Data Analyst

Data analysts organize and store data, then use it to tell stories that help companies make better decisions. They convert abstract data into easily understandable insights that the rest of the business can use. They are part nerd, part detective, and part storyteller.

Businesses today have metric tons of data—on their customers, their competitors, their market, and their industry. But all that information is useless without people to make sense of it.

Data analysts sift through the mountains of data to decide what’s important, what’s not, and what the important stuff means. Then they present it in a way that less intellectually gifted people can understand.

Data analysts perform tasks such as:

• Cleaning and organizing data

• Identifying trends, diagnosing business problems, and proposing solutions

• Making predictions

• Creating reports, graphs, and dashboards with all of that information

Every business and project is different, so the work is never the same. If you enjoy problem solving and analysis, it can be a very interesting job.

One of the best ways to understand what someone does is through the questions they answer and problems they solve.

The types of questions a data analyst has to answer can be divided into four main categories:

1. What happened in the past? (descriptive analytics)

2. Why did it happen? What caused it? (diagnostic analytics)

3. Based on what happened in the past, what do I think will happen in the future? (predictive analytics)

4. Based on what happened in the past and what I think will happen in the future, what should we be doing right now? (prescriptive analytics)

Here are some examples of real work situations a data analyst would find themselves in. See if you can decide which one of the four types of analysis each example represents.

Example 1: 

You work for an e-commerce company. Last quarter, sales on the West Coast decreased by 15%. The CEO wants to understand why. 

Your boss asks you to find the answer and brief him before his meeting next week.

Example 2: 

You work for a transportation logistics company. The business collects data on load sizes and truck routes. 

You are asked to analyze the data and suggest how the company can more efficiently allocate its trucks to different regions.

You’ll spend a lot of time in Microsoft Excel.

You’ll use interfaces like Microsoft SQL Server, RStudio, and CPython depending on what programming languages you work with.

You’ll make presentations using PowerPoint or Google Slides.

Finally, you’ll use a data visualization software like Tableau. Programs like tableau will allow you to turn all of the brilliant insights you find into easy-to-understand graphs, sleek charts, and sexy dashboards.

You need to be good at analyzing problems and deciding how to solve them. Enjoying math and word problems is usually a good indicator of this.

You need excellent communication skills. You’ll need to take complex ideas or processes and explain them in simple ways to people who don’t share your knowledge.

In addition to these soft skills, there are some specific technical skills you’ll need:

1. Statistics

You need a strong understanding of statistics and how it’s used to understand trends and make predictions. 

2. Microsoft Excel

Most people know how to perform some basic functions in Excel. Data analysts have to be Excel gods. It’s how you’ll organize, study, and present a lot of the data you work with.

3. SQL

Structured query language (SQL) is the programming language that is used to build databases and then talk to them. So you’ll need to speak SQL.

4. R or Python

R is a programming language developed specifically for statistical analysis. It’s used everywhere to manage and analyze data. Python is another programming language that has powerful data modeling capabilities. 

Anything Excel can do, R or Python can do better and 10 times faster, so you need to learn at least one.

Most of your time will be spent at your desk analyzing data for your current project. Or watching cat videos.

When you’re not at your desk, you’ll probably be collaborating with a team member or sitting in a meeting. Occasionally, you may need to give a presentation.

1. The work is interesting and varied.

2. You learn more about your business and industry than almost anyone else.

3. You hone your analytical skills.

4. It’s a good balance of working with people and working with numbers.

5. Your skills are in high demand.

6. After a few years as an analyst, you can take your career in a lot of different directions.

1. Many companies don’t have a good data management system in place, which means a lot of your time will be spent cleaning and organizing data before you can even use it.

2. Managers set arbitrary, unrealistic timelines.

3. Because you make it look easy, managers think it IS easy.

• Bachelor’s degree in a STEM field is generally preferred—computer science, software engineering, information science, or math are all popular majors.

• Many data analysts also get an advanced degree.

• Microsoft Excel

• SQL

• R programming

• Python

• Tableau

• Google Analytics

• Problem solving

• Analytical ability

• Communication skills