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Group Members
R.Sebasteen Kishore 12PCA118
J.Kalaimani 12PCA120
Source :
Big data for dummies – Alan Nugent
www.slideshare...
Big data is the capability to manage a
huge volume of disparate data, at the
right speed, and within the right time
frame ...
Volume : How much data
Velocity : How fast that data
is processed
Variety : The various types of
data
VOLUME
VELOCITY
VARI...
Big Data Warehouse :
 A process of transforming data into information and
making it available to users in a timely enough...
Data warehouse included the following
characteristics:
 It should be organized so that related events are linked
together...
 Big data and data warehousing share the same basic goals : to
deliver business value through the analysis of data.
 How...
Traditional Data Warehouse :
 Complete record from transactional system.
 All data centralized
 Addition every month/da...
Data flows for traditional warehouse :
Changing the Role of the Data Warehouse :
It is useful to think about the similarities and differences between the way
dat...
Differences between the traditional data warehouse and big
data include :
The distributed computing model of big data wil...
Big data stores will provide the capability to analyse
huge volumes of data in near real time.
A big data store will take ...
Bigdata warehouse
Bigdata warehouse
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Bigdata warehouse

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Bigdata warehouse

  1. 1. Group Members R.Sebasteen Kishore 12PCA118 J.Kalaimani 12PCA120 Source : Big data for dummies – Alan Nugent www.slideshare.com
  2. 2. Big data is the capability to manage a huge volume of disparate data, at the right speed, and within the right time frame to allow real-time analysis and reaction.
  3. 3. Volume : How much data Velocity : How fast that data is processed Variety : The various types of data VOLUME VELOCITY VARIETY
  4. 4. Big Data Warehouse :  A process of transforming data into information and making it available to users in a timely enough manner to make a difference  Data had to be gathered from a variety of relational database sources ,  And then ensured that the metadata was consistent, and that the data itself was clean and then well integrated.
  5. 5. Data warehouse included the following characteristics:  It should be organized so that related events are linked together.  The information should be non-volatile so that it cannot be inadvertently changed.  Information in the warehouse should include all the applicable operational sources. The information should be stored in a way that has consistent definitions and the most up-to-date values.
  6. 6.  Big data and data warehousing share the same basic goals : to deliver business value through the analysis of data.  However, big data and data warehousing differ in the scope of their data  Big data is in many ways an evolution of data warehousing. To be sure, there are new technologies used for big data, such as Hadoop and “nosql” databases.  The majority of business users will access the data in this information architecture from the data warehouse, using SQL- based environments. The Evolution of data warehousing :
  7. 7. Traditional Data Warehouse :  Complete record from transactional system.  All data centralized  Addition every month/day of new data  Analytics designed against stable environment  Many reports run on a production basis
  8. 8. Data flows for traditional warehouse :
  9. 9. Changing the Role of the Data Warehouse : It is useful to think about the similarities and differences between the way data is managed in the traditional data warehouse and when the warehouse is combined with big data. Similarities between the two data management methods include :  Requirements for common data definitions  Requirements to extract and transform key data sources  The need to conform to required business processes and rules
  10. 10. Differences between the traditional data warehouse and big data include : The distributed computing model of big data will be essential to allowing the hybrid model to be operational. The big data analysis will be the primary focus of the efforts, while the traditional data warehouse will be used to add historical and transactional business context.
  11. 11. Big data stores will provide the capability to analyse huge volumes of data in near real time. A big data store will take the results of an analysis and provide a mechanism to match the metadata of the big data analysis to the requirements of the data warehouse.

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