Data LifeCycle Analysis
We think data is crucial in today’s digital world and we belive that the future will be data driven. As it gets created, consumed, tested, processed, and reused, data goes through several phases and stages during its entire life. A data analytics architecture maps out such steps for data science professionals. It is a cyclic structure that encompasses all the data life cycle phases, where each stage has its significance and characteristics.
The lifecycle’s circular form guides data professionals to proceed with data analytics in one direction, either forward or backward. Based on the newly received information, professionals can scrap the entire research and move back to the initial step to redo the complete analysis as per the lifecycle diagram for the data analytics life cycle.
Data analytics are being used by medium to large-scale businesses throughout the world to achieve great success.
- The king of online retail, Amazon, accesses consumer names, addresses, payments, and search history through its vast data bank and uses them in advertising algorithms and to enhance customer relations.
- Many investment banks like Amex and JP morgan chase and many more use big data to study consumer behavior.
- Netflix leverages big data to understand the viewing preferences of users from around the world.
Data Analysing is used to effciently used for
- Customer Loyalty and Retention
- Targeted and Specific Promotions
- Identification of Potential Risks
- Boost Performance
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