The term “data science” is trending like never before, with many looking to study the subject and pursue careers in the expanding market, but what does data science mean at its core? This article intends to explain the general definition of digital data science and its uses in simple terms.
Definition of Data Science
Digital data is one of the most valuable assets of the 21st century. Your browsing history, Instagram likes, Geo-location check-ins are all relevant to various data scientists. The ultimate goal of data science is to measure and understand how to make our lives more convenient (sometimes without us even realising it).
The job of data scientists combines many things, but their main role is to collect and identify trends within data sets. Companies may benefit from found data stats to root new products or systems that cater directly to clients’ needs.
How does Data Science work?
We can observe the process of a typical project through the Data Science Life Cycle:
- Business Problem
Understanding a given problem that needs a solution - Data Acquisition
Obtaining the data through either direct data entry or automated data collection and machine learning (e.g. scraping or crawling) - Data Preparation
Preparing data for processing with methods such as data architecture, cleaning and transformation - Processing, Data Analysis, and Modeling
Scientists process the data through mining, modelling, and summarisation. By examining any patterns or biases that appear, the scientists can perform proper data analysis. - Visualisation and Communication
Presenting complex data analysis results in digestible formats for clients, such as graphs, charts, and reports
What is Digital Data Science used for?
Here are some examples of what data science can be used for:
Tracking and analysing what content people respond to and creating algorithms from data for recommendations (e.g. Netflix, Spotify, YouTube, TikTok) and targeted ads (e.g. Google Ads)
Detecting patterns in climate data
Forecasting market and sales behaviour
Creating automated bots that can detect and classify assets, such as junk mail
Self-driving cars use a combination of data science, machine learning, predictive analytics to make safe decisions when on the road
Building cybersecurity software that can automatically detect new viruses, malware, and cybercrime through data science
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4 Comments. Leave new
Definitely a must-read blog for beginners, simply explained in a concise manner.
A lot of useful information is contained in this article. Superb work. Thank you for letting us know about this.
A great read for the upcoming Data Scientists. Thanks for explaining all the things in a precise and simple way.
Very informative blog!!