Modernization for agility at scale and insights at speed
Thanks to rapid advances in artificial intelligence (Al) and machine learning (ML), companies are finding that a real oasis of evergreen differentiation and value is within reach.
Many organizations are turning to cloud-enabled enterprise data platforms to find that value. These platforms offer extensive scalability and dynamic resource elasticity; powerful cloud analytics capabilities; and the ability to aggregate data from multiple cloud environments, on-premises sources, and third-party applications, making it all accessible from a single inclusive view.
Promises—and pitfalls—on the journey to data modernization
To understand the role and value of data observability, it’s important to recognize the benefits and pitfalls that often lie along two paths.
Path 1: Cloud first
Many enterprises choose to "lift and shift" their data from existing legacy infrastructure, with a plan to optimize later. This can be a smart approach from an initial cost perspective, and accelerate access to new cloud analytics and automation capabilities. But too often, existing inefficiencies get carried over in the process, or new issues can appear.
Path 2: Optimize first
Other organizations optimize both underlying data models and extract-transform-load processes prior to moving to cloud. This approach can help reduce the risk of unexpected disruptions while supporting data team transition. However, this can cause higher costs in the near term as well as delayed access to the transformative cloud capabilities.
Common hurdles on both paths
Seeing your way to value
What’s needed are new ways of cultivating value from cloud-enabled enterprise data platforms—and across your whole data ecosystem—through data observability.
Data observability defined
Deloitte defines data observability as a technology-enabled, people-powered discipline that helps you see, understand, and optimize your end-to-end data supply chain in ways that foster transparency and trust, reduce risk, improve efficiency and budget management, and cultivate data as an investible asset to drive evergreen value.
A more resilient, efficient, and effective data ecosystem
Data observability isn't just about implementing a new platform or tool. It's about leveraging the right combination of technology, processes, governance, and talent—in the right order—to get more out of data investments and nurture evergreen business value.
Our approach to data observability is rooted in three guiding principles:
What gets seen gets managed.
In the rush to modernize data operations via cloud migration, organizations too often wind up perpetuating—and even expanding—the inefficiencies and related risks, costs, and trust issues that existed in their legacy data systems and processes. That's where the discipline and technologies of data observability become essential.
Don’t just observe. Optimize.
Data observability reveals operational challenges and problems. As leaders better understand how data moves into and through your enterprise data platform, data operations teams can be pointed at improvements that have a direct impact on your business. Data observability becomes a critical enabler for managing costs and infusing efficiency across your data ecosystem.
Transform visibility to value.
Data should be viewed as money—an investible asset—and managed accordingly. Deloitte helps embed this mindset into your day-to-day data operations by bringing a financial operations lens to what you see. Working alongside you as a trusted collaborator, we help you transform data observability from an activity of your organization into an integral driver of business value.
Cultivate a thriving data ecosystem
Migrating to a modernized, cloud-enabled enterprise data platform with the right strategy can provide fertile ground on which to grow—enabling faster insights, improved collaboration, and more efficient and effective data operations.
Data observability from Deloitte can help provide comprehensive visibility across the end-to-end data life cycle. The result? Your
cloud-based data lake can become a renewable oasis for growth.
Set yourself up for success: Establish comprehensive visibility across your entire data life cycle
Dive into the full report to learn more about how data observability can help streamline your data operations and infrastructure.
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