Data Analytics powerpoint presentation 1
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Data analytics for module 1 in VTU
Data Analytics powerpoint presentation 1
- 2. Objective of the course • The principle focus of this course is to introduce conceptual understanding using simple and practical examples rather than repetitive and point click mentality. • This course should make you comfortable using analytics in your career and your life. • You will know how to work with real data, and might have learned many different methodologies but choosing the right methodology is important. • The danger in using quantitative methods does not generally lie in the inability to perform the calculations. • The real threat is lack of fundamental understanding of: Why to use a particular technique of procedure How to use it correctly How to correctly interpret the result.
- 3. Learning objectives 1. Define data and its importance. 2. Define data analytics and its types. 3. Explain why analytics is important in today’s business environment. 4. Explain how statistics, analytics and data science are interrelated. 5. Why python? 6. Explain the four different levels of data. Nominal Ordinal Interval Ratio
- 4. 1. Define data and its importance • Variable, measurement and data • What is generating so much data? • How data add value to the business? • Why data is important?
- 5. 1.1 Variable, Measurement and Data • Variable- is a characteristic of any entity being studied that is capable of taking on different values. • Measurement- is when a standard process is used to assign numbers to particular attributes or characteristics of a variable. • Data- data are recorded measurements.
- 6. 1.2 What is generating so much of data? • Data can be generated by, Humans Machines Human-machine combines. • It can be generated anywhere any information is generated and stored in structured or unstructured formats
- 7. 1.3 How data add values to business Data Warehouse of data Development of data product Algorithm solutions in production, marketing and sales etc..(e.g. Recommendation Engines) Discovery of data insight Quantitative data analysis to help steer strategic business decision Business Value
- 8. 1.4 Why data is important • Data helps in make better decisions • Data helps in solve problems by finding the reason for underperformance. • Data helps one to evaluate the performance. • Data helps one improve processes • Data helps one understand consumers and the market.
- 9. 2. Define data analytics and its types • Define data analytics • Why analytics is important? • Data analysis • Data analytics vs. data analysis • Types of data analytics.
- 10. 2.1 Define data analytics • Analytics is defined as “the scientific process of transforming data into insights for making better decisions. • Analytics, is use of data, information technology, statistical analysis, quantitative methods and mathematical or computer based models to help managers gain improved insight about their business operations and make better, fact based decisions-James Evans
- 11. 2.2 Why analytics is important? • Opportunities abounds for the use of analytics and big data such as: Determining credit risk Developing new medicines Finding more efficient ways to deliver products and services Preventing fraud Uncovering cyber threats
- 12. 2.3 Data Analysis • It is a process of examining, transforming and arranging raw data in a specific way to generate useful information from it. • Data analysis allows for the evaluation of data through analytical and logical reasoning to lead to some sort of outcome or conclusion in some context. • Data analysis is a multi-faceted process that involves a number of steps, approaches and diverse techniques.