Global Data & Analytics Market: 2022

Global Data & Analytics Market: 2022

After displaying robust growth in 2021, the global data and analytics market is all set to continue its bullish run in the coming year

The global data and analytics market saw its value appreciate 10.3% from US$83 billion in 2020 to US$91.6 billion in 2021, according to the latest report from Global Data, a UK-based data analytics and consulting company. This solid growth can be attributed to enterprises beginning to resume their investments on technology after a tumultuous 2020, which saw significant erosion in enterprise revenues due to COVID-19. 

Enterprises were expected to speed up their digital transformation journey to be future-ready for disruptive events like pandemic, trade wars, etc. Data and Analytics will be a core part of their focus in coming years. According to analyst firm, IDC banking, discrete manufacturing, and professional services are currently making the largest investments in big data and analytics solutions. Rapidly expanding Internet of Things (IoT) networks, Data as a product, quantum computing, and data use for hyper-personalization – there are many emerging trends in the big data segment driving growth, according to a Gartner survey.

The survey finds that businesses across the vertical sectors are realizing the importance of data collected through their customers as well as via operations. From understanding the consumer spending patterns to ensuring the robustness of supply chains, analytics platforms are slowly becoming beginning to infiltrate almost every aspect of functioning of a modern enterprise.

BFSI leads the growth

Banking, Financial Services & Insurance (BFSI) sector is the single largest spending contributor to the global data and analytics market, accounting for 14.9% of total addressable market value as of 2020. Its spending on IT management is poised to grow from an US$12.4 billion in 2020 to US$18.7 billion by 2025 at a CAGR of 8.5% over 2020-2025. Widespread digitalization in banking and insurance operations, rising adoption of mobile and web-based banking, and financial platforms along with emerging fintech applications such as digital wallets are the major drivers of the market. 

Information technology (IT) is the second largest contributor to the global data and analytics market, accounting for 9.5% of the total spending estimated for data and analytics software or US$7.9 billion in value as of 2020, which is set to grow to US$11.1 billion by 2025. 

Manufacturing sector is the third largest contributor for the global data and analytics market, with its spending on data and analytics growing from an estimated US$7.8 billion in 2020 to US$12.5 billion by 2025. Manufacturing is expected to outplace IT as the second largest end-use vertical over the forecast period Digital transformation and growing data volume are the key drivers of the growth of data and analytics spending Digital transformation has become one of the key strategic objectives within most enterprises. 

Data & analytics drive digital transformation

Most businesses now see digital technologies as a key to operational improvement and market growth. Furthermore, data and analytics are often at the heart of digital transformation as enterprises scramble to drive actionable insights into their businesses and customers, hence most of the times digital transformation includes implementation of various business analytics platforms. 

Similarly, there has been an almost explosive growth in enterprise data in recent years, owing to proliferation of handheld devices among consumers as well as technologies such as internet of things (IoT), driving businesses to implement data management tools as well as various big data analytics platform to effectively manage and utilize both structured and unstructured data. Cloud has become the de-facto deployment model for analytics platforms Cloud has become an inevitable part of business data analytics (BDA), as processing extremely large datasets requires a computing platform capable of handling data meeting the criteria of variety, velocity, and volume.

Enterprises shifting to Cloud

Furthermore, as enterprises are shifting majority of their data and workload off-premises to Cloud, it is more convenient to use platforms for data management and analysis hosted in Cloud, rather than using them on-premises. Consequently, major hyperscale Cloudproviders now provide a significant portfolio of analytics solutions, available to their existing customers Analytics augmented with AI and NLP giving rise to smart analytics.

With augmentation of AI, machine learning (ML), and NLP, the world is witnessing the arrival of smart analytics or automated analytics. Both established software vendors as well as start-ups have been developing different tools and methods to automate data science & analytics tasks, which would free up data professionals to focus more on building data science models which can help enterprises to realize the full potential of the digital transformation. 

Collaborative analytics emerges as a trend

Collaborative Analytics increasingly finding favour.Enterprises are moving away from individual data analysis to platforms and processes that allow sharing of data, results, and decisions, resulting in better communication, validation, and coordination of actions. 

Collaborative analytics is part of the broader movement in analytics to approach BI from a community-driven perspective. It uses a combination of business intelligence software and collaboration tools to allow a broad spectrum of people in an organization- (and beyond) to participate in data analytics. It emphasizes the problem-solving process, correctly identifying that data analysis that generates the most valuable insights doesn’t happen in a vacuum. Without the input of people who have a thorough understanding of the industry, are talking with customers, working on product development, managing production, etc., data analysts are operating without context.

Collaborative analytics makes data sharing process easier and enables efficient decision making. Ultimately, it brings together data, processes, tools, and people onto a single unified system enabled by technology and an open, adaptive, and smart ecosystem. Engaging co-workerswhile sharing knowledge and data via collaborative analytics enables companies to make more informed and transparent decisions at an accelerated pace.

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