Exploring Data Analysis
- 2. What is?
- 3. • Data analysis is a process of inspecting, cleansing, transforming, and modeling data with the goal of discovering useful information, informing conclusions, and supporting decision-making. • Data analysis is a primary component of data mining and Business Intelligence (BI) and is key to gaining the insight that drives business decisions. Organizations and enterprises analyze data from a multitude of sources using Big Data management solutions and customer experience management solutions that utilize data analysis to transform data into actionable insights.
- 4. Importance and Purpose of Data Analysis
- 5. •It is important to first clearly understand for whom and for what purpose you are conducting the analysis. It is essential because analytics assist humans in making decisions. •Data analysis is a process of applying statistical to organize, represent, describe, evaluate, and interpret data. The process of evaluating data using analytical and logical reasoning to examine each component of the data provided. •To do this effectively, Data Analysts need to be able to: Understand business direction and objectives.
- 6. Model of Data Analysis 1. Decide on the Objectives 2. Identify Business Levers 3. Data Collection 4. Data Cleansing 5. Grow a Data Science Team 6. Optimized (Enhance) 7. Repeat
- 7. • Proven way for organization and Enterprises to gain the info. to make better decision • Serves Customers, increases Productivity & Revenue • Getting Right info for Business, Value out of IT, and more Effective Marketing Campaigns • So much data available • Namely, handling and presenting all of the data are two of the most challenging aspects of data analysis • Traditional architectures and infrastructures are not able to handle the sheer amount of data that is being generated • Takes longer than expected to get actionable insight from the data for decision maker.
- 9. • Data management and customer experience management solutions give enterprises the ability to listen to customer interactions, learn from behavior and contextual information. • Create more effective actionable insights, and execute more intelligently on insights in order to improve and involve targets and business practices.
- 10. Allstate P & C, Life Insurance Company
- 11. Case Brief : Allstate has more than one Auto products compare to other insurance carriers in Market. Main goal of company to sell more insurance and inexpensive compare to their competitors. Company focusing on different segments of insurance. Business Requirement- company wanted to raise sales by offering certain types of insurance to certain market. Short Term Goal: offer Drive wise auto insurance to all insured Mid Term Goal: offer more mile wise auto insurance to selected insured who qualifies. Long Term Goal: TBD
- 12. Technical Approach/ Recommendation - Target on customers who drives less mileages by offering Mile wise product vs Traditional(Drive wise) product. Product Detail: mile wise - pay as drive(drive less- pay less), Drive wise- traditional 6 month policy Market Detail: offer product to retired, work from home and commuters
- 13. Now I am working at IEEE as a “Data Quality Associate”. I have complete understanding of data Accessibility and Retrieval from Clouds and Big Data based- data information. I will be delighted to get an opportunity to advance my knowledge.