CDW Executive SummIT: How To Ride the Waves of Data

Organizations that implement effective governance and combine data sources can take advantage of powerful insights.

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Matt is an associate editorial director and award-winning content creation leader. He is a regular contributor to the CDW Tech Magazines and frequently writes about data analytics, software, storage and cloud topics.

The waves of data that organizations must navigate are growing in size and power. The amount of data that will be created in 2025 is expected to surpass 181 zettabytes. That’s 181 billion terabytes.

CDW Chair and CEO Christine Leahy compared the massive amounts of data that are being produced to the 100-foot waves created by the unique conditions of the Nazaré Canyon off the coast of Portugal.

“The technological moment we’re in is producing larger waves than we’ve ever seen before,” Leahy said, speaking at the CDW Executive SummIT in Las Vegas.

Organizations that are able to use this data effectively can ride these waves to new heights, but those that fail risk being overwhelmed.

CHECKOUT: CDW's AI research report shares how businesses are adapting to this technology.

Good Data Quality: A Requirement for AI and Analytics Success

“Organizations are sitting on a huge amount of value in their data, and extracting that value is super-critical,” said Russell Fishman, senior director of Field Advocacy and Solutions Technology (FAST) for NetApp.

But to make optimal use of this data, organizations must follow some best practices. One foundational requirement is to ensure that data reaches a high level of quality. As organizations look for ways to apply artificial intelligence to their workflows, the need for data quality is even greater.

“We have insanely high expectations of AI, but we provide it very little with our data,” said Philip Sandoz, business development manager with Genetec.

AI is really a tool that takes data and makes something out of it. But if you don’t have good data, you can’t get there.”

Andy Szanger Director of Strategic Industries, CDW

To improve data quality, organizations should implement effective data governance. By establishing a governance framework of policies and processes to manage their data, organizations can ensure its accuracy, security and consistency.

Automating data governance is an effective way to make sure it is done quickly and accurately while also reducing the burden on human workers. A governance program improves trust in data, enables better decision-making and helps organizations achieve compliance with regulations such as the European Union’s General Data Protection Regulation.

With an effective data governance program in place, organizations can position themselves to take advantage of emerging AI capabilities.

“AI is really a tool that takes data and makes something out of it,” said Andy Szanger, director of strategic industries with CDW. “But if you don’t have good data, you can’t get there.”

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Combining Data Sources for New AI-Driven Insights

Finding the right applications for data analytics is an important step. Organizations have so much data, and AI can offer so many opportunities that organizations should focus on the projects that will bring the greatest ROI.

“There is a challenge in picking out the right wave,” Leahy said. “Being able to identify the right wave is critical, because there are so many of them.”

One way that organizations can find value in their data-driven efforts is to identify key data sources, such as video surveillance systems or customer relationship management tools, and apply analytics to multiple streams. This enables them to glean insights that would not be possible simply by studying a single source. For example, by combining video surveillance and exception-based reporting systems, retailers can conduct their loss prevention investigations much more rapidly.

By identifying these combinations and making sure their data quality is high, organizations can ride the massive waves of data they’re producing. As organizations figure out what combinations provide the most valuable insights, AI will help them make their analyses at scale. Ultimately, it will become an essential tool for analytics success.

“I think it is fair to say that over the next 10 years, AI use is going to be less of an option and more of a requirement,” Sandoz said.

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