But two-dimensional tables of data are not very amenable to learning the mind tends to gloss over a large amount of it, scan for highest and lowest values, and miss the details in between. The data itself isn’t changed by data viz further analysis isn’t done. And it can provide a clearer picture of the business conditions that are of greatest concern to decision-makers.īut analytics does not do what data visualization can do: help to communicate and explain that picture with precision and brevity while in a format that the brain consumes exceedingly quickly. More precisely, it helps them become cognizant of the performance metrics within the collected data that are most impactful to the business. Data analytics helps businesses understand the data they have collected. The reason data analytics is limited might be simple enough. Those tools are data visualization tools. Additional tools are needed to help extract more timely, more nuanced, and more interactive insights than data analysis alone can provide. Depending upon the level of detail that stakeholders need to draw actionable conclusions, as well as the need to interact with or drill-down into the data, traditional data analytics might not be sufficient for businesses to excel in today’s competitive marketplace. Endless columns and rows of alphanumeric data can be difficult to digest at scale. Analytics can be prescriptive, predictive, diagnostic, and/or descriptive to produce insights, observe trends, compare metrics, and more.īut it can only do so much. But, once obtained, what tools will give decision-makers the best insights, conclusions, and results to steer with? What should a business do to reap the greatest value from the masses of data they’re collecting? Data Analytics or Data Visualization?ĭata analytics has proven its worth time and again by helping businesses examine structured and unstructured datasets and extract useful information so key stakeholders can make more-informed and more effective decisions. For reasons of practicality and efficiency, it is best for all of these solutions to be tied into a single BI tool to deliver the most accurate, complete, and broad picture of the performance of the business. Recognizing this, more and more business intelligence (BI) solutions are emerging that collect all varieties of data, reach across numerous departments, and serve a multitude of purposes. The “bigger” the data, the more true this comes. Said another way, the value of business data isn’t in each bit, byte, or field, but in the results and insights that can be gleaned from the relationships between data points.

While it’s now touted as one of an organization’s most valuable assets, data alone is worthless without supporting technologies to mine it, process it, organize it, and analyze it.

Best data visualization tools 2018