How to Become a Data Analyst

What Do Data Analysts Do?

The field of data analysis is open ended enough that each position is going to somewhat unique in its duties. There are some common traits with all analysis jobs. It would be worthwhile to first look at some data analysis basics.

Data analysis can be broken down into roughly four different areas of analytics: descriptive, diagnostic, predictive, and prescriptive.

Descriptive analytics covers what has happened. This is the fundamental job of analysis: looking at existing data and explaining what it can tell you about past behavior. This could be as simple as how many units of a product were sold last month, or as complicated as pulling in data from a variety of sources to examine overall costs. This provides companies with a lot of what but not much why.

In diagnostic analytics, historical data is set against other data to try to understand (for example) why profits were down last month. This involves pulling any and all other data to search for correlations. Beyond number crunching, this involves some human analysis and speculative thinking.

If descriptive and diagnostic analysis is about what happened, predictive analysis is about – you guessed it – what’s going to happen. This involves taking the data from the past and using it along with human reasoning to make accurate predictions of future behavior. This is where the real decision making can come into play for a business, as they can use those predictions to determine what products to market heavily, where to spend money, or any number of company actions.

Finally, prescriptive analytics are to help decide what actions to take in the future to get ahead of potential problems or seize a latent opportunity. The work from the preceding three forms of analysis help shape this data so that an organization can make logical and fruitful decisions for their future.

Data Analyst Job Description

The responsibilities of a data analyst varying with employer and specific positions, but there are some general tasks that are common to any analyst position. Any data analyst professional will be collecting data, sift through that data looking for patterns or trends, and produce reports based on their findings. This process will inevitably involve collaborating with others to gather than information and present it in a useful manner.  In short, the data analyst job is designed to help companies make informed business decisions.

More specifically, a data analyst will spend a lot of time making data queries on databases (usually with SQL. More on that below), perhaps using self-coded programs to extract that data more efficiently. They will analyze it, possibly using mathematical tools and technical skills to present their findings in reports for a variety of audiences to understand.  Statistical analysis is also an important part of the role, similar to the responsibilities of a data scientist.

Data Analyst Coding Languages

Coding is an important part of data jobs, and data analysts should be well-versed in a variety of languages. Each individual job will have different coding requirements, but data analysts are usually familiar with at least a few common languages. These languages vary in use, purpose, and format, but each is tremendously important for certain aspects of the job. Below, we’ve included 3 examples of common coding languages in the field of data analytics.