Month: August 2018

Basic Data Analyst Qualifications and Skills

Data analysts have become more and more important and in high demand. This is because Data Analyst Qualifications is a useful skill that organizations need in order to understand and process their data. Data is the future and in order for an organization to take advantage of big data to grow their business and gain more insight on their customers and business process, they need data analysts with the right qualifications to help them handle their data. Think of data analysts as data whispers – they know what to do and how to handle data to meet the needs of their clients and organizations. Below are the major skills and qualifications that data analysts need.

Computer Skills

I guess everyone does need computer skills in their daily life and in their jobs. However, data analysts not only need computer skills but they also need advanced computer skills. A data analyst needs to be proficient in at least one or more programming languages such as C++, MATLAB, R,  or Python. Different companies use different platforms to store their data but one of these programs always end up being needed. Also as new projects come along and new data is created, the data analyst will need these computer skills to adapt and analyze the new data.

There are many coding languages and it is not expected that data analysts be proficient in all but a basic understanding of a good number of these coding languages is expected. And once a data analyst understands the fundamentals of coding, it becomes easier to learn new coding languages. Furthermore, much of a data analyst jobs require them to create and analyze reports and they will need to use other basic computer tools like Microsoft, Powerpoint slides etc (more on this below).

Analytical and Creative Skills

It goes without saying that a data analyst will need to be able to analyze data. With the continuous and rapid growth of data, a data analyst needs to process sharp analytical and creative skills to help them sieve through the data. They need to possess basic techniques of cleansing, organizing, and structuring data to provide efficient and reliable results. They need to come up with dataset rules (probably using a coding language) that works seamlessly with other technologies and can adapt when new data (both structured data and unstructured data)  is brought in. They will also need to be able to interpret data results, investigate data and be able to deal with and get rid of “bad data” or compromised data.

Numerical and Statistical Skills

You can’t talk about data without at some point, mentioning statistics. In order for data to provide real-world value and use, it has to be processed using mathematics and statistics. A data analyst needs to have more than a basic grasp of mathematics and needs to be able to use statistical tools. A data analyst should also understand statistics and formulas to satisfy common business needs such as compound interest or depreciation. They should have the ability to express numeric results as charts, tables, and other graphical elements.

Business and Communications Skills

Being a data analyst means the whole organization relies on you for their data needs. Data analysts will have to communicate constantly with department heads and team heads to help them meet their data needs. Hence, they have to have good communication skills and a willingness to collaborate with and help other people in their organization. The would also need to communicate frequently with people outside the organization such as clients, other data analysts in other organizations, IT personnel etc. A data analyst should be able to communicate with transparency, in a timely manner, and with professionalism.

Attention to Details

A data analyst should be able to notice the small things, not miss any details and should have a good attention span. This skill is what will enable a data analyst to identify trends and patterns in the data. The attention to detail is also what’s going to enable a data analyst to spot errors in data and get rid of it before it causes any damage to the larger dataset. A data analyst knows that any data that’s used in information systems should be cleaned to eliminate irrelevant or incorrect data entries. Both manual and automated processes may be necessary to ensure data is consistent and accurate.

Data Analyst Skills Using Data Visualization (Advanced)


Some of the major tools that a data analyst would have to use our data visualization tools. There is a lot of insight to be gained from data that can be visualized. This means using graphs, charts, etc to display data and communicate with data is very important. Data visualization is an essential vehicle for communication between the data analyst and the rest of the organization. It helps to simplify the data and communicate in clear terms what the data means.

For example, tools like Excel spreadsheet graphics can be used to communicate smoothly what a data setting means. It can also be used to make visually engaging charts and graphs that show growth, decline or changes in the datasets and everyone is able to understand it clearly. Powerpoint presentations can also be used to communicate lots of information in a simplified and quick way. There are other data visualization tools like Keynote, Prezi etc.

Conclusion

The old way of presenting data is no longer good enough, the more data is out there the more data people have to process and so the less time and attention span they have to spend on each data set. This is why people make their resumes to look more appealing with data visualization tools, colors and informative but succinct statements and facts about themselves.