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Data Analytics For Beginners | Introduction To Data Analytics | Data Analytics Using R | Edureka
The document outlines a data analytics master program offered by Edureka, covering topics such as data cleaning, statistics, data visualization, and machine learning. It details the roles and responsibilities of a data analyst, required skills, and provides insights into salary expectations. Additionally, it emphasizes the significance of data analytics in generating insights and improving business processes.
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Introduction to various aspects of data analytics including roles, tools, and importance.
Statistics is crucial for data analysis involving descriptive and inferential methods for data evaluation.
Focuses on data cleaning (correcting errors) and data manipulation (organizing data for analysis).
Covers data visualization methods such as charts and graphs to represent data effectively.
Machine learning automates analysis and prediction without explicit programming, enhancing data use.
Details the responsibilities of data analysts and presents average salary data for the US and India.
R’s capabilities in data analysis: open-source, flexibility, and cross-platform benefits.
Encouragement for practical experience with data analysis to enhance learning and insights.
Overview of courses including Statistics, Data Visualization, and Machine Learning offered over weeks.
Further training options available in topics like R Programming, Decision Trees, and Predictive Modeling.
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Data Analytics For Beginners | Introduction To Data Analytics | Data Analytics Using R | Edureka
- 2. Data Analytics MasterProgram www.edureka.co/masters-program/data-analyst-certification Topics For Today’s Session Introduction To Data Analytics Data Cleaning and Manipulation Statistics Data Visualization Machine Learning Roles, Responsibilities & Salary Hands-On
- 3. Copyright © 2018,edureka and/or its affiliates. All rights reserved. Introduction To Data Analytics
- 4. Data Analytics MasterProgram www.edureka.co/masters-program/data-analyst-certification Why Data Analytics? Gather Hidden Insights01 Generate Reports 02 Perform Market Analysis03 Improve Business Requirement 04
- 5. Data Analytics MasterProgram www.edureka.co/masters-program/data-analyst-certification What is Data Analytics? Data Analytics refers to the techniques to analyse data to enhanced productivity and business gain. Business Administration Exploratory Data Analysis Growth in Business
- 6. Data Analytics MasterProgram www.edureka.co/masters-program/data-analyst-certification Who is a Data Analyst? Collect Data Analyse Data Create Reports
- 7. Data Analytics MasterProgram www.edureka.co/masters-program/data-analyst-certification Data Analyst Skills Statistics Data Cleaning EDA Data Visualization Machine Learning
- 8. Copyright © 2018,edureka and/or its affiliates. All rights reserved. Statistics
- 9. Data Analytics MasterProgram www.edureka.co/masters-program/data-analyst-certification Statistics Statistics is a branch of mathematics dealing with data collection and organization, analysis, interpretation and presentation. Analyse Data Build a Model Infer Result
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- 11. Data Analytics MasterProgram www.edureka.co/masters-program/data-analyst-certification Categories in Statistics – Descriptive Statistics Descriptive Descriptive statistics uses the data to provide descriptions of the population, either through numerical calculations or graphs or tables. Characteristics of Data Descriptive Statistics
- 12. Data Analytics MasterProgram www.edureka.co/masters-program/data-analyst-certification Categories in Statistics – Descriptive Statistics Descriptive There are mainly two measures you need to understand in Descriptive Statistics. Measures of Centre01 Measures of Spread 02
- 13. Data Analytics MasterProgram www.edureka.co/masters-program/data-analyst-certification Descriptive Statistics – Measures of Centre Descriptive There are 3 terms, you have to understand in Measures of Centre. Mean Measure of average of all the values in a sample is called Mean. 110 + 110 + 93 + 96 + 90 + 110 + 110 + 110 8 = 103.625
- 14. Data Analytics MasterProgram www.edureka.co/masters-program/data-analyst-certification Descriptive Statistics – Measures of Centre Descriptive There are 3 terms, you have to understand in Measures of Centre. Measure of average of all the values in a sample is called Mean. 110 + 110 + 93 + 96 + 90 + 110 + 110 + 110 8 = 103.625 Measure of the central value of the sample set is called Median. 21,21,21.3,22.8,23,23,23,23 22.8+23 2 = 22.9 Measure of the central value of the sample set is called Median. 21,21,21.3,22.8,23,23,23,23 22.8+23 2 = 22.9 Median
- 15. Data Analytics MasterProgram www.edureka.co/masters-program/data-analyst-certification Descriptive Statistics – Measures of Centre Descriptive There are 3 terms, you have to understand in Measures of Centre. Measure of average of all the values in a sample is called Mean. 110 + 110 + 93 + 96 + 90 + 110 + 110 + 110 8 = 103.625 Measure of the central value of the sample set is called Median. 21,21,21.3,22.8,23,23,23,23 22.8+23 2 = 22.9 Measure of the central value of the sample set is called Median. 21,21,21.3,22.8,23,23,23,23 22.8+23 2 = 22.9 Mode The value most recurrent in the sample set is known as Mode. 21,21,22,23,24,25,25,25,26 Mode - 25
- 16. Data Analytics MasterProgram www.edureka.co/masters-program/data-analyst-certification Descriptive Statistics – Measures of Spread Descriptive Range Range is the given measure of how spread apart are the values in a dataset. Range = Max(𝑥𝑖) - Min(𝑥𝑖) Inter Quartile Range Inter Quartile Range(IQR) is the measure of variability, based on dividing a dataset into quartiles. 1 2 3 4 5 6 7 8 Q1 Q2 Q3 Variance Variance describes how much a random variable differs from its expected value. It entails computing squares of deviations. Standard Deviation Standard Deviation is the measure of the dispersion of a set of data from its mean. 𝑖=1 𝑁 =(𝑥𝑖−𝜇)² 1 𝑁
- 17. Data Analytics MasterProgram www.edureka.co/masters-program/data-analyst-certification Categories in Statistics – Inferential Statistics Descriptive Inferential Inferential Statistics generalizes a large dataset and applies probability to draw a conclusion. It allows us to infer data parameters based on a statistical model using a sample data. Statistical Model Inferential Statistics Start Process Step Decision Answer
- 18. Data Analytics MasterProgram www.edureka.co/masters-program/data-analyst-certification Inferential Statistics – Hypothesis Testing Descriptive Inferential Statisticians use hypothesis testing to formally check whether the hypothesis is accepted or rejected. State the Hypotheses – This stage involves stating the null and alternative hypotheses. Formulate an Analysis Plan – This stage involves the construction of an analysis plan. Analyse Sample Data – This stage involves the calculation and interpretation of the test statistic as described in the analysis plan. Interpret Results – This stage involves the application of the decision rule described in the analysis plan. Hypothesis testing is conducted in the following manner:
- 19. Data Analytics MasterProgram www.edureka.co/masters-program/data-analyst-certification Descriptive vs Inferential Statistics Descriptive Statistics Inferential Statistics Concerned with Properties of Population Makes inferences from the sample Presents data in a meaningful manner Compares and predicts the future outcomes Outcomes are shown in form of charts, tables and graphs Outcomes are in the form of probability scores Describes the known data Tries to make conclusions beyond the data available Measures of central tendency and spread of data Hypothesis Testing and Analysis of variance.
- 20. Copyright © 2018,edureka and/or its affiliates. All rights reserved. Data Cleaning and Manipulation
- 21. Data Analytics MasterProgram www.edureka.co/masters-program/data-analyst-certification Data Cleaning and Manipulation Data Cleaning The process of detecting and correcting corrupt or inaccurate records from a database is said to be Data Cleaning. Data Manipulation The process of changing data to make it more organized and easy to read is known as Data Manipulation.
- 22. Copyright © 2018,edureka and/or its affiliates. All rights reserved. Data Visualization
- 23. Data Analytics MasterProgram www.edureka.co/masters-program/data-analyst-certification Data Visualization Data Visualization is the representation of data inform of charts, diagram etc. Bar Graph Scatter Plot Pie Chart Box Plot Line Graph
- 24. Copyright © 2018,edureka and/or its affiliates. All rights reserved. Bonus: Machine Learning
- 25. Data Analytics MasterProgram www.edureka.co/masters-program/data-analyst-certification Machine Learning Machine Learning is a concept which allows the machine to learn from examples and experience, and that too without being explicitly programmed.
- 26. Data Analytics MasterProgram www.edureka.co/masters-program/data-analyst-certification Data Analyst: Roles and Responsibilities Determining Organizational Goals Mine Data Data Cleaning Analyzing Data Pinpointing Trends and Patterns Creating Reports with Visualizations
- 27. Data Analytics MasterProgram www.edureka.co/masters-program/data-analyst-certification Salary of Data Analyst Average Salary (US) Average Salary (IND) $83,878 ₹404,660
- 28. Copyright © 2018,edureka and/or its affiliates. All rights reserved. Need of R
- 29. Data Analytics MasterProgram www.edureka.co/masters-program/data-analyst-certification Need of R R is open-source and freely available. R is cross-platform compatible. R is a powerful scripting language. R is highly flexible and evolved.
- 30. Copyright © 2018,edureka and/or its affiliates. All rights reserved. Hands-On
- 31. Data Analytics MasterProgram www.edureka.co/masters-program/data-analyst-certification Hands-On To perform data analysis on the below data set and gather some insights.
- 32. Data Analytics MasterProgram www.edureka.co/masters-program/data-analyst-certification Data Analytics @edureka Program Starts 2nd Week 7th Week 15th Week 11th Week 01 02 03 04 Statistics Essentials Probability Bayesian Interference Regression Making Statistics Data Analytics with R Data Manipulation Exploratory Analysis Regression Data Visualization Data Mining Sentiment Analysis SAS Training Advanced Statistical Techniques SAS Macros PROC SQL SAS ODS Advanced SAS Procedures Tableau Training LOD Expressions Tableau Desktop Tableau Public Data Visualization Integration with R Graduated as Data Analyst Self-Paced Instructor - Led
- 33. Data Analytics MasterProgram www.edureka.co/masters-program/data-analyst-certification Data Analytics @edureka QlikView Certification Training Advanced MS Excel 2010 R Programming Certification Training Analytics for Retail Banks Decision Tree Modelling Using R Certification Training Machine Learning with Mahout Certification Training Advanced Predictive Modelling in R Certification Training