Data analytics is a hot topic over the last several years. You see ads all over for learning it and news articles on how companies are using it to be more successful in targeting their customers. But what exactly is data analytics.
That’s what we’re going to find out.
So Much Data
One of the things that there is no shortage of in the world today is data. With all the people connected to the internet on all their devices, we are generating a mind blowing amount of pictures, videos, stories, transactions and other information.
With all this data, how do we even begin to make sense of it?
Companies Have It
Getting all the data is no longer a problem. People are creating the data either by actually inputting their info (like answering questions on a sign up form) or sometimes unknowingly, as companies, government, research facilities, etc. scrape the internet or buy chunks of data.
Some companies and other organizations will offer rewards and incentives to end users or the groups they deal with to get data such as demographics, habits and patterns, product preferences, medications, health issues, relationship status, and an unlimited list of other areas.
Whenever you go online, you have to assume you are generating data.
Making Use of It
The value of your data is that it can tell us the past and therefore, help predict the future.
What have you bought at a certain store over the last twelve months? We could guess by that what you (and everyone else whose data we have) will buy in the next twelve months.
Companies can plan for stocking the products people will want to buy and phase out the things that will just be taking up shelf space.
Data analysis can help governments plan for population increases and make sure they build the roads, sewer systems, and fire stations to support that projected group of people.
Small business owners can figure out which of their products will create the most revenue for the least amount of investment and help them grow their business rather than become a stastic themselves.
Sorting Through All That Data
Like I said earlier, there is no shortage of data. The problem arises when you try to look at it and make sense of it.
In my job, I have hundreds of billions of records, each with lines of data that contain information on people. This data is such an enormous amount of information, it boggles the mind. How do we actually see it in a way that’s useful?
By taking the data and organizing it, cleaning it, sorting it, and filtering it, we can start to see things in it that make sense.
For example, if I’m a small business and have a database of all of my customers. I can pull the data for customers in the last year who have not purchased anything new, but have made at least three purchases from me previous to this year.
I can then send out a coupon for 50% off their next purchase. If I send that coupon to only the customers who fit that criteria, I can increase my ROI (return on investment).
First, I know this group of people likes my products and my company because they have repeatedly bought from me. I am not wasting mailing costs on people who may have never heard of me and may never buy from me.
Second, the coupon provides a incentive to make them an active customer again. I again increase my ROI by only offering the discount to customers who need a gentle reminder, not those who are already still purchasing.
So what is data analytics? it’s that scenario. Making sense of the data you have so that you can see trends, preferences, concerns, and problems. You can predict with extreme confidence before you spend money or effort on a guess.
Who Does the Data Analytics?
So who is it that does the data analytics? Well, this is a good question. There are a few answers.
Data analytics is actually done by people in a variety of fields. It is also done by computers and algorythms.
Some of the people that do data analytics work in programs or languages like SQL, R, SAS, Stata, MATLAB, Python, Tableau, and more.
The people who use these tools use them for a variety reasons, but all of them are used to make use of data that otherwise would be just a jumble of information.
Data analytics can involve lots of people at different steps in the process. Some people gather the data and store it on servers. Some people organize it and deliver it in smaller, more wieldy data subsets. Some people sort it, filter it and present it in a colorful interactive graph.
So, what is data analytics? Good question. It’s a complicted question, but here’s a simple answer.
Data analytics is taking a set of data and organizing it and presenting it in a way that it it useful.
There is so much data out there. It can be overwhelming to try figure out what it all means in it’s raw state.
We need people, tools, and algorythms to make the data useful.
Data analytics is not only th future of information, for some people it’s their future career opportunity.