5 Skills You Need to be a Great Data Analyst

Becoming a great data analyst takes more than just having strong quantitative skills. To be successful in this field, you must also possess certain soft skills and be able to effectively communicate your findings. In this blog post, we will explore 5 skills that you need to succeed as a data analyst.

1. Analytical and problem-solving skills – As a data analyst, you will be responsible for analyzing data and providing insights that will help improve business decisions. Hence you will need to have strong analytical and problem-solving skills and a curious bent of mind to understand the business processes and functions.
2. Data organizing skill – A data analyst is someone who collects, organizes, and analyzes data. They must be able to work with large data sets in organizing data and performing data wrangling using various methods. Here you will use a combination of different query languages like SQL for working on structured or unstructured databases like SQL/Oracle or mongodb/Hbase respectively.
3. Data visualization skill – Data analysts use a variety of tools to visualize and analyze data. Dashboards and visualizations are two common types of tools used by data analysts. Dashboards provide a quick and easy way to view data sets, while visualizations allow for more in-depth analysis. Data visualizations help tell a story visually and makes it easier to understand for business users. You will also learn about the popular tools used for data visualization in the next section.
4. Data analysis skill –  As a data analyst you need to analyze data to identify trends, patterns, insights and relationships in data sets. So you need to know various analysis methods like Pareto analysis, Scenario analysis, Inferential statistical methods to test hypothesis, statistical and machine learning methods etc.
5. Communication skill – Data analysts work with businesses to help them make better decisions by turning data into insights. In order to be successful in this role, you must be able to effectively communicate the findings to non-technical business audiences.

Tools used by Data Analysts

Data analysts use a variety of tools to help them understand data sets and glean insights from them. Two of the most popular tools are powerBI and Python. PowerBI is a business intelligence tool that helps users visualize data and spot trends. Python is a programming language that is widely used for data analysis due to its ease of use and powerful libraries.

1. Power BI from Microsoft is a powerful data visualization tool that can help you see your data in new and interesting ways. With Power BI, you can create stunning visualizations that tell a story about your data, and help you see relationships and patterns that you might not have noticed before. Power BI is also very user-friendly, so even if you’re new to data visualization, you’ll be able to learn and create beautiful visuals with ease.
2. Python is a versatile open-source language that can be used for data analysis, scientific computing, artificial intelligence, and more. It is easy to learn for beginners and has many features that make it useful for experienced programmers. It has a wide range of libraries and tools that make it easy to work with data. Python is also a popular language for data wrangling, creating data pipelines and data analysis using statistical and machine learning models.