Big Data Market in India 2023

Big data analytics is the process of analyzing large amounts of raw data to uncover information and patterns that will assist businesses in making informed decisions. It is a type of analytics that employs processes such as predictive modeling, to examine large amounts of unstructured data and provide businesses with solutions that keep them ahead of the competition. Organizations rely heavily on big data to boost profits, improve analytics skills, and support risk management capabilities.

Market insights:

The global big data market was valued at INR 21329.61 Bn in 2022. It is expected to reach INR 69,777.53 Bn by 2027, expanding at a Compound Annual Growth Rate (CAGR) of ~27.96% during the 2023 - 2027 period. The big data market in India was valued at INR 157.24 Bn in 2022. It is expected to reach INR 253.22 Bn by 2027, expanding at a CAGR of ~10.60% during the 2023 - 2027 period. At present, India is one of the top 10 countries in the market, with over 600 data analytics firms. This number is expected to increase in the future. Big data has become prevalent in several industries, including telecommunications, financial services, e-commerce, and healthcare, because of the increased demand for cloud-based solutions and predictive analytics capabilities.

Impact of COVID-19:

The pandemic has caused delays in the implementation of new big data technologies and tools, further slowing down the market's growth. In order to forecast the development of the coronavirus sickness and its risks, data analysts from hospitals in India and around the world succeeded to collect information on patient travel and hospital data. With the shift towards remote work, there has been an increased need for cloud-based big data solutions, creating opportunities for cloud service providers in the Indian market.

Market Influencers:

Market drivers:

As businesses strive for agility, flexibility, and resilience, they will become more reliant on cloud platforms, infrastructure, and software than before. The demand for cloud-based collaboration tools, content management solutions, and online streaming platforms has increased. The continued trend of increased remote workers in 2021 resulted in a surge in spending on desktop-as-a-service (DaaS) and infrastructure-as-a-service (IaaS). Across sectors, several organizations consider data science as a critical component of an enterprise's ability to scale sustainably.

Key deterrents to the growth of the market:

Analysts will get poor results if the system relies on data with flaws, errors, or which is incomplete. Data quality management and a mandatory data validation process covering every Extract, Transform, Load (ETL) stage can help ensure the quality of incoming data at various levels. It is also critical to perform a system redesign step by step, gradually replacing old elements with new ones.