Data Modernization for the Digital Age

Modernizing your data core is critical to build a truly digital business.

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The unpredictability of today’s business environment has accelerated the need for companies to better manage their data, so getting a better handle on data can have a significant impact on better business decisions.

A modern data architecture enables businesses and IT leaders to consume and interpret information so they can anticipate market changes and improve business outcomes. Achieving actionable insights from corporate data stores is, in many ways, the ultimate competitive advantage.

It’s no small task. The total amount of data organizations across the globe created, captured, and consumed is expected to reach 59 zettabytes this year, according to market researcher Statista.

It’s not just structured data such as documents, spreadsheets, and PDFs; now there are blog posts, videos, and even Twitter posts thrown into the mix. The variety of unstructured data generated is practically eclipsing the amount of structured data. This brings up not only storage challenges, but the challenges of processing those myriad data types.

Modern Data Governance

As corporate data stores continue to grow, the modern business has to develop data retention and governance policies around all that data. How much data will you store? What types of data will you store? How can you best architect your data platform to ensure optimal current and future performances? Every modern business must face these questions head-on.

This makes data modernization an even more pressing task. A modern business must focus on updating and building out the data architecture to modernize the data core. It is important to determine and deploy a framework of data solutions, as well as data privacy and governance methodologies to construct and manage a scalable, modern data platform to gain optimal value, expedite operations, and reduce capital expenditures.

While moving data storage, management, and analytics to the cloud is an urgent component of modernizing the data core, nearly all midsize to large enterprises still operate physical, on-premises data centers, and likely will continue to do so for some time. So how does that fit into the overall strategy? What is the most effective percentage of cloud-based vs. data-center-based storage? These are some of the other strategic considerations organizations must address.

Controlling Costs

Of course, cost always is a factor. Legacy infrastructure costs can be 55% higher than cloud data costs.1 Modernizing the data core can reduce data storage and management costs, and improve data access speeds. Data modernization can enable organizations to quickly capitalize on the benefits of moving to the cloud to deliver analytics and intelligence that inform everything from operations process automation to customer experiences.

Example: A global life-sciences company sought to lower its IT operational costs while providing faster, more flexible access to mammoth amounts of global health data.

In business for more than 100 years, this company had accumulated a vast repository of global human health data, which it relied on to address questions and concerns, respond to legal inquiries, and incorporate in ongoing research. It is a potentially enormous competitive advantage — and a regulatory and compliance necessity.

However, the company did not have the flexibility to use that data the way it wanted, given its legacy mainframe environment, which inhibited rapid access to the data. In a world of data mining and rapid innovation, that posed a time-consuming and expensive operational challenge. It also threatened the company’s viability in the new digital marketplace.

The company partnered with Cognizant to deploy a cloud-based solution using the Cognizant Data Modernization Method based on Amazon Web Services (AWS). Doing this resulted in the following:

  • Reduced mainframe data hosting costs by more than 95%
  • Saved $3.6 million annually by migrating to the cloud
  • Improved data access and retrieval speeds by 50%
  • Provided a unified security model that ensures active data governance

Partner Up

While modernizing data management and analytics tactics may seem overwhelming, expensive, and outside the range of your in-house staff, partnering with a seasoned managed service provider (MSP) can ease the burden. Working with an MSP such as Cognizant to provide cloud-based data modernization services can help consolidate siloed data sources and migrate legacy systems to the cloud.

That adds up to more valuable data strategies, cost savings, and better business outcomes.

For its part, AWS has the most comprehensive, secure, scalable, and cost-effective portfolio of services to build your data lake and analytics solutions. AWS-powered data lakes can handle the scale, agility, and flexibility required to combine different types of data and analytics approaches to gain deeper insights in ways traditional data silos and data warehouses cannot do.

1 https://blogs.gartner.com/marco-meinardi/2018/11/30/public-cloud-cheaper-than-running-your-data-center/

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