Data analytics is the process of examining data sets in order to draw conclusions about the information they contain. It enable organizations to make more-informed business decisions keeping all the aspects of analytics in mind. There is a step by step process in Data Analytics which assists the business to know their existing strategies’ loopholes and lapses. Data Analytics can act as a tool for the Data Analysts rather than a trouble. The depths of Data Analytics can amaze you to the extent of starting your own business with Data Analytics as your partner. To realize and accept the true nature and power of DA we have dwell into it.
Data analytics is primarily conducted in business-to-consumer (B2C) applications. Global organizations collect and analyze data associated with customers, business processes, market economics or practical experience. Data is categorized, stored and analyzed to study purchasing trends and patterns.
Evolving data facilitates thorough decision-making. For example, a social networking website collects data related to user preferences, community interests and segment according to specified criteria such as demographics, age or gender. Proper analysis reveals key user and customer trends and facilitates the social network’s alignment of content, layout and overall strategy.
Syllabus of Data Analytics
- Warming up
- Setting up machine
- The basics of Python language
- Regular Expressions in Python
- Scientific libraries in Python – NumPy, SciPy, Matplotlib and Pandas
- Effective Data Visualization
- Scikit-learn and Machine Learning
- Practice and deep learning