Data is everywhere. In our connected world we imprint millions of data points in a single day; everything from what coffee we order to what news sites we read to whom we call. Big data is the term used to describe the volume, velocity, variety, veracity, valence, and value of data points that can be collected, analyzed and reported on.

For example, real-time and historical data can be melded together and a model derived to answer process control questions such as “ If the temperature is increased by 2 degrees Centigrade will the compound increase in durability and strength?” or it can answer questions such as “do cautionary ads on cigarette packages cause people under 25 to not smoke?”

Organizations all over the globe house vast amounts of data on their business, past, present, and planned-future that is not being effectively utilized. There are three forms of data analytics:

1. Descriptive (reporting on the current situation)

2. Predictive (what will happen given certain conditions)

3. Prescriptive (what to do in order to produce a certain outcome).

Most organizations today are using some form of descriptive analytics such as report or dashboards and then trying to draw inferences from them in order to make business decisions. A better way is to apply a predictive model to answer specific questions with data. Using the company data in this method requires developing a data science team and empowering them to break down any silos that exist around the data and make it accessible for analysis. If an organization is able to define a holistic data model where all data science teams can “fish from the same pond” true synergy happens and data becomes an enormous competitive advantage. Not only can private data be added to the pool but public and purchased data sets can also be added deepening and enriching it to produce better answers.

All is not utopia though as having enormous data sets will not yield the results you desire unless the right questions are asked. Business acumen and substantive experience is also needed on a data science team. These individuals help formulate the questions that will drive the business forward and allow the right model to be applied to the data. Data science is both art and science mixed together. At its’ heart is answering questions with data but the key is asking the right questions. A skilful application of data analytics can save money or yield profits.

“To understand where you are going you have to know where you came from”. I believe that data patterns can not only provide a competitive advantage but also enrich the lives of people around the world by revealing insights that can afford humankind a quantum leap towards a better future be it in medicine, prosperity, or peace in our time.

David Shaw is an Associate of nStratagem.  We have a great deal of experience in helping organizations through these issues and challenges. Feel free to view our Case Studies and contact us directly to see how we can help you..

** The views, information, words, concepts or opinions expressed in our blogs, articles and blog articles are solely the opinions of the individual authors and do not necessarily represent those of nStratagem, its employees or its affiliated companies.

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