
We all know becoming a real expert takes years of hard work and dedication. People say the ability to teach a subject leads to real mastery, yet although we value highly skilled teachers, businesses do not have time, resources or patience to pour into any one individual’s growth. We still demand the highest level of expertise in consultations, but faster and cheaper.
Data experts, “data scientists,” used to be hard to find because of the time it took to truly master the art of data analysis. Years of schooling and training in statistics are necessary to make full sense of complex and growing data. When a business asks for advice based on data, scientists must put learned information into context by taking into account industry, geography, and the specific market dynamics. With so many moving parts to consider, relying on only a few “experts” can be painstakingly time-consuming, and costly. [Read more...]
Whether it’s infographics, maps, flow charts, or other design-driven diagrams, data visualization is now seen as the preferred way to interact with data. In fact, infographics and other visualizations have been some of the most shared images in social media history. Why? They’re easy to understand, quick, and beautiful. They engage.
People do not often think of data points as having dire consequences, but it could mean the life and death of a business. In every realm of business and sector of life from politics, economics, society, the environment, to technology, there are big data complications. Without the blend of analytics and integration solutions, there are growing risks of security threats, need for efficiency and cost reductions, and a desire for more collaboration. Big data is not just big because companies and organizations collect large volumes of it, but also because it has real and lasting implications on everyone.
I frequently discuss big data with executives from some of the largest Fortune 500 companies in the US. I continually act as a sounding board for their frustration as they try to extract value from historical big data. There is a prevalent misbelief among them that there is a great deal of value in years and countless rows of data, but they struggle to monetize this hidden value, and for good reason.







