Big data PPT

Power point Presentation on the topics of Big data highly understandable easily understand
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1. Presentation On Big Data & Hadoop LUCKNOW INSTITUTE OF TECHNOLOGY LUCKNOW Presented By:- Rajendra Prasad ( B.Tech CS IV th Yr. )

2. Terminologies Data Big Data Structured & Unstructured Data Data Generating Factors Cloud Hadoop

3. What is Data? Any type of Raw material for computer. facts and statistics collected together for reference or analysis. Every single step performed on the computer produce Data which may be useful or not. Processing DATA INFORMATION

4. What is Big Data? Data which is beyond to storage capacity or which is beyond to the processing power is termed as big data. Big Data is a phrase used to mean a massive volume of both structured data and unstructured   data  that is so large it is difficult to process using traditional database and software techniques.

5. Structured Data Structured data  is easily searchable by basic algorithms. Data produce by RDBMS is structured data. Example:-Tables Student Name Roll No Mobile RAJ SINGH 1636213006 [phone] VAIBHAV 1636213007 [phone] HAIDER 1636213003 [phone]

6. Unstructured Data Beyond the structured data every Information is Unstructured data. Like FB Produces Videos,Audios,Text,Images .

7. Semi structured Data Log Files Example - gm@il , Yah@@ m@il Person Each time using Total Log files 4 gmail 5 20 5 yahoo 4 20 2 facebook 10 20 Total 60

8. Data Generating Factors Sensors data CCTV Cameras Airlines data Hopitality Data (Hotel, Restaurants and bars)

9. Social Network Online Shopping Data

10. Data Produce By Companies Google (35-40 pb /day) Facebook (20-25 pb /day) You tube (60-80 pb /day) Hence Data size is increasing day by day

11. Example If a firm producing 10 gb of data first day and can process and next day 10 gb can process but it cannot process further due to ROM & Processor capacity. RAM 64-120 mb RAM 4-16 gb ROM 1-10 gb ROM 1-4 tb Data reading Capacity 200 kb/sec Capacity 100 mb Now we have to use HD of different size which is costly and processing takes large amount of time Earlier Computer (90’s) New Generation computers

12. IBM ( In’l Buss.Mach.Corpo . ) Definition Now three problems comes into the picture regarding to this huge amount of data Volume (in GB,TB,PB) Velocity (Speed of Processing) Variety (Structured & Unstructured) These characteristics together called big data.

13. Cloud Now Cloud Server comes into the picture which can keep PB of data on server can process.

14. How to Process Big Data 1000 TB P3 P2 P4 P1

15. Hadoop For reducing the processing time HADOOP comes into the picture. Douge Cutting introduce Hadoop in 2006.

16. Hadoop is an Open Source Java Based software framework sponsored by Apache Software foundation for distributed storage and distributed processing of very large data sets on computer clusters built from commodity hardware. It provides storage for big data at reasonable cost. Hadoop process big data in a single place as in storage cluster.

17. History of Hadoop Hadoop is inspired by Google File System (GFS). Google file System firstly introduce HDFS only on paper work. Yahoo Implement HDFS in 2005-2006. Hadoop introduce HDFS and MapReduce in 2006. GFS Yahoo HDFS HADOOP

18. Hadoop Architecture HDFS ( Hadoop Distributed File System) MapReduce

19. Hadoop Distributed File System HDFS is a file system of storage layer of Hadoop . It only deals with storage. It can store data and can handle very large amount of data. HDFS does not deals with Processing.

20. MapReduce MapReduce is programming framework. It organize multiple computers in a cluster in order to perform the calculations. It take cares of distributing the work between Computers and putting the result together. Hadoop Data Processor Processor Processor Processed Data

21. THANKS …….