Admissions open for Data Analytics & Data Science, at DataMines | Hurry few seats left

Resources

Home Resources

What is Data Science?

Data Science is like being a digital detective. Imagine you have lots of digital clues—numbers, words, pictures—from different places like your computer or the internet. Data scientists are like detectives who collect these clues, clean them up, and organize them. It’s a bit like sorting out a messy room, making sure only the important things are kept.  Then, they use special tools to explore these clues, finding interesting patterns or connections. It’s like having a magnifying glass to look closely at things. After that, they create magic formulas called models, which can predict things or help understand the clues better.

Once the detective work is done and the models are good, they use their findings to help businesses make smart choices or even predict exciting trends. So, data science is all about being a digital detective, solving puzzles, and making the world a smarter and more interesting place!

What is Data Analytics ?

Data analysis is the process of analysing, cleansing, manipulating, and modelling data in order to extract relevant information, draw conclusions, and aid decision-making. It entails analysing databases to find patterns, trends, and insights that can provide useful information. The process normally begins with the collection of pertinent data, which is subsequently organised and prepared for analysis. Data analysts employ a variety of statistical and computational techniques, as well as visualisation tools, to investigate data and extract useful findings. Data analysis is used in many different industries, including business, research, healthcare, and social sciences.

In the business world, it assists organisations in understanding customer behaviour, optimising processes, and making strategic decisions. Data analysis is critical in scientific research because it allows researchers to derive conclusions from observations and experiments.  

Implemantation of data science in day to day life ?

Data science is quietly improving many parts of our daily life by making them more personalised and efficient. Consider internet shopping—when you see recommendations for things you might like, that’s data science analysing your previous purchases. Social networking networks utilise it to display postings from friends or topics of interest to you. Phone navigation apps, such as Google Maps, use data science to determine the shortest routes by analysing real-time traffic data. Health and fitness applications monitor your activity and sleep to make recommendations for a healthy living. Even when you type on your phone, predictive text employs data science to forecast what you will say next.

Netflix and other streaming services utilise data science to recommend films and series based on your likes. In a nutshell, data science acts as a behind-the-scenes helper, tailoring and optimising our digital experiences across a variety of activities in our daily lives.

Implemantation of Analytics in day to day life ?

Data analysis is seamlessly incorporated into our daily routines, improving decision-making and efficiency in many areas of life. For example, when we check the weather forecast before organising an outside activity, we rely on data analysis to accurately predict future conditions. Similarly, social media networks use data analysis algorithms to create personalised feeds that display material based on our interests and choices. In healthcare, data analysis is crucial for detecting diseases, monitoring patient health, and forecasting treatment effects.

Even when we purchase online, data analysis algorithms recommend products based on our browsing and purchasing history, simplifying the shopping process. Data analysis is an invisible yet vital tool that changes our daily decisions and experiences, making life more informed and efficient. Examples include navigating traffic with real-time updates and tracking fitness goals with health applications.