One of the challenges facing data analysis is that there are multiple domains, industries and tools used in the data analyst industry.

So, attempting to master every single data analysis tool in the workplace may be futile.

What is helpful is a strong understanding of the data analysts roles, duties, tasks, responsibilities and the techniques or principles commonly employed in data analyst jobs

The Data Analysts Job Description

The data analysts job description frequently includes importing, cleaning, transforming, validating or modeling data with the purpose of understanding or making conclusions from the data for decision making purposes.

The data analysts job description may include presenting data in charts, graphs, tables, designing and developing relational databases for collecting data and in some organizations it also includes building or designing data input or data collection screens.

The data analyst may have to write Data Definition Language or Data Manipulation Language SQL commands, be responsible for improving data quality and for designing or presenting conclusions gained from analyzing data using statistical tools like Microsoft Excel, SAS, SPSS and others.

Data analysts work in diverse domains including healthcare or social sciences and they come from a diverse background.

Some data analysts have backgrounds in technology, information management, relational database design and development, business intelligence, data mining or statistics.

What is important is not the specific tool like SAS or SPSS but the investigative mindset or techniques that can be used with any specific tool.

It is important not to get tool minded but to get process minded. For example, it’s important to understand the concept of designing a business report because you can learn and implement that report in Crystal Reports or SQL Server Reporting Services or even with Microsoft Access Reports.

A good data analyst can convey his or her mastery of data analysis concepts at the job interview and direct the interviewers to a favorable conclusion.

For example, let’s say that a data analyst job description stresses SQL Server Reporting Services skills and you only have knowledge of Microsoft Access.

What you can do is let the job interviewer know that you have strong data analysis skills and will be comfortable working on new tools.

You can achieve this by stressing your data analysis experience by talking about your data validation experience, discussing how you have analyzed large datasets, drawn your own inferences and presented them successfully to management using a reporting tool.

Then you emphasize the strength or advantages of your data analysis background and repeat that you are willing to learn the data analysis tool used by the employer in question.

So, a solid understand of data analysis techniques or processes will help reduce the need for you to learn every data analysis tool in the market!

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