Data Analysts: Who Are They And What Are Their Skills?

You may have heard data analysts but do you know what does a data analyst do and what are the key skills and responsibilities of a data analyst?If you want to find answers to the questions above, then you’ve come to the right place. In this post, we’ll take a close look at data analysts to let you have a better understanding of who are data analysts and what are their skills and responsibilities.

Data Analysts

Data Analysts

What is a data analyst?

The role of a data analyst can be defined as someone with the knowledge and skills to turn raw data into information and insights that can be used to make business decisions.

What are the responsibilities of data analysts?

Data analyst responsibilities include the following:

  1. Extract data from primary and secondary sources by using automated tools;
  2. Delete corrupt data, fix coding errors and related issues;
  3. Develop and maintain databases, data systems – reorganize data in a readable format;
  4. Perform analysis to assess the quality and significance of the data;
  5. Filter data to identify and correct code issues by viewing reports and performance metrics;
  6. Use statistical tools to identify, analyze, and interpret patterns and trends in complex data sets to aid in diagnosis and prediction;
  7. Assign numerical values ​​to basic business functions so that business performance can be evaluated and compared over time;
  8. Analyze local, national, and global trends affecting organizations and industries;
  9. Prepare reports for management using relevant data to illustrate trends, patterns and forecasts;
  10. Work with programmers, engineers, and management leaders to identify process improvement opportunities, recommend system modifications, and develop data governance strategies;
  11. Prepare final analysis reports for stakeholders to understand the data analysis steps so that they can make important decisions based on various facts and trends;
  12. Another component of the data analyst job description is EDA or exploratory data analysis projects. In such a data analyst project, the analyst needs to scrutinize the data to identify patterns. The next step for the data analyst is to use data modeling techniques to summarize the overall characteristics of the data analysis.

What skills data analysts need?

A successful data analyst requires both technical and leadership skills. A background in mathematics, statistics, computer science, information management or economics can serve as a solid foundation on which to build a career as a data analyst.

The key skills of a data analyst are as follows:

  1. Must have strong mathematical skills, which can help collect, measure, organize and analyze data;
  2. Familiar with SQL, Oracle, R, MATLAB and Python programming languages;
  3. Familiar with database design and development, data model, data mining and segmentation technology;
  4. Rich experience with reporting packages, such as business objects, programming (Javascript, XML, or ETL frameworks), databases, etc.
  5. Very proficient in using statistical software such as Excel, SPSS, SAS for data set analysis;
  6. Good at using data processing platforms such as Hadoop and Apache Spark;
  7. Familiarity with data visualization software such as Tableau, Qlik, etc.
  8. Understand how to create and apply the most accurate algorithms to data sets to find solutions;
  9. Ability to solve problems;
  10. Accuracy and attention to detail;
  11. Good at queries, reports, and presentations;
  12. Team work ability;
  13. Strong oral and written communication skills;
  14. Rich experience in data analysis;

Types of Data Analytics

Data analytics can be divided into four types, and these four types of data analytics depend on each other to bring increasing value to organizations.

  • Descriptive analytics: It can check what happened in the past, such as monthly revenue, quarterly sales, annual website traffic, and so on. These types of discoveries enable organizations to spot trends.
  • Diagnostic analytics:It considers why certain things happen by comparing descriptive data sets to identify dependencies and patterns, which helps organizations determine the causes of positive or negative outcomes.
  • Predictive analytics:It attempts to identify possible outcomes by detecting trends in descriptive and diagnostic analysis, which allows organizations to take positive actions, such as contacting customers who are unlikely to renew their contracts.
  • Prescriptive analytics: It tries to determine the business action to take. While this type of analysis is valuable in its ability to solve potential problems or stay ahead of industry trends, it often requires the use of sophisticated algorithms and advanced techniques such as machine learning.

In a 2016 survey of more than 2,000 business executives, consultancy PricewaterhouseCoopers (PwC) found that businesses found descriptive analytics insufficient for informed, data-driven decision-making. As a result, diagnostic and predictive analytics are increasingly important to organizations.

Conclusion

Thank you for reading our article and we hope it can let you have a better understanding of data analysts and their skills and responsibilities. If you want to know more about data analysts and something related to them like data catalog, data stewards, or SQL lineage, we would like to advise you to visit Gudu SQLFlow for more information. Thanks again! (Published by Ryan on Apr 22, 2022)

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