Developers now have access to strong transformation tools thanks to recent database advancements.
Data architectures have had a bad rap when it comes to digital transformation.
Many businesses have prioritized modernization by migrating software to the cloud or developing ecommerce capabilities (if they are retailers). However, data has been left out of the digital transformation story in many situations because data systems are massive, monolithic, brittle, and difficult to manage—in other words, there are significant risks to the business if the modernization process fails. Many businesses have shifted their focus to easier-to-manage projects, deferring data platform modernisation to a later date.
I'd like to talk about a few common misunderstandings that might stymie data architecture modernization efforts, as well as a vital strategy for achieving this goal.
Two misconceptions about digital transformation
When businesses explore digital transformation, there is a common misconception that it is a massive, all-or-nothing endeavor that transforms a traditional business into a modern, digital one.
Consider how merchants modified themselves from a high-level perspective. A classic brick-and-mortar retailer did not simply reboot and become an ecommerce business. Instead, ecommerce began with a small percentage of sales, such as 2%, then 10%, then 20%, and so on.
It’s the same for most enterprises across verticals. Transformation is a step-by-step process that usually starts small—one initiative at a time (from a project to a program, to, eventually, a platform).
Another myth persists: innovation is driven from the top down. In general, though, technology executives optimize and expand effective processes that have begun within their business, as well as provide platforms for project-based innovation. However, developers are usually the ones that construct these initiatives. Digital transformation emerges from small-scale trials that, if successful, must grow quickly. This poses a problem, especially when it comes to updating an organization's data estate.
Equipping developers for transformation
To succeed in digital transformation, developers must be able to swiftly start a small project and scale it up quickly as needed—without having to halt for scalability testing, or worry about how much funding the project would demand, or how much latency it will introduce into a system. When you multiply these requirements over a number of new projects, the need for robust, scalable, and user-friendly data platforms becomes vital to success.
Databases, on the other hand, have made this type of job difficult for a long time. It needed time and effort to scale up and down, which often resulted in costly overprovisioning.
By providing "serverless," or "pay-as-you-go," data, a small collection of cloud databases, including DataStax and MongoDB, is allowing developers to focus on their modernization projects without the distractions of provisioning, scaling, and other parts of data administration. Scaling up or down is made easier and faster by separating the computing and storage processes.
Data use is accurately matched to workload peaks and valleys in a serverless system. The pay-as-you-go model avoids the time-consuming and costly job of calculating peak loads, allowing developers to pay only for what they use, regardless of how many database clusters they design and deploy.
Serverless data is making a real difference at Circle Media Labs, a provider of apps and devices to help parents manage their family’s time online. The company relies on Astra DB from DataStax, a serverless, multi-cloud database-as-a-service (DBaaS) built on Apache Cassandra®.
Nathan Bak, a former principal engineer at Circle, used this pay-as-you-go version of Cassandra, a high-performance, open source, NoSQL database, to test a variety of product and service ideas based on the company's massive data set. He points out that with a serverless database, there is no competition over who gets access to a database for constructing proofs of concept; everyone can host their own Cassandra cluster.
One of these projects grew into a successful new product for Circle, which necessitated rapid scaling.
Cassandra without limits
Circle profited from the ability of a serverless database to facilitate the development of numerous projects at once while avoiding infrastructure worries, even as a cloud-native organization. Having this level of Cassandra access might be especially beneficial in digital transformation efforts.
Cassandra has long been the database of choice for businesses looking to scale massively: if nothing else could manage a project that required robust reliability at scale, Cassandra was the answer. It's why Netflix, Best Buy, Bloomberg News, and a slew of other companies have placed their faith in the database.
Developers can have access to all of Cassandra's benefits without the expenses or management requirements thanks to today's serverless technologies.
It's easy to become overwhelmed by digital transformation efforts, whether you're updating your data architecture or any other aspect of your business. Understanding that your developers are important to the success of any transformation endeavor is a fundamental technique for working through this potentially debilitating obstacle. To play their part, development teams want tools that allow them to tackle projects that, if successful, will be ready and able to scale up to enterprise levels.
By Ed Anuff, Chief Product Officer, DataStax
Source: CIO
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