Time easily expand and join with other data sources

Time is money they say, and it today’s fast changing and
volatile world it does make sense. And no matter how big is the company,
managing data is now the foremost challenge that companies has to face. As the
cost of storing data is getting cheaper, industries have minted huge amount of
data which they want to store and use in an efficient and productive ways. Be
it banking, consultancy, heavy engineering industries or a small boutique,
almost every transaction has to be reported. Global giants are leveraging
organizational level data to enhance asset health, capture markets, improve
productivity and drive business performance. Business data warehousing, with
the help of other BI tools, is one stop solution for managing data.

A data warehouse is a spreadsheet which is build on an
appropriate database which further can be easily expand and join with other
data sources and it can efficiently filter data according to various dimensions
and metrics which further can be put to visualizations. (Silva,2017)

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A data warehouse is a “a relational database” which is
constructed for query and analysis instead of transaction processing.
(Walker,2015). It consists of historical data extracted from transaction data,
though it can accommodate data from other sources. (Walker,2015). Analysis
workload is isolated form transaction workload in data warehouse. (Walker,2015)

Vendors like Teradata, Oracle,
Cloud era etc provide the platform for data warehouse and any company, which
are looking to start or upgrade their data warehouse capabilities can approach
them.  

One of the client of Teradata,
Coca-Cola Company is taking benefit of data warehousing.  To take advantage from huge amount of
structured data, which is piling every day, for making quick decision, good
strategy and predict outcomes, Coca-Cola started a data warehousing project. And
the firm now prides itself on another beverage – Minute maid.  They have made
algorithm known as “Black Book” which systemize mother nature. Having data on
over 600 flavors that makes an orange, including its sweetness, acidity etc of
every lot of juice,  the algorithm give
instructions on how to mix the juice to get the same taste every time. Further,
it can analyse weather plan, crops etc to make changes in juicing plans.

Another example is
BMW who introduced
Teradata’s Agile Information Platform (AIP). In
course of its working, BMW used it’s logical data model for transport and
logistics sector which helped the team to smoothly start the designing of their
data warehouse, to make a blueprint for AIP’s data architecture.

Image at left shows the various BI(Business Intelligence)
tools used in
data warehousing.

Lately, most of the industries are shifting
their data to the cloud to make it cost effective and more accessible. The concept
of big data and cloud computing are getting popularized and offering industries
power for quick, easy and overall data access.

 

One such example is of global giant – General Electric,
which leverages the concept of data warehouse for its in house cloud based
operating system – Predix.