With the rise of the modern data platform—capable of storing, processing, and analyzing massive data sets—the pace of change in cloud data has been exponential. With the advent of elastic architectures that allow applications to scale up or down with demand, upfront capital investment is no longer required for physical storage solutions, and expensive, on-premises data centers are no longer an absolute requirement.
Cloud advances enable an enterprise to go from idea to execution in dramatically less time and process both data-at-rest and data-in-motion to unlock value in ways previously impossible. Cloud represents a key transformation that not only affects the physical on-premises server architecture, but also the applications that power the enterprise.
Traditionally, large enterprises have been powered by a complex suite of monolithic applications hosted on premises. The enterprise resource planning software promised an integrated environment that powers much of an enterprise’s daily functioning. Historically, this software has been tightly coupled to the physical, on-premises storage solutions that run it—solutions that are large and complex. Cloud data is completely changing this.
The modern enterprise is now being powered by distributed and scalable best-of-breed software as service platforms that offer many benefits over traditional systems. Modern cloud applications use software as a service in a way that is scalable without requiring an on-premises database. With no need to purchase physical hardware to run dedicated software on, maintaining complex software stacks isn’t necessary. Cloud vendors provide the flexibility to scale with the demands of an enterprise.
With its modern, schema-less architecture that allows for any type of data to be stored—including audio, video, and transaction data—big data isn’t constrained by traditional storage solutions and data transfer methods. By moving big data workloads to the cloud, enterprises now have the per-use/on-demand scalability and flexibility in their software stacks, as well as the ability to import/export and use the data in any way they see fit.
These features future-proof applications and provide an agility previously impossible. As new demands surface, such as the current transition to “per-use” style infrastructure, cloud future-proofs enterprise data by not locking it into a closed-source system. And enabling a connected architecture with the cloud opens up a whole range of enterprise transformations.
Cloud computing has not only transformed the applications an enterprise uses, it has also revolutionized the storage of massive sets of data, as well as the analytics and solutions that those data sets can power. Distributed data lakes have become the wave of the future, and cloud technologies are powering the transformation. Instead of needing to pre-purchase hardware and software, you can now buy applications and infrastructure and pay for them on a “per-use” basis.
An enterprise can load all of its previously disconnected data sets and databases into a cloud data lake and immediately drive insights. For example, Microsoft Azure HDInsight offers a common platform for a massive variety of data in a schema-less storage and processing solution, and companies have the much-needed freedom of choosing their preferred cloud provider.
With this level of agility, an enterprise can begin driving insights from their data, unlocking myriad potential uses cases. These cloud data lake solutions, built on HDInsight, can store any type of data—oil and gas sensor data, website clickstreams, even audio and video—because of the schema-less design and open source software stack.
With the ability to integrate all your data sets into a connected data platform, and the ease of communicating and transferring data via cloud applications, you’re able to unlock revenue and drive value in new ways. For a retailer, a connected platform can combine website clickstreams, Salesforce, social media feeds, and more into a single view of the customer. For an oil and gas company, this kind of platform provides the ability to monitor and optimize streaming sensor data in real time and to scale up or down with computing demands. Cloud represents a truly multifaceted benefit, driving down costs while unlocking new revenue streams through data analytics.
To learn more about how you can utilize the cloud in your data solutions, check out this e-book.