When looking at data science and data analytics, it’s easy to think that they mean the same thing. While both deal with data, they have different focuses, methods, and uses. Below, is an insight into what data science and data analytics are.
What is data science?
Data science is a broad field that involves finding insights from large amounts of data using scientific methods, processes, algorithms, and systems. It combines areas like maths, statistics, computer science, and subject knowledge. Data scientists use advanced tools and techniques like machine learning, artificial intelligence, and predictive modelling to spot patterns, make predictions and help with decision-making.
According to Harvard Business Review, a data scientist’s job includes collecting, cleaning and preparing data, and then using complex analytical methods. They often need coding skills in languages like Python or R and might use platforms like Hadoop or TensorFlow. Data science aims to discover deep, strategic insights that can drive innovation and solve complicated problems.
What is data analytics?
Data analytics, in contrast, is more about examining datasets to draw specific conclusions and help make decisions. It is closely tied to business intelligence. Data analysts use statistical tools and software such as Excel, SQL, and Tableau to perform descriptive, diagnostic and inferential analysis.
The main goal of data analytics is to identify trends, measure performance and generate actionable insights based on past data. It’s a more focused approach than data science, often involving the creation of dashboards and reports that help businesses understand their current state and past performance. Data analytics is crucial for improving efficiency and making informed decisions.
For those businesses who want to make the most of their data, understanding these differences is important. Working with a specialist data analysis company such as Shepper can provide the expertise needed to analyse data effectively.
Key Differences
In short, while both data science and data analytics deal with data, they serve different purposes. Data science is about developing new methods and models to predict future trends, while data analytics focuses on interpreting existing data to make immediate business decisions and optimise current processes.
