Data-driven to business insights

Small group of coworkers, happy to be data-driven to new insights
SAS is a Leader in The Forrester Wave™ Enterprise Insight Platforms, Q1 2019

As I previously blogged, data can change your business if you’re willing to both consider new data and reconsider existing data. You also have to recognize that it’s not all about the data. Nor is data the only decision maker. Humanizing data is essential to extracting business insights from data.

"Humanizing" data means all kinds of humans. In other words, data science is not only for data scientists. For example, you can enjoy watching sports without being a professional athlete. And you can appreciate music without being a professional musician. Likewise, you can – and should – learn the basics of data science (especially statistics) even if you're not a professional data scientist. You will still need professional data scientists frequently, but you won't be able to direct them or interpret their findings unless you understand the basics.

Data: Useless without a business context

A conceptual bridge exists between analysis and insight. Analytics must illuminate business conditions because data is useless if you don’t have a business context to interpret it. Insights are what people draw from analytics. Because once we have data and perform an analysis, we have the knowledge to form insights and change our actions or responses accordingly. “When we have data and insight generated by AI at our fingertips,” Sebastien Charrot recently blogged, “it radically changes how we make decisions. Ultimately, analytics helps us make better, more accurate and effective decisions.”

Data-driven businesses are driven by analytical insights, not intuition. And they use technology as an insight platform, especially for empowering nontechnical report builders and business analysts. Through data preparation, business analytics and visualization, leading organizations are data-driven to business insights so that everyone throughout the enterprise can easily collaborate, assess possible outcomes and make better, data-driven decisions. Smarter algorithms and automated analysis can make all of this possible without programming. In turn, accessible insights are delivered in plain, easy-to-understand business terms that anyone can understand.

See what TDWI has to say about operationalizing analytics for business value

About Author

Jim Harris

Blogger-in-Chief at Obsessive-Compulsive Data Quality (OCDQ)

Jim Harris is a recognized data quality thought leader with 25 years of enterprise data management industry experience. Jim is an independent consultant, speaker, and freelance writer. Jim is the Blogger-in-Chief at Obsessive-Compulsive Data Quality, an independent blog offering a vendor-neutral perspective on data quality and its related disciplines, including data governance, master data management, and business intelligence.

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