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DataOps for the Data-Driven

Michael Zimmerman Michael Zimmerman
Managing Editor, Insights, Hitachi Vantara

March 16, 2022

Q&A with Manish Jain

The road to the data-driven enterprise is not for the faint of heart. The continuous waves of data pounding into ever-complex hybrid environments only compound the ongoing challenges of management, governance, security, skills, and rising costs, to name a few. But Hitachi Vantara has developed a path forward that combines cloud-ready infrastructure, cloud consulting and managed services to optimize applications for resiliency and performance, and automated DataOps innovations. This holistic approach is designed to establish a protected digital core that stretches from the data center, through the cloud, to the edge. The result is continuous access and availability to the right data at the right time for analysis and insights to accelerate data-driven decision making. Insights Managing Editor, Michael Zimmerman caught up with Manish Jain, Vice President, Product Management, at Hitachi Vantara to better understand the DataOps pillar of the strategy.


Manish Jain

Q1. What role does DataOps play in a data-driven enterprise that people may not understand or consider?

Not only does DataOps play a big role in the data-driven enterprise, but the role is growing more critical as data volumes rise and enterprises expand. That’s because the challenges of data ingest, governance, access, scalability, and security intensify as companies grow their digital footprint to include connected and disconnected silos of on-premises, cloud, and edge computing datastores. In this new world, the agile and automated methodologies of DataOps are key as they provide companies data services like integration, governance, quality, and analytics. In a recent survey conducted by Hitachi Vantara across 600 Chief Data Officers in the U.S. and EMEA, we found that 65% of respondents were actively pursuing new ways to improve the data agility and automation. So DataOps is real and it’s here to stay. With these capabilities in tow, organizations can corral the right data, from the right sources at the right time for analysis and insights to drive strategic decision making.

Q2. How can DataOps be leveraged to support cloud environments?

DataOps and hybrid cloud are intrinsically aligned in so far as data is generated, shared, stored, and analyzed in every corner of the enterprise. In 451 Research’s recent State of DataOps 2022 survey, more than 88% of respondents considered it “critical” to have the ability to deploy their workloads on multiple cloud providers as a part of their strategy. As a result, DataOps processes and technologies need to be able to transcend the datacenter across the cloud, to multiple clouds, and to the edge of the network. Analytics and AI are only as good as the data that fuels them. Incomplete, incorrect, duplicate, dirty, etc., data will result in faulty and erroneous analytic outcomes. Such inaccurate outcomes will skew predictive next steps and lead to problems large and small for an organization. To ensure DataOps supports hybrid cloud environments, companies must ensure their tools are portable and integrated under an open, composable architecture.

Q3. What is Hitachi Vantara doing about it?

We’ve been continually advancing our Lumada DataOps solutions to meet the increasing challenges posed by enterprise expansion. We have done so once again with the updated Lumada DataOps portfolio. This enhanced integrated platform enables organizations to automate the daily tasks of collecting, integrating, governing, and publishing trusted data from across the distributed enterprise. In addition, our new Lumada Industrial DataOps IIoT Core software accelerates IT-OT convergence and industrial data operations by building a fabric for analytic solutions for Industrial customers. Industry leading features include data integration, AI/ML Analytics and application management.

Q4. How do these DataOps innovations work with the other new solutions and services from Hitachi Vantara?

Hitachi Vantara’s history is in data. From the early days of data storage and management to today, where we provide everything from storage to systems, and analytics to AI. The data lifecycle is at the core of what we do and is critical for accelerating data-driven decision making. To do this, however, requires a modernized digital core. We’ve architected a holistic vision for doing just with innovations ranging from advanced systems to services to help companies better process data and workloads across their enterprise. That means our Lumada and Lumada IIoT solutions are aligned and integrated seamlessly with our new CloudOps and Infrastructure Automation Platform services, as well as the new Hitachi Vantara storage and system innovations.

Q5. What’s the main message behind today’s DataOps news?

Our mission is to help customers accelerate data-driven transformations with intelligent DataOps that span the datacenter, edge, and public cloud with ease. In today’s news, we announced new additions to our Lumada DataOps portfolio that allow organizations to create data fabrics that are governed by our enhanced Data Catalog v7.0 for quality and governance improvements. With new updates to our Data Integration, which is powered by Pentaho 9.3 technology, customers can improve productivity, reduce complexity, and increase speed to integrate data across the hybrid cloud. Lastly, we are also launching a new Industrial DataOps portfolio that targets IT/OT convergence and includes ML analytics models for industrial environments unlocking transformational business insights. With advances to the Lumada portfolio, we will enable organizations to collect, manage, govern, and publish trusted information across complex, distributed environments.

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Michael Zimmerman

Michael Zimmerman

Mike is managing editor of thought leadership, including Hitachi Vantara Insights and corporate Newsroom. Before joining the company, he spent +25 years in journalism and communications, working  with edit teams and business leaders to craft stories of import and interest.