From Overload to Insight: Managing Data in the Age of AI

Facing a growing sea of data, companies are investing in innovative data management strategies to help efficiently extract actionable insights, while maintaining a balance between data accessibility and security.

The world is generating more data all the time, approaching 7 petabytes per second, but not all of that data is valuable. Up to 90% of generated data is simply copies of old data. To ensure that they can identify and utilize the most valuable data available to them, businesses are gearing up to invest around $200 billion in data management and analytics technologies.

Efficient data organization and security strategies can be make-or-break for a company’s growth, as poor data management can cost organizations an estimated $15 million per year in wasted resources and missed opportunities. Navigating the complexities of modern data management requires a nuanced understanding of the tools and practices that can turn this challenge into an opportunity for innovation and efficiency.

Better data organization means better insights

Managing data effectively to improve business strategy is crucial in today’s data-driven world. The first step, according to Julija Šurnienė, Data Platforms Lead at Reiz Tech, an end-to-end IT solutions provider, is for a business to identify the specific goals it wants to achieve through data management and analysis, whether that is improving operational efficiency, enhancing customer experience, or increasing revenue.

“A business will first have to conduct a comprehensive audit of all existing data sources within the organization, including both internal and external sources,” says Šurnienė. “What are the company’s key data assets? What are their types and formats? And, most importantly, what is their relevance to the company’s objectives?”

Cataloging tools are particularly useful at this stage, Šurnienė says. “Data catalogs are tools that use metadata to turn complex data into searchable inventories. This makes spotting trends, patterns, and connections much easier. It’s not just about accessing the data, it’s about making the data say something useful, helping everyone involved make smarter decisions based on clear, tangible insights.”

Create a data democracy

One data management strategy gaining ground lately is known as data democratization. Instead of keeping a business’s data locked away, accessible only to a few gatekeepers in the top ranks, this approach gives all team members access to the data that will help them uncover valuable insights. The ultimate aim of data democratization is to foster a more informed and empowered workplace.

“The first step toward establishing a ‘data democracy’ is identifying the types of data relevant to specific team members’ roles and responsibilities,” Šurnienė says. For example, a sales team might require customer information and sales performance metrics, while marketing personnel would benefit from campaign performance data and competitor analysis. “Data can be used most efficiently when access is tailored to the specific needs of different functions within the company.

Another key to successful data democratization is establishing effective feedback mechanisms. “Input from employees is of extraordinary value, since they know first-hand what data is most useful to their work, and what challenges are preventing them from achieving their goals,” Šurnienė says. Surveys, focus groups, and regular meetings can lead to better data accessibility policies and practices, ensuring that every team member has the information they need to succeed and contribute to the company’s overall success.

Granting access while remaining secure

When organizations grant wider access to data across teams and departments, a critical concern arises: How can security be maintained when data becomes broadly accessible across the company? The solution centers on implementing what is known as data governance and advanced data architectures. This means providing structured access controls and ensuring that sensitive information remains secure while still being accessible to those who need it.

Šurnienė points out, “In the shift towards more accessible data, the key challenge lies in identifying the balance between openness and security, ensuring that we’re only sharing what’s necessary and keeping the rest secure. As data generation continues to explode, maintaining this balance is going to be the key challenge for experts going forward.”