What do Data Analysts do all day?

Before we dive into data analytics, it's important to understand what Data Analysts do – and don't – do. These days, it can seem like everyone is working with data. There are Data Scientists and Data Engineers (not to mention Business Analysts) – so what sets Data Analysts apart from the pack? It's all about the balance of skills you bring to the role. Data Analysts work with large data sets to identify trends, create visual presentations, answer questions, and ultimately solve problems. In addition to their technical skills, they have strong business knowledge and a knack for crafting compelling charts and other visuals. That's in contrast to Data Scientists, who design new processes for modeling and analyzing data, and Data Engineers, who write the code that keeps all that data organized and accessible.

Make sense? In a nutshell, your job as a Data Analyst involves using the tools developed by Data Engineers and Data Scientists to help companies understand and improve their business. In addition to crunching numbers, you're an accomplished translator and storyteller who can glean valuable insights and communicate them to other stakeholders.

Breaking Down Data Analytics

"Data Analysis" is still a pretty big category! To help you get a handle on the kind of work you'll be doing, let's talk about the four main categories of data analytics. These are standard terms in the industry, so understanding what they are how they work will help you sound polished and prepared in job interviews.

1. Descriptive Analytics tells you what happened in the past. You'll look at monthly revenue reports, quarterly sales, web traffic, and other metrics to spot trends that matter to your business.
2. Diagnostic Analytics tells you why things happened the way they did. This is where you use tools like customer segmentation and other comparative data sets to figure out why your company missed sales targets or exceeded their own expectations.
3. Prescriptive Analytics is the study of what might happen in the future. Data Analysts use sophisticated models and tools like machine learning to detect clusters and predict future trends. This can help companies take proactive actions to jump on new opportunities or avert crises.
4. Predictive Analytics helps you tell your company what they should do. Like predictive analytics, prescriptive analytics uses sophisticated tools from data mining and machine learning to model potentials solutions. Because these techniques are speculative and resource intensive, not all companies use them.

Descriptive analysis is an essential foundation for the rest of your work, but in most roles, diagnostic and prescriptive analytics will be your bread and butter. They're what help you answer the questions that companies care about, like how they can expand their business and avoid repeating past mistakes.

Tools and Technologies

Data Analysts have lots of tools to help turn raw data into well-crafted stories and visual presentations. In this section, we'll go over the most essential ones. Then, we'll walk you through everything you need to master them, from beginner-level introductions to advanced guides. With these resources under your belt, you'll be a data expert before you know it.

1. You already know what Microsoft Excel is – and Data Analysts are Excel pros.
2. SQL, or Structured Query Language, is a computer programming language designed to work with databases. It's important for any application that involves storing or accessing lots of information.
3. There are lots of different programs Data Analysts use for Data Visualization – like Looker, Tableau, and Power BI.