There is more data than what is required. This data needs to be organized and used as and when required so as to increase productivity. Data Science has given rise to a paradigm to solve numerous business problems. Data science requires overall knowledge, especially in computational science, mathematics and statistics. Today, data science is applied in almost all fields including telecommunication, health care, transport, education, etc. It has been making lives easier and convenient.
What exactly does Data Science comprise of?
It has six essential steps or rather processes. The first is the ‘Why? What?’ part. The data scientist asks relevant questions from the client, understands and defines the objectives for the problem that needs to be tackled. It is a very crucial step as it provides clarity about the current scenario and what is desired. Secondly, it’s the ‘Data Acquisition.’ This includes gathering of data from multiple sources like web servers, API’s, logs, databases, etc. A full-fledged research is carried out. The collected data needs preparation. Data is cleaned and transformed into a more desirable form. Data cleaning is the most time-consuming process as it includes a number of complex operations. Tools like Talend and Informatica are used to perform such complex transformations that helps the data scientist to understand the data structure better.
The fourth and the most important step is ‘Exploratory Data Analysis (EDA).’ It answers ‘what you can actually do with the data.’ With the help of EDA, one can define and refine the selection of feature variables that will be used in the model development. What if we skip this process? We might end up developing an inaccurate model which will not serve our purpose. Next, we proceed towards the ‘model development.’ This is very challenging, as well as interesting at the same time. We use diverse machine learning techniques (KNN, decision tree, Naive Bayes) to develop the best suited model. Data modeling can be done using Python, SAS or R.
Finally, we have our last process, ‘Visualization and Communication.’ The result is now discussed with the clients and explained in an easy to understand way through reports and dashboards. The final model is tested and deployed to the production environment.
That was all about Data Science course. It’s a vast field and finds its application in-
- Better decision making
- Predictive Analysis
- Pattern Discovery
Genomic data provides a deeper understanding of genetic issues and reaction to a particular drug or disease. Logistics companies like DHL, FedEx use data science to predict the best route for delivery, the best suited time and the best mode of transport to have a high cost efficiency. One major area where data science is applied is ‘Airlines.’ Airline companies can easily predict delayed and cancelled flights and inform the passengers beforehand to avoid havoc and inconvenience. Those were a few areas of the application of Data Science and there are numerous others.
Why go for Data Science? It is one of the technologies that has revolutionized our way of living. The average salary of a Data Scientist is from $95000 to $165000. Data Science training is gaining strength and is attracting more and more individuals. It’s worth giving a try!
Learn data science training from 360DigiTMG to broaden your horizon.
Navigate to Address
360DigiTMG – Data Analytics, Data Science Course Training Hyderabad
2-56/2/19, 3rd floor,, Vijaya towers, near Meridian school,, Ayyappa Society Rd, Madhapur,, Hyderabad, Telangana 500081