[Infographic] Top 7 Skills Required for Data Analyst

Most companies understand the value of data-driven business strategy, and that’s why they often look for talented individuals for data analyst roles. Today, a data analyst is one of the most demanding jobs of the 21st century.

In India, the average salary is ₹852,516 for an experienced data analyst; however, an entry-level data analyst can expect to earn ₹325,616. The average age requirement to become a data analyst is 30+ years. Learn more about data analyst salary. in India

Roles and Responsibilities of a Data Analyst

  • Understand, extract, and finally analyse necessary information from the provided raw data.
  • Try to identify patterns, potentials, and new growth factors.
  • Must have problem-solving abilities.
  • Should be familiar with automation tools and streamline manual tasks.
  • Communicate to the management often.

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Here are the required top skills for a data analyst

1. Structured Query Language (SQL) 

The most ubiquitous industry-standard database language is Structured Query Language or SQL. It is one of the essential data analyst skills. Through SQL, a data analyst manages and stores large datasets.

2. R or Python Programming

To manage the data, the data analyst needs to master one of the programming languages. Anything Excel can do, with the use of R or Python, will be done faster. R and Python are open-source and provide a data analyst with the structure for data analytics.

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3. Machine Learning

Machine learning is known to be the critical component of a data analyst’s toolkit. Both AI and ML are said to be the pillars of predictive analysis for modern systems.

4. Data Visualization

Data visualisation skill helps to interpret and understand data. One needs to tell a compelling story through the available data to put across their points. 

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5. Microsoft Excel

The mainstay of a data analyst is still going to be Microsoft Excel. It will let you communicate things and represent data.

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6. Critical Thinking

A data analyst has to synthesise and uncover connections in the data that are not always clear.

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7. Data Presentation

Both data presentation and visualisation go hand-in-hand. A data analyst will be required to establish business goals and objectives.

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What Next?

If you are curious about learning data science to be in front of fast-paced technological advancements, check out upGrad & IIIT-B’s Executive PG in Data Science.

What are the qualities of a good data analyst?

Analysing data is a highly technical field, and to be successful, one must have multiple skills and characteristics. Data analysts should have these characteristics.
A strong data analyst needs to follow a systematic methodology when approaching a problem. As a general rule, data analysis necessitates the ability to create step-by-step instructions that others can follow in order to analyse the data they obtain.
Data analysts should be able to identify how valuable the data is to their company and their boss. This understanding should be reflected in their reports, and reports that target the readers should satisfy the requirements of those who will read them.
The best data analysts are the ones who are able to think outside the box when it comes to displaying data. This is what makes previously-seen data innovative and new.
A strong ability to find mistakes in the data and to include them in reports is a critical attribute for data analysts. Additionally, they should be able to clearly articulate how these flaws could result in skewed findings.
In order to find trends and identify patterns in different sets of data, data analysts have to examine a number of data sets in order to spot emerging patterns.

What are some tips to ace data analysis?

Have these tips on how to encounter the challenge as you're building new skills, working through rough patches, and increasing your confidence as a data analyst.
1. The value of data skills is demonstrated when you think about your future goals.
2. As a second step, complete an online course that improves foundational skills.
3. Set aside a few minutes every day to work on your data skills.
4. Errors are opportunities to learn.
5. To build on your data analyst abilities, start by doing small things.
6. Put your knowledge to the test on projects that use real data.
7. Don't just consume data, get involved in the community that provides it.
8. As well as your workplace skills, put equal emphasis on your creative ones.
9. As well as your workplace skills, put equal emphasis on your creative ones.
10. Never stop learning, even after you've completed your education.
11. Master data skills by understanding how, what, where, when, and why they are used.

Is data analysis difficult?

Data analysts must be able to use skills such as coding in R or Python, as well as perform database queries with SQL, in order to excel. As frustrating as it can be, these skills can be learned (and can land you a job as data analyst) with the right attitude and approach.

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