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Home > The Essentials of Data-First Modernization

The Top 5 Imperatives of Data-First Modernization

If your enterprise is like most, you are confronting a series of business-critical data challenges and data opportunities. Some of the challenges might be around freeing data trapped in silos, getting data at the edge under control and applying intelligence to all of your data. On the other hand, one of the main opportunities is to transform data into a core asset that drives customer engagement, decision-making and business innovation.

Data-first modernization provides a path to both mitigate the data challenges and maximize the data opportunities. Data-first modernization lets you unlock trapped legacy data and capture the value of all data from edge to data center to cloud. It enables your organization to leverage analytics and intelligence to fast-forward your digital transformation initiatives to deliver rich experiences and accelerate decision velocity.

See related article: The Business Case for Data-First Modernization: What It Is, Why It’s Necessary, How to Get Started.

This article examines five imperatives for transforming into a data-first organization, empowered by an edge-to-cloud enterprise IT platform that facilitates the shift to data-first modernization.

No. 1: Data is a core asset that must be controlled, everywhere it lives. In most organizations, data remains spread in silos across a sprawl of multigenerational IT infrastructures and applications. This means the value of the data is trapped in those silos, limiting the ability of the organization to fully leverage it as an asset that drives business efficiencies, competitive advantage and improved customer and employee experiences. One of the prime goals of data-first modernization is to eliminate legacy silos and avoid creating new silos as more applications and workloads migrate to the cloud and edge.

No. 2: Data is everywhere and must be accessible at the speed of business. Not only is it imperative to control the data everywhere it lives; it is also necessary to make sure it can be accessed and used at digital speed. Trapped data is a disadvantage; movement must be frictionless. Acting on data where it is created—predominantly at the edge—leads to faster and more efficient results. It is also important to take into account the reality that the native location of data changes over time, so having a platform that seamlessly manages data from edge to cloud is essential.

No. 3: Data has rights and sovereignty that must be protected. Data must be governed, managed and protected with full integrity to be compliant. A data-first modernization path enables organizations to mature beyond a basic awareness and definition of data requirements, to a more refined model that incorporates corporate risk management, regulatory and reporting mandates, and compliance frameworks. Automation is a critical element in managing approval, auditing and enforcement of data sovereignty and compliance.

No. 4: Organizations must industrialize their data supply chains. The concept of a data supply chain is an innovative approach for today’s environments, supporting the  movement of data fluidly—and securely—everywhere across the enterprise and its broader ecosystem. Just as modern supply chains are industrialized, so too should data supply chains. With a data-first modernization approach, organizations can adopt a “cloud everywhere” model. This means being able to choose the right location for your data and workloads, so you can keep control over which data should be in the public cloud and which should not.

No. 5: Data in multiple, disparate operating models must be unified. Digital engagement of customers and the workforce is where value is created, connecting the physical world to the digital world. Data provides the insight and control necessary to do this. Yet, data is of limited value if it is not unified and available. Data needs to be cleansed, reconciled, integrated and shared. Driving one integrated model—regardless of the physical location of the data—delivers insights, business agility and outcomes. That requires a comprehensive data management platform that can accelerate business insights by operationalizing data and making it easier to exploit.

Taking the Next Step
Thousands of enterprises around the world are discovering that they can accelerate data-first modernization by bringing the cloud to their distributed apps and data where they are. With the HPE GreenLake edge-to-cloud platform, HPE delivers a cloud model—self-service, pay as you go, scalable and managed for you—via an enterprise platform at your edge or in your colocation facility or data center, so you don’t need to sacrifice performance, data sovereignty, flexibility, scalability or economics. For more information, please review the additional articles and resources on this site and visit HPE GreenLake.

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