Market Trends of Big Data Technology Industry
Retail Industry to Dominate the Market
- With Big Data technologies and sophisticated analytics, the retail sector is undergoing a significant revolution. Retailers are using Big Data analytics to stay competitive due to the growth of e-commerce, online purchasing, and high levels of rivalry.
- Big Data is used throughout the whole retail process in the business to study customer behavior, forecast demand, and improve prices. Most big data applications in retail today are for system-wide cost reduction, enhancing the customer experience both online and in-store, data-driven adaptive supply chains, and real-time analytics and targeting.
- With the use of big data analytics, the industry is now more aware of consumer behavior patterns and can plan production based on these. Using big data from the public internet as user-generated content (UGC) or online customer reviews (OCR) data presents an up-and-coming alternative for analyzing retail customer behavior.
- In January 2022, J.D. Power, a global provider of data analytics and consumer intelligence, relaunched three major automotive data products maintained by the company’s Autodata Solutions division. These include solutions for vehicle identification number (VIN) descriptions, inventory management, and payment and incentives data for digital retail and desking applications.
- Retailers may store, integrate, and analyze a wide range of online and offline customer data, e-commerce transactions, clickstream data, email, social media, and call center records using a big data platform provided by vendors like MapR Technologies.
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Asia-Pacific to Witness the Highest Growth
- Asia-Pacific is seeing a boom in data produced from digital goods and services due to population expansion and increased e-commerce. While big data has been widely used by Asian-Pacific international banks (APAC), more local institutions are increasingly doing the same to achieve a "second-mover advantage."
- Due to increased Internet usage, organizations can access a vast amount of structured and unstructured data. Due to these advantages, substantial multinational corporations now have their big data evaluated for practical knowledge.
- End users are also embracing big data analytics outsourcing service models. Data analytics outsourcing is a business strategy where a data-driven organization entrusts a service provider with its data in exchange for access to insightful reporting. The provider handles infrastructure setup and maintenance, data management, and data analysis. The need for immediate insights is driving the need for significant data analytics outsourcing because managing the data generated by enterprises takes time.
- More physical servers must be added to the cluster to accommodate the growing data, which takes time and money. A cloud platform's complete scalability gives businesses access to limitless storage capacity on demand. As a result of its advantages, the technology is expanding in areas where it is being used.
- Moreover, In February 2023, Guizhou Province, a major big data hub in southwest China, announced its plan to invest 20 billion yuan (USD 2.9 billion) in big data-related initiatives in 2023. The director of the province announced that the province will accelerate the construction of 5G, computing networks, data centers, and other forms of advanced digital infrastructure. Such developments are expected to boost the growth of big data technology in the region.
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