What tools and skills does a data analyst use?

what tools and skills does a data analyst use

Data analytics is an umbrella term for a huge field of interdisciplinary roles. Amazon web services (AWS) defines data analytics as the actionable insight gleaned from raw data sets. “It includes a range of tools, technologies, and processes used to find trends and solve problems by using data,” AWS says. 

In previous blogs, we’ve discussed how data analytics helps in marketing, security, education, healthcare, and more. But what tools do data analysts actually employ, and what skills are needed for a successful career as a data analyst?  

Tools: programming, data visualization, accounting

Data analysts utilize all kinds of tools, ranging from some of the most cutting-edge, innovative software to tools of accounting and analysis developed centuries ago. 

  1. Programming. Data analysts can serve as both programmers as well as analysis experts so they are typically able to understand programming languages like Python, a high-level programming language with dynamic semantics built in data structures that makes it easy to learn and use as a data expert. Those who can program using Python also employ data-specific software tools, such as Pandas, an open source data analysis and manipulation tool.
  1. Data visualization. What makes data analysts interesting is their ability to understand complex data sets and utilize data visualization tools to be able to communicate these insights in a way that is understandable. Visualization of data can be through pie charts, histograms, Gantt charts, heat maps, waterfall charts, infographics, scatter plots, and more. Tools include software such as the classics, like Microsoft Excel, to Tableau, one of the most popular for data analysts. 
  1. Accounting. Digital tools over the years have helped automate many manual accounting processes, so that data analysts can play a more analytical role. Analysts utilize accounting tools to inspect financial records for fraud or analyze and interpret yearly financial statements.

Skills: quantitative reasoning, communication, and solution-finding

In addition to software and other data tool capabilities, data analysts need the skills to interpret, communicate and utilize data results.   

  1. Quantitative reasoning skills are the ability to use mathematics, such as statistics and algebra, to solve complex problems. It is not just understanding how to find solutions using numerical data, but also to find explanations and interpretation for that data. Quantitative skills help in “interpreting and analyzing mathematical information, finding appropriate methods of solving problems and evaluating the validity of results.”
  1. Communication skills go hand-in-hand with data visualization and interpretation tools. Communication skills include the important ability to explain what is gleaned from data insights. Many people using this data won’t be programmers or other analysts, so data analysts need to be able to understand the interpretations in meaningful ways. 
  1. Solution-finding skills take the analysts skillset to the next level. A data analyst should have the skills not only to interpret and understand what the data before them means, but also be able to solve the problems that arise from this data and understand what types of decisions and changes can create more positive outcomes. 

Carlow data analytics students take courses to understand the various tools of data analysis, including data visualization, accounting, and courses to build understanding in the full capabilities of programming languages like Python. Further, the data analytics major also includes programming to develop skills that lead to a successful career as an analyst, including courses like Communication: Personal to Professional;  Quantitative Reasoning; and a choice of detailed electives that help them solve problems and find solutions.