Everybody needs more data and more analytics, with so many different and sometimes often conflicting needs. Data engineers need batch resources, while data scientists need to quickly onboard ephemeral users. Data architects deal with constantly evolving workloads and business analysts must balance the urgency and importance of a concurrent user population that continues to grow. We have use cases we have never seen before, now becoming commonplace requests from businesses looking for better and deeper insights.
Managing users within this changing data landscape leads to three pressure points: Long wait times, missed service agreements, and cloud mandates. The time it takes to get new resources into business users’ hands is way too long, often longer than the window of opportunity allows. Meanwhile, some workloads hog resources making others miss defined agreements. Finally, we have pressure to move work to the cloud, knowing that the cloud can allow us to grow and innovate faster.
Today’s cloud landscape is filled with multiple solutions, ready to help us get our insights from data faster, help us discover amazing patterns and correlations, and drive new innovations all at a better cost. Or so they all claim. When adopting cloud data management, there are some fundamental principles we need to embrace to be successful, or we risk security gaps, failure to maintain regulatory compliance or unexpected cost overruns.
Fundamental principles to be successful with Cloud data management
Cloud data management fundamentals include embracing new technologies, looking at platforms and point solutions, and maintaining the secure, well-governed data center we depend on every day. New technologies like Kubernetes, containers, and the separation of compute and storage, allows for more flexibility and greater isolation of workloads. Public cloud offerings create convenient choices for quick availability of resources for important workloads, while platforms combine multiple analytics functions together across a common data context. With a platform approach, we can expand security, governance, traceability, regulatory compliance, and a number of other essential data disciplines to our enterprise services.
Whether you are in manufacturing, looking at predictive maintenance, working on Patient 360 in healthcare, improving customer experience in banking, or any other industry’s hottest struggle, having a cloud data management infrastructure will benefit you in numerous ways. You will be able to align data engineering, data science, machine learning, data flows, data streams, analytics, data warehousing, and more, with greater flexibility, faster delivery of service and results, without clashing between all different types of users working together.
To be successful with cloud data management, however, you cannot forgo the essential role that security, traceability, and governance play in making the most data available to most users. Contrary to how it might seem to some, the more assured you are on data security, the more data sets you can make available to users for self-service, knowing that the data will remain secure throughout its use in any workload. By that same measure, you can also make more data available if we can always maintain traceability for where it was used, where it came from, and how it was applied to a given report or other decision support vehicle. In this way, regulatory compliance can continue to be assured even when using both on-premises and public cloud solutions at the same time. Using a single data context, well-governed, ensures we have the best quality data available to all users at once.
The cloud promises us unprecedented sharing of data, self-service ease of use, and immediate results on any form of analytics while applying the latest in state of the art technologies. Once we make the move, even more innovation will continue, at an even faster pace, making newer, faster, and better insights possible. As long as you start with a solid cloud data management foundation.
Join us for Cloud Data Management Fundamentals, a virtual event on October 8, 2020, 10:00am US pacific time, 1:00pm US eastern time, where we discuss this topic in further detail, complete with customer use case examples, and a view of what is to come next.
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