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Top 10 Data Analyst Skills You Need To Get Hired In 2022

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One of the most in-demand people in the world today, Data Analysts are people who specialise in gathering, sorting and analysing data such that it helps with making important business decisions. They are vital for many companies across different industries that rely on data. According to a study by the International Data Corporation (IDC), the global business analytics and Big Data market grew from $122 billion in 2015 to $189 billion in 2019. It is predicted to reach $274 billion in 2022.

So, since you are thinking of exploring a career in data analytics, or have decided to become a data scientist, or are here simply to upskill yourself, the following data analyst skills will help you get where you want to go.

Top 10 Skills Required For Data Analyst Career

Following are the skills you will need to become the most sought-after data analyst:

1. SQL

One of the easier languages to learn, Structured Query Language (SQL) is used to communicate with databases. Knowledge of SQL lets you sort, update, and organise data stored in relational databases. It also lets you modify data structures. An important skill to have, be ready to face a technical screening with SQL during your interview rounds.

2. Data Visualization

Data Visualization is one of the data analyst key skills. It is the process of presenting data in the form of charts, graphs, maps, sparklines, heat maps, or infographics. It’s a person’s ability to present data findings in such a way that it is easy to understand; data visualization enables businesses to get a better understanding of data-driven insights. Following are a few data visualization tools that you can use:

  • Dundas BI
  • Tableau
  • Google Charts
  • Plotly
  • RAW

3. Data Cleaning

As you are aware, data cleaning is the process of removing or fixing incorrect, duplicate, corrupted, or incomplete data present within a dataset. It is one of the most important data analyst skills because a well-cleaned dataset can generate outstanding business insights. On the other hand, data that is not cleaned properly can produce deceptive insights that can lead to wrong business decisions.

4. Linear Algebra And Calculus Data Analyst Skills

Linear algebra plays an important role in applications of machine learning and deep learning; it supports matrix, vector, and tensor operations. Similarly, calculus is used to build functions that command algorithms to achieve their goals and objectives. Advanced mathematical knowledge is a non-negotiable data analyst skill set. In fact, in this field, you’ll find many data analysts who come from a mathematics or statistics background.  

5. Machine Learning

Although it is not a ‘must have’ in your data analyst skill set, having an understanding of machine learning can help you gain advantage in the data analytics hiring field. While you may not always find yourself working on machine learning projects, having knowledge of the same definitely won’t hurt.

6. Statistical Programming Languages

Statistical programming languages like MATLAB, R, Java or Python help you in performing advanced analysis when it comes to cleaning and visualising large data sets. Although there’s a debate over which language is the best for data analysis, it’ll always be a good idea to learn at least one of them thoroughly. While R aims to solve data analytics problems, Python is easier to learn. And although Java is not so popular with data scientists, it does have excellent Data Science and Machine Learning libraries.

7. Data Warehousing

Data warehousing is the process of creating virtual warehouses for storing and organising datasets. As an analyst, you’ll be responsible for managing these warehouses and monitoring the data within to ensure there are no security issues.

There are several benefits to data warehousing. They are:

  • Informed decision making
  • Historical data analysis
  • Data quality, consistency, and accuracy
  • Access to combined data from many sources

8. Communication

This is one of the important skills needed for a successful data analyst career. Since you will be communicating (be it verbally or via emails, presentation decks, and reports) with various stakeholders throughout the organisation and across all the departments, your communication and presentation skills need to be strong.

9. Critical Thinking

Only when you know what to ask will your datasets give the right answers. You need to be a critical thinker in order to gain important and informative insights from your data.  Identifying the problems, knowing which data will solve these problems, collecting that data and processing it properly to extract the correct information is all part of the day to day life of a data analyst.  

10. Problem-Solving Data Analyst Skills

As a data analyst, you should be able to find effective solutions to any technical problems and roadblocks you might run into. Although there are many tools available online that can help you with resolving these types of issues, problem-solving is still a good skill to have.

The Bottom Line:

With the rapid growth in this field comes the opportunity to improve your skills needed for a data analyst career. You can do so by signing up for Data Science courses or bootcamps. GeekLurn’s own Data Science Architect Program is a 2-year course with 6 months of live interactive sessions by industry experts. Along with 18 months of sponsored project work, the program also gives a 100% job guarantee. To know more, feel free to contact us.

Neel is a Product Manager with an interest in Data Science, Machine Learning, Cloud Computing, DevOps, and Blockchain with expertise in Python, R, Java, Power BI and Data analytics.

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Neel Neeraj

Neel is a Product Manager with an interest in Data Science, Machine Learning, Cloud Computing, DevOps, and Blockchain with expertise in Python, R, Java, Power BI and Data analytics.
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