Data
warehousing
A data warehouse is a relational database that is designed
for query and analysis rather than for transaction processing. It usually
contains historical data derived from transaction data, but it can include data
from other sources. It separates analysis workload from transaction workload
and enables an organization to consolidate data from several sources.
In addition to a relational database, a data warehouse
environment includes an extraction, transportation, transformation, and loading
(ETL) solution, an online analytical processing (OLAP) engine, client analysis
tools, and other applications that manage the process of gathering data and
delivering it to business users.
Data warehouses are designed to help you analyze data. For
example, to learn more about your company's sales data, you can build a
warehouse that concentrates on sales. Using this warehouse, you can answer
questions like "Who was our best customer for this item last year?"
This ability to define a data warehouse by subject matter, sales in this case
makes the data warehouse subject oriented.
Integration is closely related to subject orientation. Data
warehouses must put data from disparate sources into a consistent format. They
must resolve such problems as naming conflicts and inconsistencies among units
of measure. When they achieve this, they are said to be integrated.
In order to discover trends in business, analysts need large
amounts of data. This is very much in contrast to online transaction processing (OLTP)
systems, where performance requirements demand that historical data be moved to
an archive. A data warehouse's focus on change over time is what is meant by
the term time variant.
DATA
WAREHOUSING ARCHITECTURE
DATA
WAREHOUSING TRAINING @ DUCAT
We are providing Real Time & Practical Hands-on Data Warehousing training ( Informatica, Cognos , OBI EE ,
QlikView, Data Stage, Tera Data, ETL Testing) at affordable cost. We
teach Data Warehousing Informatica Training courses with real time scenarios
and give interview guidance. Join us to shape your career in Data
Warehousing (DWH). This course provides the basic & advanced
skills and knowledge for developers new to Informatica Power Center need to
implement data integration projects, exposing core features of Power Center
through lecture and hands-on exercises. In addition to gaining tremendous
insight into the data integration platform, Participants shall be exposed to
Data Warehouse - Informatica Best Practices, troubleshooting techniques, Test
Cases and the use of technical support options like session logs.
ADVANTAGES
OF DATA WAREHOUSING COURSE
By providing data from various sources, managers and executives will no longer need to make business decisions based on limited data or their gut. In addition, “data warehouses and related BI can be applied directly to business processes including marketing segmentation, inventory management, financial management, and sales.”
A Data Warehouse Saves Time
Since business users can quickly access critical data from a number of sources—all in one place—they can rapidly make informed decisions on key initiatives. They won’t waste precious time retrieving data from multiple sources.
Not only that but the business execs can query the data themselves with little or no support from IT—saving more time and more money. That means the business users won’t have to wait until IT gets around to generating the reports, and those hardworking folks in IT can do what they do best—keep the business running.
A Data Warehouse Enhances Data Quality and Consistency
A data warehouse implementation includes the conversion of data from numerous source systems into a common format. Since each data from the various departments is standardized, each department will produce results that are in line with all the other departments. So you can have more confidence in the accuracy of your data. And accurate data is the basis for strong business decisions.
A Data Warehouse Provides Historical Intelligence
A data warehouse stores large amounts of historical data so you can analyze different time periods and trends in order to make future predictions. Such data typically cannot be stored in a transactional database or used to generate reports from a transactional system.
A Data Warehouse Generates a High ROI
Finally, the piece de resistance—return on
investment. Companies that have implemented data warehouses and complementary
BI systems have generated more revenue and saved more money than companies that
haven’t invested in BI systems and data warehouses.
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