Data Analyst Roles, Responsibilities and Skills Required

Data analysts help organizations derive valuable insights from collective information. They clean and organize data, find patterns, and create visuals to explain notable findings simply. Analysts work with different departments to ensure data quality and security. Their goal is to turn numbers into actions through analysis for better decision-making. Let’s discuss the various roles and responsibilities data analysts take on to extract meaningful insights from information.

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What is the work of a Data Analyst in the industry?

Every device or technology we use generates data every second. There is an estimate that the total amount of data generated all around the world every day is 2.5 quintillion bytes. With this much amount of data, companies can generate business value worth billions of dollars. For this, companies hire Data Analysts to give value to the business and accordingly Data Analyst roles and responsibilities vary.

However, Data Analysts’ roles and responsibilities depend on the type of company they are working for. If it is an e-commerce company, then the data collected would include its customers’ previous purchase data, interest in products, reviews given for products, and more. For pharmaceutical companies, the important information would be patient data, data regarding the demand and supply of drugs, responses from doctors on drugs, and more. A Data Analyst explores and analyzes all varieties of data. They prepare data for Data Scientists to build smart and automated systems.

Let us look at the below diagram to understand the role of a Data Analyst:

Data Analysts search and extract relevant data for their organizations. After extracting data, they perform exploratory data analysis to understand it and make it in a structured form for Data Scientists to build Machine Learning models.

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Use Case: Analysis of Data in the Healthcare Sector

Healthcare is one of the sectors highly benefitted by data analysis methodologies. Patients’ data generated by medical organizations are in quintillion bytes. To utilize such huge amounts of data, they need to convert the raw data into a properly structured form to understand it efficiently. Here comes the role of Data Analysts.

Confused about cleansing the data set? Check out our blog on Data Extraction.

Data Analyst’s responsibilities are the extraction of the data from data warehouses and preparing it for analysis. At first, the extracted data is in the raw form, on which operations such as manipulation and visualization will yield inconsistent results. To make the data structured, Data Analysts perform various techniques to make it ready for use. You can see the below image that shows the form of well-organized and structured data.

Below are a few of the Data Analysts roles and responsibilities to convert data into a structured form:

Classifying data as per rows and columns
Removing redundant and non-essential rows and columns
Eliminating null values
Categorizing the values of columns according to data types (e.g., male, female, true, false, etc.)
Converting the data into a readable format

Once the data is ready, it is given to Data Scientists for manipulation, visualization, and predictive analytics. The analysis of data by data scientists in the healthcare sector helps gather information related to drug requirements, ventilators, and other facilities. It also helps manage doctors’ availability, vacant rooms, emergency wards, and more. Automated systems built using healthcare data enhance the healthcare management system. Finally, any creation of automation technology starts from the data analysis and preparation performed by a Data Analyst. Thus, Data Analyst roles and responsibilities help the organization in business analysis.

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Roles and Responsibilities of a Data Analyst

We have already discussed the Data Analyst roles and responsibilities with a practical use case. In this section, we will look at the specific Data Analyst roles and responsibilities.

The Data Analyst responsibilities in an organization include:

Data mining: Data Analysts extract data from multiple sources that can be primary or secondary. After that, they organize the data in a proper format that can be easily understood.
Maintaining databases: Data Analysts help design and maintain database systems. This includes creating, updating, reading, and deleting a database.
Data preparation: Data collected from multiple sources would always have errors, redundancy, missing values, and many more, which means that the data is in a raw format. After the extraction of the data, therefore, Data Analysts have to convert the raw data into structured data by resolving the errors in the data, removing irrelevant data, and identifying the potential data. They apply many data cleaning techniques to make it ready for manipulation and visualization by Data Scientists.
Quality assurance: Most organizations rely on their data for their day-to-day pursuits. Therefore, it becomes necessary to get quality data for enhancing the productivity of the organization. Data Analysts make sure that the data collected from multiple sources is relevant to the business.
Collaborating with other teams: Data Analysts prepare data for Data Scientists, ML Engineers, and other software development teams. They use the data for building ML-based automated software. Data Analysts coordinate with development teams to convey the necessary information related to the data.
Maintaining the confidentiality of data: In 2020, data and information are a vital resource for any business. Therefore, maintaining data and information security is one of the important tasks of Data Analysts in the present day.
Preparing reports: Data Analysts prepare reports that represent crucial information. These reports consist of graphs and charts to represent factors associated with the business. They help monitor the direction of business growth by analyzing factors such as profitability, market analysis, internal activities, etc.
Troubleshooting: Data Analysts help troubleshoot issues related to information, reports, and databases.

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Skills of a Data Analyst

The skills that a Data Analytics professional must possess and you must focus on to be eligible for various Data Analyst job profiles are as follows :

1. Mathematical skills (especially statistics and probability)

2. Knowledge of R and Python are highly used for data analysis, visualization, and building Machine Learning models

3. Thorough knowledge of database languages such as SQL

4. Experience in data visualization tools such as Tableau, Qlik, or PowerBI

5. Experience in preparing data using Microsoft Excel or Google Sheets

6. Capable of collecting quality data for analysis

7. Strong problem-solving capability

8. Project management skills

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Data Analyst Job Requirements

Now, in this blog on Data Analyst roles and responsibilities let us look at Data Analyst jobs posted by companies on online job portals along with Data Analyst job descriptions that show certain requirements. A few of the requirements are mentioned below: