Analytic data platforms for decision support leaders and major players for 2023

According to the IDC MarketScape : Asia/Pacific excluding Japan (APeJ) Analytic Data Platforms for Decision Support 2023 Vendor Assessment, AWS, Google, Microsoft, and Oracle are identified (in alphabetical order) as “Leaders” among the vendors in the software category, Analytic Data Platforms for Decision Support. Closely followed by “Major Players” in the market namely (in alphabetical order) Alibaba, Cloudera, Huawei, IBM, Snowflake, and Teradata.

In the current volatile economic landscape, the ability to move ahead with business priorities largely depends on an organization’s data-driven decision-making capability — its enterprise intelligence (EI). Improving EI or data-driven decision-making will often require concerted investments and actions at multiple levels: from data platforms (to enable more openness, flexibility, scale, and connectivity) and pipelines and processes (to enable more effective and consistent data processing to make data insight-ready) to tools (to build and deliver analytics and insights), decision-making and action-taking processes, and culture.

Modernizing decision support systems is the key to data-driven decision-making and must evolve to keep up with the rapid pace of innovation. Organizations must leverage high-performance and scalable analytic data platforms that can work on a variety of data types and deliver results for multiple user personas. Organizations globally and in Asia/Pacific are increasingly relying on cloud-based data platforms to modernize data workloads and report optimal benefits. This could be crucial for organizations exploring options to future-proof their EI and decision-support capabilities.

“Given the global economic downturn, businesses need to continue to leverage analytics and AI across the board to improve productivity and operational efficiencies. This has accelerated the need for a robust, yet nimble decision support platform that can balance and serve the needs of the user from scalability, performance, reliability, and time-to-value perspectives, depending on the use case it is designed to deliver,” says Deepika Giri, Associate Vice President, Artificial Intelligence and Analytics Strategies at IDC Asia/Pacific. IDC