Big Data has completely revolutionized every aspect of business and finance. Executives, managers and specialists have a world of information, statistics and data at their fingertips at all times, and can use this data to make informed decisions that will positively impact their company. Depending on the industry, size of the company and other factors, the amount of information needed and utilized is astounding to the average consumer or an employee.
This is one of the reasons why data scientist has been ranked number one on Glassdoor’s annual 50 Best Jobs in America list for three years in a row. Additionally, data engineer ranks third on the list this year, and it is clear there is a promising future for anyone looking to start a career in Big Data.
But once the executives, managers and specialists have compiled and analyzed this data and utilized it to whatever ends are necessary, what happens to these oceans of data once they are done with it? It seems like a complete waste to compile a nearly incomprehensible amount of statistics and information, analyze the data once and then essentially put it away until it may be needed sometime in the future.
Beyond the temporary needs of executives and managers, this same information could be used to make potentially groundbreaking decisions at every level of a company. But before it can be utilized beyond its initial intention, the data must be simplified so that those who are unfamiliar with data analysis can understand it and make informed decisions based on it.
Until relatively recently, no one had ever heard of a data scientist, and the term Big Data did not exist in any vocabulary. In fact, data science– as a term and as a discipline– has only been in existence for just over 15 years. It was William S. Cleveland, a statistics professor at Purdue University, who coined the term in 2001 when he argued that computer science and statistics could be merged into one field.
It appears as though Cleveland may have been onto something, and now there are no major decisions made by any corporation without a thorough examination of large amounts of data. It influences every aspect of a company from the top down, and it could be utilized beyond the very top.
While data can be used at every level of a business, it would probably be useless to hand down mounds of data that has not been properly summarized and put into an easily consumable form. So the first step in presenting your data will be to summarize it into a form which best tells the story of the data and gets the point across.
The overall goal of this step is to compile the data into a picture that can accurately demonstrate the meaning of statistics, and the most important thing you can do is to visualize the data throughout every step of the way. Proper visualization will show you– right from the start– whether the data is grouped together, spread around, trending one way or another, or if it is clustered around one central point. It also helps you notice any outliers (unusually high or low data points) quickly.
The best way to summarize your data into a presentable form is through the use of graphs. Bar graphs, or histograms, are the most common and popular techniques for presenting data in a form that is easy to understand. Another option is a line graph, which plots each data point and joins them with a line. Pie charts are a valuable option when comparing the relative size of each group and what proportion fits into each category.
The way the data is used depends on countless factors such as your industry, company, needs and the data itself. It may be used to improve virtual office software or to create more efficient warehousing techniques. The most important thing is to get the most out of the data, by allowing all members of your company to see and understand it, and utilizing it at every level of the business.