Android, Maps, Chrome, YouTube, Google Play, and Gmail.
Google also sells hardware products such as Chromebook, Chromecast, and Nexus. The company has a worldwide presence in more than 40 countries. The company offers solutions to various industries, including retail, financial services, healthcare & life sciences, media & entertainment, telecommunications, gaming, manufacturing, energy, government, education, and small businesses. It has a geographical presence in the US, APAC, EMEA, and other Americas. The solutions offered by Google in the big data market include the Big Query, Google Cloud Smart Analytics, Cloud Dataflow, Cloud Dataproc, Cloud Data Fusion, Cloud Composer, Data Catalog, Google Data Studio, Cloud Dataprep, Cloud Data Transfer, Cloud Storage, Google Analytics 360, all these solutions allows companies to ingest and analyze hundreds of millions of events every second from apps or devices all around the world.
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