the evolution of enterprise data warehouse
DESCRIPTION
A Design to store data methodically. A Cohesive Storage Platform. Data captured from disparate sources. A Central Repository of data. The intent is to allow easy access of data for Reporting, Data analysis, PredictionsTRANSCRIPT
The Evolution of
Enterprise Data Warehouse
SPEC INDIA
Terabytes to Petabytes
Data Storage - A Long Sojourn
How Data Storage changed over the years Gigabytes
Floppy Disks CDs DVDs Hard Disk Drives
Terabytes Petabytes Zettabytes Exabytes
Data WarehouseThe Powerful Combination
Big Data Data Storage for different types of data
Business Intelligence Intelligent & Meaningful Data Interpretation
The Data Collection
1 GB = 1,000 Megabytes (MB)
1 TB = 1,000 Gigabytes (GB)
1 PB = 1,000 Terabytes (TB)
1 EB = 1,000 Petabytes (PB)
1 Zettabyte (ZB) = 1,000 Exabytes (EB)
What is Enterprise Data Warehouse?
A Design to store data methodically A Cohesive Storage Platform Data captured from disparate sources A Central Repository of data The intent is to allow easy access of data for
Reporting Data analysis Predictions
The Magicians
in the Enterprise Data warehouse
The Enterprise Data Warehouse or EDW itself evolved as requirements, prudence and hardware capacities along with the devices increased over the years Data mart Online Analytical Processing Online Transaction Processing Predictive Analysis
EDW The Complete Package
•This is a single subject data warehouse focusing on typically only one department or subject matter, making it the most simple one to implement
Data mart
•This low volume of transaction processing system gives answers to queries are generally very exhaustive and complex in nature involving logical aggregations.
Online Analytical Processing (OLAP)
•Very fast query processing with short transactions are significant features of this system.
•The most critical aspect is maintaining data integrity in multi-access environments
Online Transaction Processing (OLTP)
•The future teller, the Oracle of the database. •Using complex mathematical and logical reasonings, Predictive Analysis tools finds the hidden meaning in the data to predict the future.
Predictive Analysis
Big Data The data that we have been collecting over the years is
very big & is rightly called BIG data BIG Data
A large volume of unstructured data which cannot be handled by other Database Management systems
Uses statistical inference to determine facts from a large volume o f data Regressions Nonlinear Relationships Data Dependencies
Business Intelligence BI uses descriptive statistics or statistical analysis with
the data collected to interpret the hidden meanings Transforms raw data into meaningful and useful
information for business analysis Interpretations to identify new opportunities and
develop new strategies for businesses Combines the power of Predictive Analysis Tools to put
the theories of probability and predictions to use
In a Nutshell…..Enterprise Data Warehouses augment themselves with concepts like BI and BIG Data to get a more
complete picture of the past, present and the future of the data
