5 skills you need to become a data analyst

Data analysis is in high demand by businesses today, with a corresponding shortage of qualified analysts. A Glassdoor study reveals that among the top 50 jobs, Data Scientist is No. 1.

A career in data analytics begins with basic technical skills, but success requires an evolving skill set and excellent relationship skills. The data scientist is essentially the intermediary between the IT department and the business units that require specific solutions. Here are some of the essential skills that data analysts must have to fulfill this role.

1. Computer skills

A data analyst should be proficient in at least one, and often more than one, programming or scripting languages ​​used to manipulate data. These include Java, C ++, MATLAB, Python, PHP, and many more. Almost all business programs have to interact with data in one way or another. It depends on the company’s existing platforms, which are also likely to evolve as new projects emerge.

While it is not possible to master all coding languages, the more experience you have, the more value you will bring to your employer. Once you have learned the basics of coding, it becomes easier to adapt to the different frameworks and syntaxes of new languages.

Data management and manipulation skills are essential. This takes place through languages ​​such as HIVE, R, Scala and SQL, or Structured Query Language, SQL takes different forms on a wide range of data platforms, such as Microsoft’s T-SQL or MySQL, commonly used online. Building queries to extract the information you want is a must for data analysis.

In addition, a large part of your job will be to create efficient and accurate reports using tools capable of spotting patterns and forecasting trends. Some common solutions include Microsoft Power BI, SAS, Oracle Visual Analyzer, and Cognos.

2. Analytical and creative skills

Collecting data in the digital age can lead to huge data sets. You must understand the techniques of cleaning, organizing and structuring data in order to provide effective and reliable results. It means defining data rules to work seamlessly with data technologies.

Investigative and auditing skills are needed to ensure that you are providing the right information for the right business problem. Interpreting data results involves determining the extent and cause of any problem involving “bad” data.

3. Numerical and statistical knowledge

Providing data to provide real value will also require math skills with formulas and statistics. You will need a good grasp of math, but also number combination skills to consistently produce new measurements. A data analyst should also understand the statistics and formulas to meet common business needs such as compound interest or amortization. You should have the ability to express numerical results in the form of graphs, tables and other graphical elements.

4. Business and communication skills

As an analyst, it is your responsibility to provide accurate information to decision makers. You need to be able to understand not only the data, but also the specific requirements of end users. Analysts need to be good communicators to ensure that the data provided matches the goals and criteria of the business. You will have to discuss and collaborate with executives, clients, other IT professionals and various employees.

A team attitude and an ability to communicate transparently are important in sharing information. As someone with expertise in the field, it is your job to make sure everyone is aware of all the influences and constraints on the analyzes you provide.

5. Attention to detail and data purity

In data analysis, you need to be able to pay attention to details. Spotting incorrect or redundant information is essential for obtaining useful results. You should also be able to identify how different facts relate to each other. Errors in the information that business units receive can lead to wrong conclusions that waste time and money.

All data used in information systems should be cleaned or “cleaned up” to remove irrelevant, outdated, or incorrect results. Manual and automated processes may be required to ensure data consistency and accuracy.

The demand for analysts is increasing in many roles and industries. Many IT professionals build some level of data usage into their work. Learning more data skills and tools can open up new opportunities for you. Soft business skills and proven data expertise will further increase your value.

About the Author

Josh McAllister is a freelance technology journalist with years of experience in the IT industry. He is passionate about helping small business owners understand how technology can save them time and money. Find him on Twitter @ josh8mcallister

Sean N. Ayres