Are You Ready to Become a Data Analyst?

Data analysts enjoy strong career prospects. Do you have the skills required for this role? Let’s find out!

If you enjoy working with data, searching for interesting patterns and valuable insights, you may wonder “Should I become a data analyst?” In this article, I’ll explain what data analysts do and what skills a successful data analyst needs.

What Does a Data Analyst Do?

Data-driven organizations rely on specialists who know how to get value out of data. Data analysts are among these specialists, along with data engineers, data scientists, and business analysts. So, what exactly does a data analyst do?

Data analysts collect and analyze data and then report the valuable insights from this data. To be more specific, data analysts:

• Collect the right kind of data from a variety of sources using SQL, Python, and other tools.
• Clean the data when necessary (i.e. put it into a format that can easily be used and remove any errors).
• Perform data analysis, including exploratory data analysis, data visualization, and data modeling.
• Discover valuable patterns in data and provide insights to guide management’s decision-making.

It is hard to overestimate the role data analysts play in data-driven organizations. With proper data analysis, a business can understand their customers better, improve the targeting of marketing activities, optimize their offers, and much more.

Ultimately, data analysts have an impact on all the strategic decisions a company makes; no wonder this career pays off. In the US, the median salary for an entry-level analyst sits at about $64,000. A data analyst with 9+ years of experience usually gets $96,000 or more.

There is a strong market demand for data analysts. So, if you are excited about working with data, searching for interesting patterns, and reporting valuable insights, a career as a data analyst might be something for you to consider. With that in mind, let’s review the skills that data analysts are usually expected to have.

What Skills Do You Need to Become a Data Analyst?

At this point, a data analyst career may sound very appealing to you. But are you ready to become a data analyst? To succeed in this career, you will need a specific set of skills. Let’s briefly review some of the most crucial ones.

Problem-Solving Skills

Data-driven companies leverage data analysis to solve specific problems like retaining customers, increasing market share, improving logistics, etc. As data analysts assist businesses in solving these and other problems using data, it’s important for them to have a problem-solving mindset.

This implies that, as a data analyst, you are not just playing with data, doing some descriptive statistics, and drawing nice visualizations. If you really want to be valuable to your company, you need to start with a problem and build your data analysis to solve this problem.

For example, let’s say your company is facing increased customer churn (i.e. customers are leaving) and you’re asked to help. You could just do some descriptive statistics about your customers and create a few nice graphs showing customer number dynamics, but this would be of little value to the company. To assist in solving the problem of customer churn, you need to go deeper.

Start by brainstorming possible reasons for customer churn: bad service, high prices, increased competition, etc. Then, you check your hypotheses with data – e.g. does the company have an unusually high number of complaints? Are there any new competitors with attractive price offers? By getting the answers to such questions, you are more likely to find the true cause of the problem and help management solve it.

SQL to Interact with Databases

To get insights from data, you need to get your data first. Companies of all sizes usually store most of their data in relational databases. This includes information on their product stock, sales, customers, suppliers, employees, and more.

You may have heard that there is a data engineer role to take care of relational databases. So is it really necessary for data analysts to learn SQL? Absolutely! Data engineers are mainly focused on building relational databases and complex data pipelines rather than running simple SQL queries to get data out of a database. At the same time, it is important that data analysts are able to interact with a database themselves and do not need to rely on other specialists to get some basic data.

SQL is the main tool for interacting with relational databases, so SQL skills provide data analysts with additional speed and independence. Knowing how to retrieve data directly from an SQL database allows data analysts to respond quickly to varying management requests and add yet more value to the company.

If you are very new to SQL, start your journey with our SQL Basics course. It covers foundational SQL syntax using 129 interactive exercises. If you want to move from simple SQL queries to creating complex, multilevel reports in SQL, check out this SQL Reporting track; it explains how to create different report types over three fully interactive courses. After learning SQL basics, pursuing an associate's degree in information technology can be beneficial for roles in data analysis and management. These programs cover advanced database concepts, including SQL, essential for managing complex data environments.

Python for Data Analysis

Data analysts are not required to have the same programming skills as software engineers or developers. However, knowing how to analyze your data with Python is practically a “must-have” for data analysts these days. You are not expected to know how to develop an application with Python, but you should know how to use Python to clean data, explore and model data, and present information clearly with visualizations and tables. Data analysts are expected to be familiar with the most popular packages created for this kind of task and to use these packages to perform analyses efficiently.

If you are new to data analysis with Python, check out the interactive courses on LearnPython.com. I particularly recommend the Python for Data Science learning track for aspiring data analysts and data scientists.

Statistics

To spot real trends, fluctuations, and causal relationships, you need to be familiar with basic statistical concepts such as significance, hypotheses testing, predictors, response variables, etc. Just building a correlation graph is not enough for understanding the true relationships between variables and all the underlying processes and interactions.

Real-world data is usually very complex. Two variables may correlate without having any causal relationship. And there might be a third variable that has an impact on both of these variables. Sometimes, two factors have a significant impact on the outcome variable only when applied simultaneously. All of these scenarios can be explored and studied using different statistical tools, and it’s crucial for a data analyst to be familiar with them.

Presentation Skills

To have a real impact on management’s decision-making, data analysts should be able to present the results of their data analysis with great clarity and engagement. A good data analyst can read data and tell exciting stories around this data.

At the same time, data analysts should never go beyond data and always allow for several possible interpretations. For example, they can say that the recent spike in the number of leads might be due to the last ad campaign, but seasonal variations could also add to the growth. A more in-depth analysis would show the likely input of both factors.

In any case, data analysts’ reports shouldn’t be overwhelmed with complex statistical terms and redundant graphs. The best data experts are concise, clear, and deliver their message in language that’s understandable to their audience.

Data Visualization Skills

Any data story benefits from meaningful visualizations; they make decision-makers’ lives much easier. The ability to create visually appealing, easy-to-interpret graphs is very important for data analysts. Using different types of visualizations, data analysts can emphasize the importance of the trends and patterns they have identified.

You can use Excel or other dedicated tools to create your graphs and charts. Recently, though, an increasing number of data analysts are choosing Python for data visualization; the programming language allows them to create professional-looking graphs with just a few lines of code. You can start exploring visualizations with Python in our Introduction to Python for Data Science course.

Start by Practicing Your Data Analyst Skills

If you lack some of these data analyst skills, don’t worry. There are many online sources from which you can acquire them – in the comfort of your own home and around your schedule.

Start with learning how to interact with relational databases in our SQL Basics course. It’ll teach you how to extract data from one or more tables, how to aggregate and group your data, and how to combine your query results – all with plenty of practical exercises.

To get even more practice and prepare yourself for real-world job assignments, take our SQL Practice learning track. You’ll be able to practice your SQL and challenge your problem-solving and analytical chops.

If you enjoy being challenged and learning new skills, here are some handy SQL resources to advance your data analyst career:

• Read These 5 Data Analysis Books to Jump-Start Your Career
• 5 Best Online SQL Courses for Business Analysts
• Advanced SQL Courses for Data Analysts – A Complete Review

Thanks for reading, and happy learning!