BIG DATA ANALYTICS USING R

BIG DATA ANALYTICS
USING R
Analytics is the combination of mathematical, statistical, and heuristic techniques to glean useful insights from data and to implement actions derived from those insights.
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1. BIG DATA ANALYTICS USING R Big Data & IoT Umair Shafique (03246441789) Scholar MS Information Technology - University of Gujrat

2. BIG DATA ANALYTICS USING R

3. TABLE OF CONTENTS: WHAT IS BIG DATA ANALYTICS? DATA SOURCES OF BIG DATA WHY DO WE NEED BIG DATA ANALYTICS? STAGES OF BIG DATA ANALYTICS TYPES OF BIG DATA ANALYTICS TOOLS USED IN BIG DATA ANALYTICS DOMAINS USING BIG DATA ANALYTICS HISTORY OF R ABOUT R LANGUAGE FEATURES OF R REASONS TO LEARN R APPLICATIONS OF R PROGRAMMING INSTALLATION OF R COMPANIES USING R R VS PYTHON SKILLS FOR DATA ANALYST

4. WHAT IS BIG DATA ANALYTICS? Big data analytics is  the often complex process of examining big data to uncover information , such as hidden patterns, correlations, market trends and customer preferences, that can help organizations make informed business decisions . Big data analytics helps businesses to get insights from today's huge data resources. Social media, cloud applications, and machine sensor data  are just some examples.

5. DATA SOURCES OF BIG DATA

6. WHY DO WE NEED BIG DATA ANALYTICS? Making Smarter and More Efficient Organization Optimize Business Operations by Analyzing Customer Behavior Cost Reduction New Generation Products  Detect Risks and Check F rauds  

7. Use Case 1

8. Use Case 2

9. STAGES OF BIG DATA ANALYTICS

10. TYPES OF BIG DATA ANALYTICS

11. 1. Descriptive Analytics

12. 2. Diagnostic Analytics

13. 3. Predictive Analytics

14. 4. Prescriptive Analytics

15. TOOLS USED IN BIG DATA ANALYTICS

16. DOMAINS USING BIG DATA ANALYTICS

17. History OF R R was created by Ross Ihaka and Robert Gentleman in the University of Auckland, New Zealand, 1993. This programming language name is taken from the name of both the developers. The R language was closely modeled on the S Language for Statistical Computing conceived by John Chambers, Rick Becker, Trevor Hastie, Allan Wilks and others at Bell Labs in the mid 1970s. In 1995, statistician Martin Mächler convinced Ihaka and Gentleman to make R  free and open-source software  under the General Public License .

18. About R language R is a interpreted computer programming language. R is a popular choice for data analysis, statistical computing and graphical representation . R is a programming language and software environment for statistical computing and graphics. The R programming language comprises packages and environments making analytics easier.   R can be downloaded and installed from CRAN website , CRAN stands for Comprehensive R Archive Network .

19. Features of R Open source: R is an open source programming language. It is completely free for anybody to use. Varity of packages: There are more than 15,000 packages for R on online repositories like CRAN, GitHub. Powerful Graphics: R’s graphical capabilities are amazing. It can make graphs of any type with its packages. Cross platform support: R is cross platform supportive that can run on any Operating system and any software environment without any hassle. No need for a Compiler: the R is interpreted language. It does not need a compiler to convert the code into a program. Perform Fast Calculation: Through R, you can perform a wide variety of complex operations on arrays, data frames, vectors and other data objects of varying sizes.

20. Reason to learn R Open-source and Free Tool Strong Graphical Capabilities  Highly Active Community A Wide Selection of Packages Comprehensive Environment Can Perform Complex Statistical Calculations Running Code Without a Compiler Interacting with Databases Cross-platform Support 2 Million jobs are opening for R programmer

21. Applications of R Programming R is used in finance and banking sectors for  detecting fraud, reducing customer churn rate and for making future decisions. R is also used by bioinformatics to analyze strands of genetic sequences, for performing drug discovery and also in computational neuroscience. R is used in social media analysis to discover potential customers in online advertising. Companies also use social media information to analyze customer sentiments for making their products better. E-Commerce companies make use of R to analyze the purchases made by the customers as well as their feedbacks. Manufacturing companies use R to analyze customer feedback. They also use it to predict future demand to adjust their manufacturing speeds and maximize profits.

22. Companies Using R Some of the companies that are using R programming are as follows : Facebook Google Ford Twitter ANZ Microsoft

23. INSTALLATION OF R

24. 4.PLOT THE GRAPHS 1. CODE EDITOR 2. HISTORY 3. CONSOLE (COMMAND OUTCOME)

25.   R     PYTHON First appeared in 1993 First appeared in 1991 It has more functions and packages It has less functions and packages It is an interpreter base language It is an interpreter base language It is statistical design and graphics programming language It is general purpose language It is difficult to learn and understand It is easy to understand R is mostly use for data analysis Generic programming, tasks such as design of software  

26. Skills for Data Analyst