Data Science! Data Science

Before we dive into data science, What is data?
Data is a collection of raw facts and figures collected for a specific task e.g. census data, number of cars that use a road per hour, daily weather updates, etc. Once this data is collected it is not useful to anyone until some analysis is done on it and this brings us to data science.

Data science Definition
Data science is the study of data to extract meaningful insights for business and solve real-life problems. Easy right :).
Data science is a multidisciplinary field that is it combines different disciplines including mathematics, statistics, probability, programming, and more.

Key Components of Data Science

• Data collection
• Data cleaning
• Data Exploration
• Modeling
• Interpretation

Data Collection
Data collection is the first step in data analysis. This involves gathering data from existing databases or collecting it directly from locals. eg if I need to do an analysis of how a school is performing I can get the data from KNEC or visit various schools, get the data from them, and do my "thing".

Data cleaning
You have the data now, many a time when this data is messy, has errors, has outliers, and has duplicates basically means it cannot be used in raw form. Data cleaning involves removing all the irregularities that may interfere with the correct analysis and insights.

Data Exploration

It's time to work with the data now that you've cleaned. Data exploration is summarising and visualizing data in order to better comprehend its properties. Finding patterns and relationships in the data is made easier by methods like data visualization, descriptive statistics, and exploratory data analysis (EDA).

Modeling
It entails creating mathematical and statistical models to predict the future or unearth undiscovered information. Regression analysis, clustering, neural networks, and machine learning algorithms are examples of common modeling techniques.

Interpretation

Data scientists interpret the outcomes of model training and prediction to obtain actionable insights. To fully understand the impact of the findings and make informed choices, this phase necessitates domain expertise e.g. transport, Medicine, climate, etc.

Data Science Applications

Health Care
Transport
Sports etc

Conclusion
Data science is the process of extracting meaning full insights that will help businesses make informed decisions as well us solve reallife problems.