Written by Cody Sanford, former CIO of T-Mobile
You’ve heard it over and over again: data is the crown jewel of an organization. This is why it is frustrating to see so many companies struggling to get real value out of their data. For the vast majority of companies, data is the root of least-leveraged revenue growth. Here, I’ll discuss what I’ve seen happen, and some ideas to help companies get the most out of their data.
Data: final frontier
Data represents the last mile to modernize the organization. Speed, scale, and agility were the goals of the first pillars of digital transformation, and organizations have spent the greater part of the past decade decoupling, refactoring, and automating to realize those benefits. Many companies are also starting to aggregate and transform data storage ecosystems by moving to cloud-native architectures.
Today, most of this data is used to enhance analytics capabilities and improve backed and unsupported digital customer journeys. But remarkably few companies have harnessed the power of all their data to generate real revenue growth.
why? Businesses’ most valuable data—created from the billions of interactions they have with their customers—remains locked in silos and isolated in diverse operational data warehouses. Ironically, these data warehouses have expanded rapidly as a byproduct of digital transformation. As services and apps become increasingly separate and more granular, they have exploded in number.
Likewise, operational databases and the abstraction layers that supported them have multiplied. With the increase in the number of data warehouses, so has the diversity of operating platforms. Most large organizations support dozens of mostly proprietary and highly decoyed NoSQL (and SQL) platforms – it’s like a puzzle with pieces that don’t really fit together.
How can your data live up to its potential?
All of this has dramatically increased the complexity that organizations grapple with when it comes to their data structures — making them difficult to optimize to scale and layer costs. This network of databases is expensive to license and expensive to maintain.
What’s worse, the data in it is often referred to storage and direct transaction support for its northbound applications. At best, the data is streamed into data lakes and used for decision analytics.
The huge potential of data – as a real-time and contextual revenue engine – remains unrealized. It is very difficult to take advantage of this opportunity.
But what if we could simplify these data environments and unlock the value of this buried data, by increasing data availability and speed, and what if we could dramatically reduce licensing and operating costs?
Unite data to win
The way you do it is by standardizing your central operational data stores; Standardize data orchestration with a single cloud-native architecture to extract, stream, merge and present data for all applications in your organization.
Getting to this point is not easy, but there are many tools and possibilities that can make data standardization achievable. An important piece of this puzzle is open source software (OSS). Increasingly, companies that succeed in Generate revenue with their data They rely on open source software to build various components of their data structures. It is an essential way to take advantage of the latest cutting edge innovations and also easily create and test different tools without major investment.
Apache Cassandra®Proven, Best of Its Kind NoSQL Database, and Apache PulsarIt’s an advanced messaging and live streaming platform that’s powerful data stacking components, for example, that together can help organizations manage all of their data in real time—whether moving data or unstable data. Other important parts of the data structure that are also OSS include Apache Spark, an engine for large-scale data analytics, and ElasticsearchAn open source search and analytics engine.
Another key to freeing teams for innovation is serverless database technologies, which enable organizations to develop and run data-centric applications without worrying about running into scope limitations. A variety of vendors offer serverless databases, including DataStax, PlanetScale, CockroachDB, and others. Workload management is becoming a thing of the past, and developers can easily test new ideas without worrying about database capacity limitations. In a similar vein, data APIs (such as open source stargate) is an important way to simplify development by eliminating the complexities of data layers, and freeing developers to do what they do best: build.
Many organizations today struggle to turn real-time data into revenue, but there are a range of technologies that enable organizations to break these valuable assets out of silos, standardize them, and use them to their fullest potential.
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About the author:
Cody Sanford served as Executive Vice President of Information and Head of Product at T-Mobile until April 2021, where he led the company’s digital transformation strategy that fuels the Un-carrier revolution. He led the development of a product-centric technology organization that today harnesses the power of people, processes, and technology to bring innovative T-Mobile experiences to life for customers and frontline employees. Under Cody’s leadership, the Product and Technology Organization has spearheaded T-Mobile’s digital transformation, with an industry-leading software development store, expansion into adjacent product and service categories, and a leadership role in delivering open source innovations that solve big customer problems.
Cody now serves as a board member and board advisor for a number of technology companies, enterprise software and technology services.