What is a Data Science?
To put it simply, a data analyst is someone who uses technical skills to analyze data and report insights.
On a typical day, a data analyst might use SQL skills to pull data from a company database, use programming skills to analyze that data, and then use communication skills to report their results to a larger audience.
It’s a fulfilling job that pays well. Being a data science also provides an experience that can be beneficial for stepping into more advanced roles like data scientist.
1: Data Cleaning and Preparation in Data Science Job
Research shows that data cleaning and preparation accounts for around 80% of the work of data professionals. This makes it perhaps the key skill for anyone serious about getting a job in data.
Commonly, a data analyst will need to retrieve data from one or more sources and prepare the data so it is ready for numerical and categorical analysis. Data cleaning also involves handling missing and inconsistent data that may affect your analysis.
Data cleaning isn’t always considered “sexy”, but preparing data can actually be a lot of fun when treated as a problem-solving exercise. In any case, it’s where most data projects start, so it’s a key skill you’ll need if you’re going to become a data analyst.
2: Data Science Exploration
It might sound funny to list “data analysis” in a list of required data analyst skills. But analysis itself is a specific skill that needs to be mastered.
At its core, data analysis means taking a business question or need and turning it into a data question. Then, you’ll need to transform and analyze data to extract an answer to that question.
Another form of data analysis is exploration. Data exploration is looking to find interesting trends or relationships in the data that could bring value to a business.
Exploration might be guided by an original business question, but it also might be relatively unguided. By looking to find patterns and blips in the data, you may stumble across an opportunity for the business to decrease costs or increase growth!
3: Improve Statistical Knowledge for data Science Job.
A strong foundation in probability and statistics is an important data analyst skill. This knowledge will help guide your analysis and exploration and help you understand the data that you’re working with.
Additionally, understanding stats will help you make sure your analysis is valid and will help you avoid common fallacies and logical errors.
The exact level of statistical knowledge required will vary depending on the demands of your particular role and the data you’re working with. For example, if your company relies on probabilistic analysis, you’ll need a much more rigorous understanding of those areas than you would otherwise.
4: Creating Data Visualizations
Data visualizations make trends and patterns in data easier to understand. Humans are visual creatures, and most people aren’t going to be able to get meaningful insight by looking at a giant spreadsheet of numbers. As a data analyst, you’ll need to be able to create plots and charts to help communicate your data and findings visually.
This means creating clean, visually compelling charts that will help others understand the data. It also means avoiding things that are either difficult to interpret (like pie charts) or can be misleading (like manipulating axis values).
Visualizations can also be an important part of data exploration. Sometimes there are things that you can see visually in the data that can hide when you just look at the numbers.It’s very rare to find data role that doesn’t require data visualization, making it a key data analyst skill.
5: Creating Dashboards and/or Reports
As a data analyst, you’ll need to empower others within your organization to use data to make key decisions. By building dashboards and reports, you’ll be giving others access to important data by removing technical barriers.
This might take the form of a simple chart and table with date filters, all the way up to a large dashboard containing hundreds of data points that are interactive and update automatically.
Job requirements can vary a lot from position to position, but almost every data analyst job is going to involve producing reports on your findings and/or building dashboards to showcase them.
6: Domain Knowledge
Domain knowledge is understanding things that are specific to the particular industry and company that you work for. For example, if you’re working for a company with an online store, you might need to understand the nuances of e-commerce. In contrast, if you’re analyzing data about mechanical systems, you might need to understand those systems and how they work.
Domain knowledge changes from industry to industry, so you may find yourself needing to research and learn quickly. No matter where you work, if you don’t understand what you’re analyzing it’s going to be difficult to do it effectively, making domain knowledge a key data analyst skill.
7: Problem-Solving
As a data analyst, you’re going to run up against problems, bugs, and roadblocks every day. Being able to problem-solve your way out of them is a key skill.
You might need to research a quirk of some software or coding language that you’re using. Your company might have resource constraints that force you to be innovative in how you approach a problem. The data you’re using might be incomplete. Or you might need to perform some “good enough” analysis to meet a looming deadline.
Whatever the circumstances, strong problem-solving skills are going to be an incredible asset for any data analyst.
Other Data Analyst Skills
The exact definition of “data analyst” varies a lot depending on whom you ask, so it’s possible not all of these skills will be required for every data analyst job.
Similarly, there may be skills some companies will require that aren’t on this list. Our focus here was to find the set of skills that most data analyst roles require in order to build the very best data analyst learning paths for our students.
This is certainly something that you can learn on the job, but if you know a specific industry or area you’d like to work in, building as much understanding as you can up front will make you a more attractive job applicant and a more effective employee once you do get the job.