K
Kathleen Martin
Guest
Data is critical to enabling developer productivity, building powerful customer experiences, and driving revenue. But many of the enterprise technology leaders I speak with face the same obstacle when it comes to harnessing their data: complexity.
Data is often locked away in multiple mismatched technologies scattered across the organization. As a result, enterprises can’t access and leverage the data with the speed or at the scale needed to accomplish their goals.
So how do you solve for data complexity? Standardize your data.
How did we get here?
Enterprises understand the importance of data. To try and harness it, many have invested in a variety of point technology solutions. This might work for one team, one project, or one application, but the reality is it locks data in silos across the organization.
These silos make it hard for developers to be agile, and they prevent enterprises from getting the big picture about their customers. When data is fragmented, organizations get stuck in what I call the “Innovation Stalemate”—without data standardization and modern, cloud-native technologies, it’s almost impossible to bring new innovations to market quickly.
Cost becomes a major challenge, too. With all these different technologies and data silos, enterprises have to maintain too many products and skills. Managing the costs of scaling data becomes a challenge. This is the “TCO Death Spiral.”
Real-time data
Data complexity prevents an enterprise from getting the most value out of all their data – especially their real-time data. Real-time data represents the current state of the business (a customer profile, or a process state) or a change in the business (a customer action, a transaction moving forward, or sensor data capture). This data should be instantly available and accurate, ready to power the most critical business applications.
Real-time data drives user experiences, protects customers and enterprises from fraud and cyberthreats, and drives critical supply chain and inventory management processes. In other words, it directly impacts customer satisfaction, revenue, and innovation.
With real-time data locked away in silos and managed in varying technologies, enterprises and developers cannot drive business transformation. The data availability needed to fuel critical applications is significantly reduced.
How do we fix it?
What’s the opposite of data complexity and fragmentation? Simplifying data environments and standardizing the data that matters most in a unified stack.
We’ve thought a lot about this at DataStax as we’ve been supporting developers and enterprises with an open data stack to serve real-time applications. Our database-as-a-service Astra DB makes the infinitely scalable open-source database Apache Cassandra® easy to use, build on, and afford. This instantly available “data at rest” is critical to many use cases (customer profile, session information, etc.).
But it’s not everything. The world operates in real time, and streaming “data in motion” captures changes on the fly. Only a stack that unifies both real-time data at rest and in motion can deliver the data standardization needed to solve for data complexity and deliver a new level of digital excellence.
You need several elements for a successful standardization. Streaming and messaging technologies like Apache Pulsar allow real-time data to be acted upon as it’s generated. (For example, when FedEx sends a notification to the buyer that their package is being delivered). It’s one of the reasons DataStax Astra Streaming, which is built on Pulsar, is a key component of the open stack we deliver for enterprises and developers.
Continue reading: https://www.cio.com/article/305012/hello-simplicity-goodbye-complexity-standardize-the-real-time-data-that-matters.html
Data is often locked away in multiple mismatched technologies scattered across the organization. As a result, enterprises can’t access and leverage the data with the speed or at the scale needed to accomplish their goals.
So how do you solve for data complexity? Standardize your data.
How did we get here?
Enterprises understand the importance of data. To try and harness it, many have invested in a variety of point technology solutions. This might work for one team, one project, or one application, but the reality is it locks data in silos across the organization.
These silos make it hard for developers to be agile, and they prevent enterprises from getting the big picture about their customers. When data is fragmented, organizations get stuck in what I call the “Innovation Stalemate”—without data standardization and modern, cloud-native technologies, it’s almost impossible to bring new innovations to market quickly.
Cost becomes a major challenge, too. With all these different technologies and data silos, enterprises have to maintain too many products and skills. Managing the costs of scaling data becomes a challenge. This is the “TCO Death Spiral.”
Real-time data
Data complexity prevents an enterprise from getting the most value out of all their data – especially their real-time data. Real-time data represents the current state of the business (a customer profile, or a process state) or a change in the business (a customer action, a transaction moving forward, or sensor data capture). This data should be instantly available and accurate, ready to power the most critical business applications.
Real-time data drives user experiences, protects customers and enterprises from fraud and cyberthreats, and drives critical supply chain and inventory management processes. In other words, it directly impacts customer satisfaction, revenue, and innovation.
With real-time data locked away in silos and managed in varying technologies, enterprises and developers cannot drive business transformation. The data availability needed to fuel critical applications is significantly reduced.
How do we fix it?
What’s the opposite of data complexity and fragmentation? Simplifying data environments and standardizing the data that matters most in a unified stack.
We’ve thought a lot about this at DataStax as we’ve been supporting developers and enterprises with an open data stack to serve real-time applications. Our database-as-a-service Astra DB makes the infinitely scalable open-source database Apache Cassandra® easy to use, build on, and afford. This instantly available “data at rest” is critical to many use cases (customer profile, session information, etc.).
But it’s not everything. The world operates in real time, and streaming “data in motion” captures changes on the fly. Only a stack that unifies both real-time data at rest and in motion can deliver the data standardization needed to solve for data complexity and deliver a new level of digital excellence.
You need several elements for a successful standardization. Streaming and messaging technologies like Apache Pulsar allow real-time data to be acted upon as it’s generated. (For example, when FedEx sends a notification to the buyer that their package is being delivered). It’s one of the reasons DataStax Astra Streaming, which is built on Pulsar, is a key component of the open stack we deliver for enterprises and developers.
Continue reading: https://www.cio.com/article/305012/hello-simplicity-goodbye-complexity-standardize-the-real-time-data-that-matters.html
