What is a data analyst?

A data analyst is a person who analyzes data and provides insights using technical expertise.

 

A data analyst may employ the following skills on a regular day:

 

• Data extraction from a database using SQL

• Knowledge of programming to analyze that data

• The ability to effectively communicate results

 

But which abilities are crucial to getting a job in data analysis? We spent many hours conducting interviews with recruiting managers, data scientists, and analysts to get the answer to that question.

What Qualifications Do Data Analysts Require?

We learned to put more emphasis on skills than technologies because the data science tools you will employ differ based on the function, the company, or the industry (like Python, R, SQL, Excel, Tableau, Power BI, etc.).

 

The top eight skills for data analysts are:

 

• Cleaning and preparing data

• Data exploration and analysis

• Statistical expertise

• Designing data visualizations

• Making reports and dashboards

• Communicating and writing

• Domain expertise

• Finding solutions

 

Let's go over each of these in more detail:

 

1. Cleaning and preparing data:

 

According to research, most data professionals will spend roughly 80% of their time cleaning and preparing data. Thus, this ability is essential.

Retrieving data from one or more sources and preparing it for the category and numerical analysis are frequent tasks for a data analyst. Resolving missing and inconsistent data that might affect analysis is another aspect of data cleansing.

 

Data cleaning is only sometimes enjoyable, but preparing data can be exciting and difficult if approached as a problem-solving exercise. Refer to the data analytics course to learn more about the data cleansing process. 

1. Data exploration and analysis:

Although including "data analysis" in a list of critical data analyst abilities may seem odd, analysis as a specialized ability is required. In its most basic form, data analysis entails taking a business query or a requirement and researching pertinent data to create an answer. 

 

The exploration of data is another type of analysis. Data exploration is the practice of looking for interesting patterns or relationships in data that may have commercial value.

An exploratory process could be primarily unguided or guided by a business question. By looking for trends in the data, you can find a solution for the organization to reduce expenses or increase sales.

1. Statistical expertise:

Statistics and probability are crucial data analyst abilities. This information will direct your investigation and exploration and aid in interpreting the data.

Understanding statistics will also help you confirm the validity of your analysis and prevent frequent logical fallacies and mistakes.

Depending on the requirements of your specific profession and the data you're dealing with, a different level of statistical knowledge may be required.

1. Designing data visualizations:

 

Clear trends and patterns in data are produced by data visualization because most people understand charts and graphs more rapidly than they do spreadsheets. After all, humans are visual organisms.

 

Create simple, appealing charts to help others understand your findings.It also requires avoiding false or difficult-to-read components, such as pie charts (like manipulating axis values).

 

Consider incorporating graphics into your data analysis. Sometimes data contains prominent features upon visual inspection but may be obscured if you only glance at the numbers.

1. Making reports and dashboards:

You'll need to enable people to use data to make crucial decisions as a data analyst. You can remove technical obstacles from others' access to crucial data by creating dashboards and reports.

 

A sophisticated dashboard with hundreds of interactive data points might be used instead of a detailed chart and table with date filters.

Depending on the position, job descriptions and criteria may differ, but practically all data analyst jobs entail writing reports about your findings or creating dashboards to present them.

1. Communicating and writing:

Another crucial data analyst skill is the capacity to communicate in many formats. You can succeed in any data analytics field by improving your speaking, writing, listening, and explaining communication abilities.

 

Collaboration with coworkers requires effective communication. For instance, having attentive listening skills will help you comprehend the analyses needed at a kickoff meeting with business stakeholders.

 

Similarly to this, you might have to impart sophisticated information to non-technical teammates during a project.

1. Domain expertise:

It is known as domain knowledge to understand subjects that are particular to the business you work for and its industry.

 

For instance, you need to be conversant with the complexity of e-commerce if you work for a company that operates an online store. On the other hand, if you're analyzing data regarding those particular mechanical systems, you need to be conversant with how they work.

 

No matter where you work, finishing your tasks will be more challenging if you don't understand the data you're looking at.

1. Finding solutions:

Here are a few possible outcomes:

 

• You might need to research a bug in your programming language or program.

 

• Your company's resource limitations may force you to think creatively about how to tackle challenges.

 

• You could be using insufficient data.

 

• In order to achieve a pressing deadline, you might need to conduct some "good enough" analysis.

 

How to Obtain a Job as a Data Analyst?

Check out Learnbay’s engaging online data science course with placement if you want to develop the technical skill set required to land a job as a data analyst. You will directly write actual code in your browser to evaluate data from the real world. You will learn the material quickly, remember it, and gain confidence thanks to Learnbay’s project-based learning approach.

Publication: 31/10/2022 10:31