October 2021 Summaries

The cloud data platform is an emerging paradigm that combines elements of data warehouses and data lakes to integrate myriad data points, generate insights, and create business value. It brings together many data types, users, and use cases, transforming and delivering data to business intelligence (BI) and data science tools, as well as applications that embed BI and data science algorithms. The cloud data platform provides a common repository to support the overlapping worlds of BI, data science, and applications, and consumes cloud provider infrastructure to optimize performance with capabilities such as columnar processing, workload isolation, and lightweight indexing. Various vendors offer distinct mixes of elements, including data clouds, SQL lakehouses, unified analytics platforms, and index-driven cloud data platforms, each extending their platform with additional capabilities. One example is ChaosSearch's index-driven cloud data platform, which helps mid-sized and large enterprises increase the scale of their log analytics and BI workloads without incurring too many expensive compute cycles, transforming, querying, and searching data objects to support analytics use cases.

The BAI Communications team, which handles complex infrastructure projects worldwide, struggled with retaining long-term log data for analytics due to high costs. After discovering ChaosSearch at AWS re:Invent, they implemented the cloud data platform, unlocking insights into network performance and improving customer services. With ChaosSearch, the team can easily query logs without moving data or creating complex ETL pipelines, resulting in cost savings and compliance benefits. The team plans to integrate ChaosSearch with business intelligence platforms like Tableau in the future.

The Raconteur Future of Data Report highlights key trends shaping the future of enterprise data management in 2021, including the growing importance of data for large organizations, the increasing adoption of artificial intelligence to support business decision-making, and the need for businesses to balance personal data collection with consumer trust. The report explores how businesses are generating and collecting more data than ever before, and innovating to make better use of it, while also addressing challenges such as data privacy and security regulations, big data analytics in human resources, and data democratization.