Power BI Blog: Datamarts – Part 3

Welcome back to this week’s edition of the Power BI
blog series.  This week, we
look at the differences between a datamart and
a data warehouse.


Datamarts are
self-service analytics solutions, enabling users to store and explore data that
is loaded in a fully managed database. 
Since datamarts are usually a subset of the full database, teams can be given access to the information they
require only, enabling them to share relevant data and insights within those

Last week, we
looked at the most common forms of datamarts. 
This week, let’s consider the differences between datamarts and data

A data warehouse is a vast, centralised
repository of data that contains data from multiple sources within a company.  Through analysis, reporting, and data mining
technologies, this collected data is utilised to drive corporate decisions.

A datamart, however, is a single
source of data for just one department (e.g. sales, customer services or
marketing).  The following table
summarises the main differences:

Datamarts can be created to reduce the processing time that would
be required to perform analytics against an entire data warehouse.  Since datamarts in Power BI may be maintained
by Power BI users, rather than the IT department, changes can be applied more
quickly without waiting for tasks to be queued for action by the IT department.

Next time,
we will begin to explore the preview of datamarts in Power BI.


Check back next week for more Power BI tips
and tricks!

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