A guide to data modernization

  • 28 March 2022
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This content, written by Joel McKelvey, was initially posted in Looker Blog on Dec 7, 2020. The content is subject to limited support.

Today’s workforce needs data they can use to make better business decisions — and make them quickly. But technology currently deployed within organizations often struggles to keep up with growing data demands, and as a result, companies face increased pressure to modernize how they collect, analyze, and use data.

What does data modernization mean?

This is a pivotal point in our march toward building a flexible, scalable, modern data stack — in realizing . We need to examine the bigger truth surrounding data, which is that legacy data tools simply lack the ability to solve modern data problems. The traditional data stack has too many steps, too many tools, and too many integrations, all of which lead to operational complexity, time delays, and high cost.

Why data modernization is so important for organizations

Data modernization strategy has become a top priority for organizations because achieving it means they can deliver ideal data experiences that offer valuable, actionable insights, API-driven application integrations, and respond to the real-time needs of a dynamic business environment.

Common challenges in data modernization

A recent lays out the need for businesses to modernize the data stack in order to transform data experiences for everyone within their organizations. ESG surveyed companies about their top challenges with their enterprise data warehouses. Overwhelmingly, organizations said performance was the biggest challenge, with current data warehouses only handling a subset of their structured data. In an attempt to fix this problem, companies would dedicate additional compute and storage resources, which are expensive, complex endeavors because of the proprietary nature and licensing structure of enterprise data warehouses (EDW). After this solution was applied, new issues would arise from workloads being run on an EDW that simply wasn’t designed for that type of function.

Growing trends in data modernization

A real fix to the problem is for organizations to modernize their data warehouse to enable data-rich experiences that transform their entire operation. There are many benefits to this approach, including:

  • Scaling to meet growing analytics needs, with users focused on analytics instead of worrying about database operations, like migration and data staging before conducting analysis.
  • Integrating new data sources to use data at any scale, with a focus on rising data volumes as well as the use of multiple data sources.
  • Reducing time to insight with fewer delays, giving users the ability to quickly find value in data, as well as ingest streaming data to analyze events as they unfold.
  • Democratizing access with data stored in one place for every business function, thereby empowering data analysts to run analytics without acquiring new skills.
  • Planning for the future and using a modern EDW as a launch pad for more advanced types of analytics, such as artificial intelligence and machine learning.

Modern analytics for modern business problems

For more and more workers, there is a continued focus on accessing and using data openly and transparently for business insights. With a simplified, modern data warehouse, resources are made available to help data teams deliver more value to the workforce they support. Today’s workforce expects information to be readily available to everyone from non-data specialists to data scientists and generalists.

Today, organizations want to empower their workers with the ability to perform near real-time data analytics without the hassle of infrastructure management. Businesses want these data-driven thinkers to have access to all the data they need by delivering data to all jobs and tasks regardless of where people sit within the organization.

Learn how to modernize your data stack: Read the whitepaper

At Looker, our goal is to help companies deliver modern data experiences through a modern data platform. We do that by aligning with organizations’ data-centric goals, and providing users access to all their data so they can make rapid, data-driven decisions. Regardless of whether your organization needs to modernize your database, embrace multicloud architecture, or advance analytics initiatives, we can help you derive better insights and make data-driven decisions at the speed of your business. More of your end users become empowered through an advanced self-service BI architecture, with reliable, fast access to more trusted data.

We want to help you realize the potential of what data can do for your organization by giving you options to work with data in more ways, at whatever stage you are at in the data analytics maturity lifecycle. Most importantly, your company gains a powerful data analytics experience regardless of the type, size, speed, rate, or location of your data.

Find out how Looker can help your organization with modern data tools to solve modern data problems by downloading the ESG white paper, today.

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