Innovative organizations need DataOps and new technologies because old-school data integration is no longer sufficient. The traditional approach creates monolithic, set-in-concrete data pipelines that can’t convert data into insights quickly enough to keep pace with business. The following trends are driving the adoption of Hitachi’s Lumada DataOps Suite.
Because of the COVID-19 global pandemic, almost every industry is experiencing volatility, risks and changes to buying behavior. Nevertheless, in crisis often comes opportunity and a forcing factor for businesses to redefine themselves. Those looking to innovate after (or even during) this crisis should focus on two key concepts — data monetization and data modernization.
How large is your Hadoop data lake? 500 terabytes? A petabyte? Even more? And it is certainly growing, bit by bit, day after day. What began as inexpensive big data infrastructure now demands ever more expenditures on storage and servers while becoming increasingly unwieldy and expensive to manage. Such rapacity makes it ever harder to realize a proper return on investment from that Hadoop infrastructure.
Why is DataOps important? Without intelligent data operations (DataOps), there can be no digital innovation. Agile data environments improve business operations and enable new customer experiences and new business models. Our customers demonstrate every day the value of their data and how it is critical for digital transformation.
Unlike typical resources companies depend upon to thrive, the amount of data available to enterprises is not finite. With edge technology and smart devices, there is truly no limit to the quantity of useful data companies can and should be using to make better informed decisions. But many businesses unnecessarily limit the variety, quality, and extent of the data at their disposal by not having the right data architecture.
How Hitachi Vantara’s global IT team is enabling the “new normal” and delivering at speeds previously thought impossible.
Computer science loves abstraction, and now, as it turns out, so does data management. Abstraction means reducing something complex to something simpler that elegantly delivers its essence. Applications all over the world become more robust and easier to maintain and evolve when a simple interface is put in front of a complex service. The consumer of the service is able to say: This is a lot simpler than allowing the consumer to reach directly under the hood and mess with the engine.
The new normal has changed the way we work and the way we conduct business. More and more employees are working from home, customers are shopping online, and everyone’s phone is still attached to their ears. Bottom line: everything we’re doing in business and in our personal lives is leaving a digital trail. In fact, now devices are getting in the game and creating more data than people, 277 times more, according to Cisco.
DataOps is data management for the AI era. It offers new opportunities for emerging industry leaders by simultaneously instituting agility, improving quality, and increasing production success. Here, I will outline how you can solve some of your biggest data management issues with Lumada solutions, which power some of the top organizations in the world. Let’s first discuss data friction and how to remove it.
Effectively managing data in an edge-to-cloud world is becoming increasingly complex. Enterprises need data management simplicity and agility to maximize the benefits they can get from their data. The enterprise that will succeed will shift resources away from mundane data management tasks to focus on using data to innovate and add business value.
