Data Modernization

What is Data Modernization?

Data modernization is a multi-step process of transforming access to data to radically improve business intelligence and decision-making. Organizations modernize by shedding data silos and the complexity of legacy systems in favor of a cloud operational model across edge to cloud.

What is data-first modernization?

Data-first modernization is an approach that elevates data as the pre-eminent organizing principle for the business. The entire organization—IT and beyond—focuses on applying the right resources to cultivate, connect, manage, analyze, and act on data wherever it lives. Data-first modernization shifts the focus of digital transformation from infrastructure-centric transformation to data-centric value creation.

Why is data modernization important?

In today's economy, data drives competitive advantage. In a rapidly changing environment, businesses need to move with speed and agility to build new capabilities and get new products and services to market faster. They need data analytics to derive the insights that power innovation and revenue growth. Indeed, research shows that data-first leaders outperform their competitors by a wide margin, bringing out new products and services faster and beating revenue goals more consistently than organizations that are slower to transform.

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What is a data-first modernization approach?

Taking a data-first modernization approach means that a company anchors 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 spread across silos and legacy systems, preventing you from capitalizing on its full value and presenting significant roadblocks to increased profitability.

With a data-first modernization approach, you leave data where it resides and rethink infrastructure so processing and storage occur closer to where analysis and decision-making happen. Your organization gains the efficiency and insights that will help maximize productivity and drive revenue growth. You'll gain 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 reimagining IT infrastructure and services that 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 in the 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 while incorporating compliance, workload, and latency requirements.
  •  Reinforce IT talent: Taking on more effective technologies may require upskilling/reskilling your internal teams along with targeted hiring and partnering with consultants to deliver the competencies needed.
  •  Leverage automation: Simplify and scale workflows by adopting an AIOps 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.

The convergence of AI and data modernization

A data-driven revolution is fueled by AI and data modernization, driving industries and establishing data as a strategic driver for innovation and efficiency.

  • Accelerated insights: AI and data modernization work together to speed decision-making using sophisticated algorithms that evaluate real-time datasets and provide businesses with accurate and timely insights.
  • Dynamic Adaptability: Within updated data infrastructures, machine learning allows AI algorithms to constantly change, making them more sensitive and able to adjust to shifting conditions.
  • Automated Intelligence: As a result of convergence, intelligent automation is created, which simplifies repetitive operations and frees up human resources for strategic endeavors. This is especially beneficial for industries like manufacturing, healthcare, and finance.
  • Industry Revolution: The combination of AI with updated data systems is transforming industries, including manufacturing, healthcare, and finance. This results in new developments in risk management, smart manufacturing, and tailored treatment.
  • Data as Catalyst: This integration uses AI to drive actionable insights and innovation while positioning data as a strategic accelerator. It reshapes industries for a time when data plays a major role in operational efficiency and decision-making.

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 edge, core, and cloud, with cloud data services and workload-optimized solutions that deliver an intuitive cloud experience for every workload across edge to cloud.

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 enables you to speed time to insight by modernizing your workloads — bringing together data and cloud services with AI-driven intelligence and delivering everything as a service across your entire IT estate so you can scale quickly in response to changing demands.