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AI Careers 101:

What is a Data Analyst? Salary, Responsibilities, Skills, & Career Path

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The World Economic Forum in Future of Jobs Report 2020 listed data analyst as the second fastest-growing job. According to Glassdoor's estimate, the median Data Analyst Salary is $71,228 per annum in the U.S. Data is the new oil. W. Edwards Deming, an American Statistician and Author said that “In God we trust. All others must bring data.”

Data has huge potential that can be used in business growth and decision-making. Data analysis refers to manipulating data to extract actionable insights. As the data continues to grow exponentially, the need for someone who can analyze this data also rises.

What is a Data Analyst?

Data analyst observes patterns and trends in data and describes them. They assist organizations in identifying opportunities and making data-driven decisions. Data Analyst infers causes behind specific events, and he does that by making reports, dashboards, data visualizations, and presentations. In healthcare, they analyze medical data to improve the business side of hospitals and patient care. In the finance sector, they suggest investment plans and business strategies based on financial data.

Data Analyst Job Description

Data Analysts have a lot to do, from gathering data to communicating the results. The detailed data analyst job description is as follows:

Data Collection: Gathering data is the first step in the analytics life cycle. In big industries where roles and responsibilities are clearly defined, data analysts receive data from data engineers. Otherwise, the data is obtained through internal databases or external sources.

Data Cleaning: In most cases, data is not clean. It contains missing values, duplicated records, and formatting inconsistencies. Before analysis, the data is preprocessed into a suitable format intended for data analysis.

Data Analysis: In this step, the Data analyst studies data to seek insights that can be helpful. They perform statistical tests and visualize the distribution of single variables and relationships between multiple variables. They look at the data from various perspectives using various statistical, visualization, and business intelligence (BI) tools and charts to get deeper insights.

Data Interpretation: Data interpretation refers to documenting the findings and results in the business problem context. In this step, the data analyst answers critical questions and arrives at relevant conclusions.

Communicating the insights: Finally, the data analyst shares the key findings with the team, including management and stakeholders. Based on the results, the data analyst suggests strategies, including identifying new opportunities, improving operational efficiency, improving marketing campaigns, etc. Insights are shared via reports, presentations, dashboards, and visualizations.

How to become a Data Analyst?

Programming Skills: Programming is the most important technical skill for data analysts. A data analyst should have a decent knowledge of SQL (Sequence Query Language) to insert, extract, and update data in the relational database. Candidate must be proficient in Python or R.

Statistics: Statistics is required to study, analyze, visualize and interpret data to make well-informed decisions. Many data visualization techniques require a solid understanding of statistics. For example, creating a scatter plot involves understanding regression & correlation, and a box plot requires understanding measures of central tendency & dispersion.

Data Visualization Skills: A picture is worth a thousand words. Data Analysts use visualizations to present information to their team and non-technical stakeholders. They use tools such as PowerBI, Tableau, Excel, and python libraries such as Matplotlib and Seaborn to make visualizations. Various charts exist, but selecting the right style is necessary to convey the message.

Soft Skills: Communication is the most critical soft skill for data analysts. Effectively communicating the key insights to the technical team and stakeholders can help a business modify its strategy. A data analyst should have a good presentation and attention to detail to convey his point. They should have critical thinking and creativity to see the data from multiple perspectives. A data analyst needs to have problem-solving and project management skills to effectively answer the questions posed by stakeholders and employers and complete the project.

Many Edtech platforms teach the skills necessary to become a data analyst. Enrolling in the proper certifications will help you learn the skills and enhance your credibility as an expert. You can further your expertise by applying your acquired skills to real-life datasets. Effective presentation and documentation of these projects will help you crack your first data analytics job.

Career Paths for Data Analysts

Data Analytics is a diverse field and has multiple job roles in the analytics industry, which are as follows:

  • Business Analyst
  • Operations Analyst
  • Financial Analyst
  • Marketing Analyst
  • Risk Analyst

Depending upon your skills, interest, and experience, you can pursue a career in any of the above roles. Career Paths for Data Analysts also include becoming senior analysts, transitioning to data scientists, or advancing into management roles.

Data analysts actualize the potential of raw data by using statistical methods and visualization tools. Moreover, many job roles under the data analytics umbrella will continue to grow till the next decade.

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