Data Analytics is the process of extracting data and developing insights from it to help companies make better, more informed business decisions. By analysing and sorting data into understandable visual components and useful information.

A data analyst can provide the business intelligence required to solve a problem or challenge that a business may face during it’s growth. By finding patterns and correlations in data, a data analyst can provide valuable insights from external sources such as customer interactions, feedback, sales, spending habits or even internal factors, such as how employees interact with particular business tools.

What is Data Analytics used for?

Summary: Gathering valuable business insights from data.
With better data, comes better solutions, and with that, better decisions in many aspects of a business such as their target audience, their internal employees and perhaps even their industry as a whole. So what does Data Analytics look like?

Well to start with, data is everywhere and has an almost infinite amount of uses across all businesses, activities and even societies globally. Having this kind of research in place can reduce business expenses by avoiding risk and could even develop new and innovative ways to offer products and services to consumers.

Advantages of Data Analysis

  • Anticipate potential customer sales patterns and behaviours.
  • Analyse the effectiveness of various marketing campaigns.
  • Insights could boost customer acquisition and retention.
  • Protect against fraud and increase supply chain efficiency.

What do Data Analysts do?

  • Manage all incoming data and build data visualisation reports.
  • Define, manage and execute analytical projects, evaluating the results.
  • Monitor practices and processes to discover opportunities for improvement.
  • Translate business needs into important analytical projects.
  • Liaise with key stakeholders and provide data driven insights.

The 5 Main Stages of Data Analysis

  • Define the problems that needs answers within the business.
  • Chart where this data will come from, what will you need?
  • Collect the relevant data from the sources you have found.
  • Analyse the data, extract insights and summaries from it.
  • Share the result of your findings with key business stakeholders.

An Example Data Analysis Study

  • Problem: After a free trial expires, most customers do not re-subscribe.
  • Solution: Define and collect all relevant data points and ask questions such as were there any cancellation spikes? Recent price increases? Evaluate the subscribers that stay, why? Do we have any recent bad media? Find patterns.

What Skills do you need to be a Data Analyst?

  • A good understanding of Mathematics and statistics.
  • An analytical mindset and problem solving skills.
  • Experience of Python, SQL and various CRM’s would help.
  • Communication skills to share your valuable insights.

“The code you write makes you a programmer. The code you delete makes you a good one. The code you don’t have to write makes you a great one.” – Mario Fusco.