Data / DevOps / Machine Learning / Sponsored / Contributed

5 Data Services That IT Leaders Need to Master and Deliver

19 Oct 2021 6:30am, by

Murli Thirumale
Murli is general manager of Pure Storage's Cloud Native Business Unit - Portworx, where he is responsible for strategy, operations and solutions that deliver multicloud data services for Kubernetes. He holds an MBA from Northwestern’s Kellogg Graduate School of Management, where he was an F.C. Austin Distinguished Scholar.

Winning with data is one of the hottest topics in business right now, but what does that mean, exactly?

Modern enterprises require infrastructure that supports rapid application development and deployment, and which lays a foundation for automation, self-service provisioning and ubiquitous data access. That’s important because it is the path to moving fast and moving smart with data, both of which are essential to today’s business market.

For the CIO, it’s key to provide data services that make it easy for DevOps teams, data scientists and line-of-business users to access, explore and mine data for a variety of enterprise applications and uses. If CIOs aren’t providing ubiquitous data as-a-service three years from now, they won’t be a CIO for much longer.

But thinking about the word “data” as an umbrella term is not very useful. You must double-click on the idea of “data” in the same way you would for “infrastructure” to create strategies for your network, compute or storage.

A Deeper Dive

Most modern businesses are already on their way to a cloudified infrastructure that enables the organization to be responsive to changing demands. In a world now largely driven by apps (think Oracle and SAP), the next frontier for all businesses is making data widely available and easy to use for employees and customers.

Innovators are beginning to recognize that the way to win with data is to feed apps with the best data possible. The action has moved from merely having an app to having the best data for that app. What is really magical is when you can conflate your company’s proprietary data with the world’s data to drive insights that can fuel a big jump forward for your company. Esri, a location intelligence SaaS provider, is an example of a company that does just that. It uses containers and Kubernetes to deliver its service to customers with massive data needs for integrating mapping information for applications like COVID-19 tracking, fire mapping and disaster management.

5 Key Pipelines

CIOs must provide data services to support application development, machine learning projects, data exploration and other advanced data needs. To my mind, there are five key “as-a-service” pipelines that apps access, comprising a comprehensive service catalog. Each should give users a one-click data pipeline delivered as a service that they can easily access so they can focus on what matters – their application – rather than standing up and managing infrastructure. The five pipelines are:

  1. Database as a service to provide scalable data repositories that are available across teams and applications.
  2. Data search as a service for ad hoc queries to understand usage and improve products.
  3. Analytics as a service for business intelligence, using tools such as Tableau or even Excel.
  4. ML/AI as a service to provide intelligent, personalized services and to understand usage patterns that tap into massive amounts of data using different tools, like TensorFlow.
  5. Streaming data and messaging as a service to support apps that depend on real-time data to deliver information to consumers or to operate machines because data is now distributed (it’s on the edge).

Open source databases like MySQL, MongoDB, Cassandra, PostgreSQL and many others have gained wide adoption, and they are key to enabling and delivering this data services catalog. CIOs are investing in them, in the billions of dollars, worldwide.

Summary

The action has moved from being responsive and inexpensive, to being fast and smart. But fast and smart isn’t just about apps; it’s about apps and data. Kubernetes and containers are your path to fast; your path to smart is ML/AI and new as-a-service tools.

For the past decade, the world has been inundated with apps. Now is the time to pay that same level of attention to data.

Lead image via Pexels.