Interview Question: What does the term Data Science mean?

Tracyrenee
3 min readNov 28, 2023

I have been studying data science for three years now and I have learned that it encompasses a lot of specialities within the field, which is why data scientists can be so well paid.

Data science combines maths and statistics, specialised programming, advanced analytics, artificial intelligence (AI), and machine learning with specific subject matter expertise to uncover actionable insights hidden in an organisation’s data. These insights can be used to guide decision making and strategic planning.

The accelerating volume of data sources, and subsequently data, has made data science one of the fastest growing fields across every industry. Organisations are increasingly reliant on data scientists to interpret data and provide actionable recommendations to improve business outcomes.

A data scientist project typically involves three stages, being:-

  1. Data ingestion: The life cycle begins with the data collection — both raw structured and unstructured data from all relevant sources using a variety of methods. including manual entry, web scraping, and real-time streaming data from systems and devices. Data sources can include structured data, such as customer data, along with unstructured data like log files, video, audio, pictures, the Internet of Things (IoT), social media, and more.
  2. Data storage and data processing: This stage includes cleaning data, deduplicating, transforming and combining the data using ETL (extract, transform, load) jobs or other data integration technologies. Data preparation is essential for promoting data quality before loading into a data warehouse, data lake, or other repository.
  3. Data analysis: The data scientists conduct an exploratory data analysis to examine biases, patterns, ranges, and distributions of values within the data. This data analytics exploration drives hypothesis generation for a/b testing. It also allows analysts to determine the data’s relevance for use within modelling efforts for predictive analytics, machine learning, and/or deep learning. Depending on a model’s accuracy, organisations can become reliant on these insights for business decision making, allowing them to drive more scalability.
  4. Communicate: Insights are presented as…

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Tracyrenee

I have close to five decades experience in the world of work, being in fast food, the military, business, non-profits, and the healthcare sector.