Step III
Required Tools & Frameworks
1. For Business Intelligence
- SAP Business Objects
- Datapine
- Microstrategy
- SAS Business Intelligence
2. Statistical Analytical Tools
3. Automation Tools
- DataRobot
- Darwin
- RapidMiner
- Automatic Business Modeler (ABM)
4. Data Modeling Tools
- ER/Studio
- Lucid chart
- SQL Database Modeler
- Erwin Data Modeler
5. Web Scrapping Tools
- Beautiful Soup
- IXML
- MechanicalSoup
- Selenium
- Scrapy
6. Machine Learning & Predictive Analysis Tools
7. Deep Learning Tools
- TensorFlow
- PyTorch
- Keras
8. Artificial Intelligence Tools
9. Data Visualization
- QlikView
- Zoho Analytics
- Infogram
- D3js
- Datawrapper
10. Frameworks & Libraries
How to Switch Your Career to Data Science?
Undeniably, Data science has become one of the hottest industries over the past few years from now. Being dominant in almost every sector, data science is powering up businesses (small-mid-large) and helping them in making business decisions and that’s what makes it special and demand is rising like a storm in the market for such professionals. In fact, people with no such background have also taken their way toward data science and by going through different processes many have made a career transition.
Data Science is the study of data using tools and technologies to build predictive models and derive meaningful information. Career transition helps you in getting a “Handsome Salary” and alongside expanding your knowledge in various sectors. This is something called A Good Call. Now, the question arises, if you’re already working in some domain then “How to switch your career in Data Science?” and to make your way smooth and provide you in-depth details, we have drafted this article that will guide you through all the way so that you can start your new path towards data science.