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Executive Summary | Cloud Data Management

Executive Summary for the TDWI Best Practices Report: Cloud Data Management

The world of IT continues to become more hybrid in that some information systems and data remain on premises while others are increasingly deployed to the cloud. Technical users are lured to the cloud because of its speed, scale, elasticity, and low level of maintenance, while business people are drawn to its agility, low cost, and ability to support new data-driven business practices.

The rise of the cloud has ramifications, especially in the realm of data management. As if managing data of increasing size weren’t hard enough, organizations are now challenged to monitor business processes, assemble complete views of customers, and weave a cohesive analysis of corporate performance based on hybrid data that is strewn across the traditional enterprise and multiple clouds. The long list of data platform and tool types that manage hybrid data coalesce into hybrid data architectures that are difficult to understand and optimize.

Cloud data management (CDM) has risen to address these new challenges. CDM is the latest evolution of data management, and it has been greatly updated and extended to support new cloud data platforms, applications, and use cases. It also integrates data from those with traditional on-premises sources and targets. CDM promises to enable the next level of business analytics and data-driven operational innovations based on data from platforms old and new.

Among users surveyed, CDM is already in use in cloud data warehousing, advanced analytics, multichannel marketing, real-time operational dashboards, and for data sync among on-premises and software-as-a-service (SaaS) applications. According to our survey results, the leading benefits of CDM are scalability, elasticity, analytics, real-time operations, and agility. Barriers to successful CDM include issues in governance, data migration, data quality, and tool maturity. A whopping 96% of users surveyed say CDM is an opportunity, which explains why so many are adopting cloud systems or migrating to them. Although most data is managed on premises today, survey data suggests that the amount on cloud platforms in the typical organization will at least triple over the next three years.

Our survey says that the infrastructure and system architectures for cloud data management are usually owned and maintained by central IT or a group responsible for enterprise data architecture. However, groups for data warehousing, DataOps, and general data management contribute to CDM solution designs and data requirement definitions. Among these workers, almost half of job titles include the word "architect" because creating unified solutions in a multiplatform and hybrid context requires deep architecture expertise for data, integration, systems, and applications.

The hybrid IT ecosystem under discussion includes an amazing variety of systems, each fulfilling a specific purpose, while also interoperating with many other systems. On the data side of things, the relational database continues its hegemony, though it has evolved to run natively on clouds and to focus on analytics (e.g., columnar, graph, and NoSQL databases). Also, data management tools (for integration, quality, metadata, and virtualization) have evolved to execute processing on servers and inside data platforms, both on premises and in the cloud, via interfaces for all these. On the application side of things, traditional on-premises applications are today regularly mixed with SaaS applications in clouds. Despite the eclectic nature of these massive software portfolios and the massive amounts of distributed data involved, cloud data management integrates hybrid data across hybrid data architectures with scale, speed, quality, and compliance.

This report explains in detail what CDM is and does so data professionals and their business counterparts can understand what CDM can do for them and how they might organize a successful program.

Actian, Couchbase, Datameer, Denodo, Hitachi, Snowflake, SAP, and Trifacta sponsored this report.

About the Author

Philip Russom, Ph.D., is senior director of TDWI Research for data management and is a well-known figure in data warehousing, integration, and quality, having published over 600 research reports, magazine articles, opinion columns, and speeches over a 20-year period. Before joining TDWI in 2005, Russom was an industry analyst covering data management at Forrester Research and Giga Information Group. He also ran his own business as an independent industry analyst and consultant, was a contributing editor with leading IT magazines, and a product manager at database vendors. His Ph.D. is from Yale. You can reach him by email ([email protected]), on Twitter (, and on LinkedIn (

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