Data Warehousing

Lot of my friends and reader asking me to write a tutorial related to Microsoft BI tools. As I personally feel that the Data Warehousing is not just understand or practice via some Tools provided by Microsoft, it need deep understanding analysing with data. Well we can learn the tools very easily but sensing the data and information is quite tough to learn. It’s growing with maturity and hard work. 

Well if readers want me to write something, here I am trying to give them something by my article.

In this article I am trying to understand the concept behind data ware housing. Why we all think about it.

What is the Data Warehousing?

One of the main features of data warehousing is to combining data from heterogeneous data sources into one comprehensive and easily maintained database.

The common accessing systems of data warehousing includes


 Queries


Analysis


Reporting

As the number of source can be anything, the data warehouse creates one database at the end. The final result however, is homogeneous data, which can be more easily manipulated.

Data warehousing is commonly used by companies to analyse trends over time. Its primary function is facilitating strategic planning resulting from long-term data overviews. From such overviews, business models, forecasts, and other reports and projections can be made. Routinely, because the data stored in data warehouses is intended to provide more overview-like reporting, the data is read-only. If you want to update the data stored via data warehousing, you'll need to build a new QUERY when you're done.

We are not saying that data warehousing involves data that is never updated. On the contrary, the data stored in data warehouses is updated all the time. It's the reporting and the analysis that take more of a long-term view.

Data warehousing is not the be-all and end-all for storing all of a company's data. Rather, data warehousing is used to house the necessary data for specific analysis. More comprehensive data requires different capacities that are more static and less easily manipulated than those used for data warehousing.

Data warehousing is typically used by larger companies analysing larger sets of data for enterprise purposes.

Smaller companies wishing to analyse just one subject, for example, usually access data marts, which are much more specific and targeted in their storage and reporting. Data warehousing often includes smaller amounts of data grouped into data marts. In this way, a larger company might have at its disposal both data warehousing and data marts, allowing users to choose the source and functionality depending on current needs.

Hope you like it. In my next session I am directly jump over Microsoft BI tools Introduction and try to discuss when you used them.

Hope you like it.

Posted by: MR. JOYDEEP DAS