The hybrid cloud data platform (HCDP) optimizes both business intelligence (BI) and data science workloads with capabilities such as integrated analytics, columnar and parallel processing, data compression, and workload isolation. Vendors selling HCDPs have decades of experience supporting and tuning analytics workloads on structured and semi-structured data. An effective HCDP is unified, analytical, automated, fast, efficient, governed, and open.

Software companies represent an ideal case study. They use the HCDP to support two primary categories of modern analytics use cases. First, they analyze the product experience to improve what customers buy. Second, they deliver analytics as a product, meaning that analytics is what customers buy.

Key Takeaways:

• The hybrid cloud data platform (HCDP) optimizes both business intelligence (BI) and data science workloads with capabilities such as integrated analytics, columnar and parallel processing, data compression, and workload isolation. An effective HCDP is unified, analytical, automated, fast, efficient, governed, and open.
• Software companies use the HCDP to support two modern categories of analytics use cases. First, they analyze the product experience to improve what customers buy. Second, they deliver analytics as a product, meaning that analytics is what customers buy.
• Because some data will persist on premises, enterprises must design HCDP architectures that make the best of the cloud—such as optimized processing, open data formats, and data science tools—available anywhere in their hybrid environment.
• Rather than going big to start, consider adopting the HCDP for one or two short-term projects with measurable outcomes. If those projects deliver results, you can win executive support to tackle more ambitious projects.
•  Implement a data architecture that enables your data teams to deliver the right insights to product managers so they can both analyze their products and build analytics into their products.

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