Data Modernization

What is Data Modernization?

Data modernization is a multi-step process of improving access to information to enable better business intelligence.  Organizations modernize by extracting data from legacy applications and infrastructure and transforming it so it can be used for analysis anywhere that applications live—in the cloud, at the edge, or on-premises

What is data-first modernization?

Data-first modernization is when IT leaders prioritize data management and take on all that goes with it, not only to keep pace with changing business requirements, but also to move faster than their competition. Forerunners in digital transformation focus on simplifying infrastructure and gaining a more efficient way to view and manage data by creating a cloud operational experience.

Why is data modernization important?

Simply put, data drives competitive advantage, and in a rapidly changing environment, businesses need to respond with speed and agility to build new capabilities. That requires using innovative technologies and industrializing data and analytics to gain insights that drive revenue growth. In fact, research shows that data-first leaders outperform their competitors by a wide margin, bringing new products and services to market faster and beating revenue goals more consistently than laggards.

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What is a data-first modernization approach?

Taking a data-first modernization approach means that a company is founding their business strategy on data—determining what data is business-critical, where is it used, and how to make the most of it—to gain competitive advantage.

As your organization’s most valuable asset, developing a strategy with data as the primary focus is essential. Without a proper modernization strategy, your data will remain sprawled across silos and legacy systems, preventing you from capitalizing on its full value and presenting significant roadblocks to increased profitability.

But if you leave data where it resides and rethink infrastructure so processing and storing can happen closer to where analysis and decision-making happens, your organization can gain both efficiency and greater insights that will help you maximize productivity and drive revenue growth. That means creating a cloud operational experience so you can simplify data management with on-demand access, as well as automated data protection and workload placement.

When data is accessible everywhere from edge to cloud, your organization can centralize operations and revamp IT services, delivering capabilities as a service to reduce costs and gain efficiencies. And with simplified data access, you can automate analytics workflows, integrate AI, and scale quickly and intelligently, which reduces management overhead and optimizes performance and agility.

How do you develop a data-first strategy?

Getting to a data-first strategy requires a reimagined IT infrastructure and services that are designed to deliver the flexibility and agility of cloud. Below are the steps that will keep you on course.

  • Determine business goals: To modernize and get the most out of your data, you need to start with your business goals, which all stakeholders have agreed upon, and align every aspect of data management around those.
  • Coordinate data: An intelligent and frictionless data environment begins with identifying where data exists—whether in a data center, at the edge, or on cloud—and coordinating all management activities (i.e., storage, governance, and security) with a unified view from edge to cloud.
  • Map services: Finding the right modernization strategy will involve mapping applications to business services, incorporating compliance, workload, and latency requirements.
  • Reinforce IT talent: Taking on more effective technologies may require upskilling/reskilling your internal employees along with targeted hiring and partnering with consultants to deliver the competencies needed.
  • Leverage automation: Simplify and scale workflows by adopting an ML Ops process, which will accelerate intelligent app deployment across hybrid environments.
  • Enlist support: True transformation requires buy-in across every level of the enterprise, with key stakeholders helping to drive organizational change.
  • Build in flexibility: Make sure that you have room for continuous improvement and growth as you adapt to changing business needs.

HPE and data modernization

HPE has decades of experience working with global organizations to build modern data management strategies and solutions. The HPE portfolio spans on-premises to cloud-enabled, end-to-end intelligent and workload-optimized solutions to help you make sense of your data and unlock business value faster.

As the #1 provider for SAP Hana® and Microsoft SQL Servers, we have more than 15,000 data management and analysis experts to help you achieve the flexibility and agility you need for data-driven business success. We can help you simplify your data management and transition to a cloud operational experience everywhere so you can seamlessly power apps and data across your environment. With the right data platform and expertise, you can transform the way you manage data.

The HPE GreenLake edge-to-cloud platform provides a foundation for unified data management so you can accelerate your data-first modernization. The platform provides seamless access to your data no matter where it resides, and automates enterprise-grade controls to consolidate security policies across your entire hybrid/multi-cloud landscape. With a unique cloud-native architecture, the platform allows you to speed time-to-insights by modernizing your workloads, using ML Ops to automate and industrialize AI/ML at scale. And it brings together the data and cloud infrastructure services with AI-driven intelligence, delivering it all as a service across your entire IT estate so you can scale quickly in response to changing demands.