3 Reasons to Learn Data Analytics

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In today’s data-rich world, whether you’re an entry-level worker or a Fortune 500 executive, a doctor or a programmer, a marketer or a teacher - there’s a benefit to learning how to analyze data. No subject area is immune to getting the data treatment.  

ESPN teams with Five Thirty Eight for regular stats and data analysis so you can understand sports from every angle. Data scientists at OkCupid and CoffeeMeetsBagel build algorithms to help people find love. At the New York Times, data journalists reshape how their readers consume information through data visualizations.

With so much data around us, understanding how to use that data effectively can help you to expand your skill set, critical thinking ability, and career trajectory.

Here are three great reasons why you should pick up some data skills:

1. Develop an analytical mindset.

The most important skill of data analytics is not knowing how to use tools like Python, R, SQL, SAS, or Tableau - it’s knowing how to ask questions.

Asking the right amount and kind of questions, with a healthy understanding of why each one is being asked, is crucial. Here’s an example of how an analyst might approach the seemingly straightforward task of hot dog eating. 

Working with a dataset helps you pick up the knack for asking questions. If you’re running an after-school program, you might ask, “what are the outcomes of our program”? However, if you get your hands on data for that organization, the practice of querying a database will require you to ask additional questions to get more specific and valuable answers. How long does someone have to participate in the program? How do we measure outcomes? Outcomes for everyone in the program or a subset? 

Your original question could become, “How does participating in our program improve reading test scores for students in 4th or 5th grade that have participated for over 3 months”? 

The more questions you ask, the better questions you ask, the closer you can get to answering the questions you’re really curious about: why is it this way and what can we do? For example, why is our program improving or not improving test scores for students in this age group?

And what can we do to make our program better?

2. Drive decision-making across industries and sectors

Data can be used across sectors to understand your customers, forecast demand and manage operations, and develop strategic approaches to human resources, just to name a few.

 Understand your customers: Companies track consumer behavior and create targeted marketing campaigns, campaigns use data to help identify likely voters, and some healthcare providers monitor patient fitness data to provide better services and preventative care messaging. 

Forecast demand and manage operations: Retail stores use data to make their supply chain more efficient, restaurants use data to forecast demand and ensure food doesn’t go to waste, and Uber uses data to ensure there is an adequate match of riders to drivers.

Managing people at work: Sports analysts use data to determine the players they should trade and how to evaluate the efficiency of their team. Google has reinvented traditional human resources with data, using it to identify the traits of most effective managers and how to create a productive environment.

Whatever challenges your organization might face, there is someone out there that has used data to solve it.

3. Learn skills that are in demand everywhere.

There are so many applications of data analytics out there, but not enough “data people”. For some companies, and many non-profits, it’s cost prohibitive to hire a data scientist or analyst because they are so in demand. According to Indeed.com, the average data analyst in Ohio earns $69,567 per year, and the average data scientist in Ohio earns $98,648 per year.

But if current employees can “up-skill” and learn the tools and techniques they need to work with data more effectively, they will become much more valuable.  Training can be an invaluable investment that provides existing staff an opportunity for growth and additional insights into the organization through the lens of data.

These three reasons might be good enough to get you on the data band wagon, but there are many others.  Data’s not going away anytime soon, in fact, there will just be more of it. 


If you’re curious about how you can improve your data skills, check out DigitalC’s Learning Studios Data Analytics Workshop, happening from October 10th to 12th.

The course walks you through the process of data analysis and how to access local data resources. You will learn how to analyze data using Excel and how to visualize data with Tableau. By the end of the three days, you’ll be able to analyze a dataset on your own and create visualizations to show others in your organization.

Questions? Please email kauser.razvi@digitalc.org.