Data and Automation: Drivers of the Future Enterprise

By Kriti Adlakha posted 11-26-2019 17:15

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Guest Contributor: Richard L. Villars, Vice President, Datacenter & Cloud, IDC

To get to the heart of the digital economy, look no further than data. The IT organization as the driver of DataOps will play a critical role in how enterprises handle data — its generation, delivery, concentration, and exploration. DataOps is at the heart of connecting with customers in new ways, developing new revenue sources, and improving business operational efficiency. Don't think of DataOps as a product; it's really a discipline designed to connect the consumers of data with the creators of data. In the process of doing so, DataOps enables collaboration and accelerates innovation. An effective DataOps discipline enables collaborative data management across the organization that in turn leads to better communication, integration, and automation of data.
With lives and businesses increasingly digitized, more data is inevitably created. By IDC estimates, 102.6 ZettaBytes (a Zettabyte is 1,000,000 PetaBytes) of new data will be created worldwide by 2023 – a big jump from the 32.6ZB of data created in 2018. More data is not just being created – new data and existing data is being leveraged in new and exciting ways.

The demands of gathering, protecting, and leveraging more diverse data is a challenge for today's IT organizations. In a recent IDC survey on the challenges of managing technology from cloud to core to edge, senior IT and operations technology leaders cited issues related to data security/compliance, data performance, data movement and data visibility as major concerns.

Those IT organizations that want to survive and thrive in the digital economy must focus on data. Indeed, the most successful IT organizations will be noted for their ability to make it easy to create, move, analyze, deliver, retain, and secure any and all data required by the organization.
That's where automation comes in.

Automation is a foundation for accelerating innovation. A successful shift to a digital business model requires well planned and orchestrated implementation of existing and new services. The threat of disruption due to poor planning or orchestration is particularly strong for organizations that were neither early cloud adopters nor "born-in-the-cloud." The challenges of integration, testing, training and change management are important to address as time is of the essence. Many organizations lack the expertise and resources to execute complex application migrations, updates and launches with the speed and consistency that are necessary for a sustainable and scalable digital services model.

As industries shift to agile and cloud-based application development and delivery practices associated with DevOps and now DataOps, professional services partners typically develop best practices that emerged in early cloud efforts and use them to help late adopters embark upon their digital transformation journey. This effort includes establishing data architectures, process flows and governance models that drive desired outcomes.
In the digital economy, it's important to understand that the journey does not end with initial implementation. On the contrary, the journey is never ending in terms of application cycles and continuous application/technology innovation. Even if organizations start with industry best practices, they eventually must create their own practices, unique to their business needs, to deal with continuous updates of existing software and data sources. In addition, organizations must develop new software in hybrid environments that involves a growing range of cloud infrastructure, applications and data services in many different locations. Reengaging a services partner for a project every time there is a software update or need to incorporate new technology into a service isn't practical – it's just too expensive and inefficient to be scalable.

Infusing AI-enhanced automation into integration and testing processes will be key to overcoming implementation skill gaps and accelerate time to market for new products and services. Automation is also critical for reducing undue reliance on experts. Instead of manual integration and testing services, where the quality of results can depend heavily upon access to skilled practitioners, these new integration methods and tools automate many of the more repetitive tasks, while ensuring ongoing consistency and governance across applications.

In these ways, the success of the future enterprise will be defined by data, powered by automation and driven by DataOps.

For more information we invite you to read the white paper : Accelerating Digital Innovation with DataOps, Cloud, and Automation, sponsored by Hitachi.
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As Vice President, Datacenter & Cloud, Richard Villars is a senior member of IDC's IT Infrastructure research team, which assesses the development and adoption of solutions for datacenter transformation and exploitation of rapidly evolving technologies in the areas of Big Data and Cloud. He develops IDC's viewpoints on the evolution of converged IT infrastructure as well as the adoption of public and private cloud solutions. He advises clients on the impact of open systems, software and network efforts on organizations' infrastructure, deployment, procurement, and management practices.

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