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Top takeaways from Strata Data Conference

Agim Cura Data quality

This past week I was lucky enough to attend Strata Data Conference. The conference allows big data's most influential business decision makers and strategists to gather in order to share experiences, thoughts, strategies, and products with the goal of positively impacting their business or technology. The event was held at the Javits Center in New York City. Placing the conference in the heart of NYC allows companies from Wall Street and Silicon Alley to attend with relative ease, ensuring all industries are tapping into the opportunity that Strata presents.

While at Strata, I was able to connect with some of the best minds in the data business. As a result, I walked away with increased insight into the current state of the industry and an understanding of key areas in data management where organizations are investing time and money. I’m excited to now share a few of my top takeaways from Strata.

It was interesting to learn that just two years ago the first wave of big data initiatives were focused primarily on business intelligence (BI) and data visualization. Now that organizations understand the importance of having the ability to visualize your data holistically and then being able to make actionable decisions based on this data, there is a new wave of trends concerning big data that businesses are focusing on. Now, we see that businesses are building data initiatives around metadata management, data classification, data cataloguing, and data profiling within a big data platform.

Organizations are also now focusing on finding the balance between a defensive and offensive data strategy. Historically, companies that have implemented a defensive data strategy have acutely focused on minimizing downside risk. What this means is first ensuring your organization is remaining compliant with regulations. Secondly, it refers to leveraging analytics to not only detect, but also to reduce fraud and safeguard the integrity of data collected and stored through standardization and governance of data sources—while looking at the data holistically. In contrast to data defence, an offensive data strategy benefits an organization by positively impacting strategic business goals such as increased revenue, profitability, and customer satisfaction. Depending on the industry an organization is in, they would need to identify the right balance between a defensive versus offensive strategy. For example, the healthcare industry is highly regulated and therefore leans more towards a defensive strategy, however a retailer is less regulated so they are able to utilize an offensive data strategy.

As organizations continue evolving, their data strategy will need to do the same. Data sources, much like applications will come and go, but the data collected will live on in your organization’s database, and if you are not managing it correctly then it will go bad and no longer provide value. This is why whether defensive or offensive, it is important you have a data management strategy that aligns with your organization’s strategic goals and initiatives so your data is fit for purpose and you can maximize its potential.

Does your organization need to improve or build a data management strategy? Check out our white paper to learn a simplified approach to building your data management program.

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