Skills Needed to Get Hired as a Data Analyst in 2023

Skills Needed to Get Hired as a Data Analyst in 2023

Who is a Data Analyst?

A data analyst is an expert who gathers and examines data across the business to settle on informed decisions or help other colleagues and initiative in using wise judgment. Data analysts unify analysis, innovation and business goals to guarantee that every data they gather is utilized to accomplish desired results for their organization.

The works of a Data Analyst could be sub-categorized into Technical and Soft skills.

Technical Skills:

Microsoft Excel

Microsoft Excel is a software program produced by Microsoft that allows users to organize, format and calculate data with formulas using a spreadsheet system. If you are interested in learning Excel, you can check out Chandoo.

Programming Skills

Statistical languages like Python and R are the most widely used and significant programming languages. If you know how to write programs in these languages, you can clean, analyze, and visualize large data sets more efficiently.

SQL

The preferred language for interacting with databases is called Structured Query Language. Knowing SQL allows you to change data structures and query, organize, and update data stored in relational databases (schema). Each row in a table comprises rows and columns; in SQL databases, rows are called a record, and columns are a field. Here are some recommended resources to understand SQL:

Data Visualization

A competent data analyst must be able to present their findings convincingly. Colleagues, employers, and stakeholders will comprehend your job if you can convey information effectively using charts and graphs. Examples of data visualization tools are Power BI, Jupyter Notebook and Tableau.

Statistical Knowledge

This knowledge enables data analysts to analyze and interpret data in a meaningful way. This knowledge includes an understanding of basic statistical concepts such as probability, hypothesis testing, descriptive statistics and inferential statistics. Statistical knowledge is a fundamental skill for data analysts, allowing them to analyze and make predictions about data, which is crucial for making informed business decisions.

Soft Skills:

Communication Skill

Collaboration with your coworkers and those who need to know of your discoveries depends on effective communication. Effectively communicating these conclusions is crucial for a non-technical audience that must analyze the data to inform business decisions. Furthermore, different team members require various information transmission techniques. You need to be able to explain your findings to others with simplicity. Even if you are the world's most gifted and analytical data analyst; you will fail if you are unable to explain the patterns you discovered to those who lack technical expertise.

Critical Thinking

Critical thinking is a practice where you pay attention to how you think and look for methods to improve it. You can use critical thinking when sorting out the justification for issues in your own work life.

The following are the steps to follow:

  • Identify the problem

  • Define the problem

  • Prioritize the root cause of the problem

  • Define the solution

  • Implement solution

  • Evaluate result.

Storytelling

Data Storytelling is a strategy for imparting customized data to a particular audience with a convincing story. Storytelling influences a business. An exemplary "storyteller" will guarantee that the outcomes from the data analysis and display get conferred to the right audience in a justifiable organization. A good storyteller leverages data, narrative and visuals.

Business Acumen

This is a crucial skill for data analysts because it enables them to understand how their work can impact the overall performance of an organization. Business acumen enables data analysts to communicate effectively with stakeholders across the organization and present data insights in a relevant and actionable way for the business. Overall, business acumen helps data analysts to bridge the gap between data analysis and business strategy, and become valuable assets to the organization.

Conclusion

In conclusion, being a successful data analyst requires a combination of technical skills and soft skills. You can use these skills to land your dream job this year because data analysis is a career path in this constantly evolving industry.

Ensure to check out DataCamp or the Google Data Analytics course to learn more.