Enabling Business Intelligence (BI) - OLAP
application that makes it very easy and effortless to
analyze your Microsoft® Access® database in multiple
dimensional views, and get useful insights and sense out of
your enormous relational data.
OLAP Statistics & Reportingfor Microsoft® Access enables you to connect to a
fact table (and their related tables, if available)
from an Access database and select fields of
interest, and then explore them in a
multi-dimensional grid, pivot tables, filters, graph
or chart view. With the capability of complex
calculations, trend analysis and sophisticated data
modelling, and reporting, it helps you to identify
critical information on your not so obvious data.
Note: You can also refer to the video demonstration hosted on our site
Works with most version of
Microsoft Access databases -
Save OLAP cube schema (*.olapschema)
and re-use it for subsequent
operations to generate cube from the
Support almost all data types in MS
Choose your own fields
from the fact/transaction table and their
related tables and set them as measures or
dimensions for the OLAP cube.
following functions for Measures -
Count, Distinct Count, Max, Min,
Average, Sum etc.
most of the common OLAP operations
including slice and dice,
drill down, roll up, and
pivoting on the cube.
date/time fields to be summarized or
broken down to year, month, day,
week, hours, minutes etc.
own composite hierarchy.
Eg. Country > State > City
own calculated member
relationship. Eg. Total Sales = (UnitPrice
X Quantity) + Freight
Gridand Chart with highly
interactive, customizable and user
pivot details to file (*.olapreport)
to make it easy for later retrieval
and use without requiring to start
offline cube (to *.offlinecube
in compressed or uncompressed
format) for use in
control over the export settings
of the grid/chart reports.
License is valid
life-time. However, technical assistance and
free upgrades are bound to the validity of the Support and Maintenance
Free license for Academic
Institutions (Schools, Colleges and Universities) -
Learn More... 50% discount for non-profit, non-academic organizations (e.g.,
Need for Business Intelligence
Often you would want to get a bigger picture of your
business, to see broader trends based on aggregated data,
and to see these trends broken down by any number of
variables. For example, here are some types of questions
about your business data, that OLAP and business
intelligence can help to answer:
How do the total
sales of all products for 2009 compare with the
total sales from 2008?
How does our
profitability of 2009 compare with that of 2007 and
What are the
spending patterns for customers of different age
groups in the last 5 years? Has that behavior
changed over time?
How many products
were sold per country, state and city this year as
opposed to last year?
For each buyer age
group, what is the breakdown of profitability (both
margin percentage and total) by product category
Find top and bottom
sales people, distributors, vendors, clients,
partners, or customers.
Purpose of this tool
For Access database,
there is no inbuilt OLAP tool in Access that one can use to
analyze aggregated and summarized data. Traditional query
(Or OLTP) is slow in aggregation task, provides limited
interactivity, and reporting is well suited to handle
textual information mostly. Moreover, complex calculation
are oftem difficult to implement. In short, there are major
drawbacks with regards to answering, analysis and reporting
with Access database. One can use Microsoft Excel to create
an OLAP cube, and analyze it. But the process is cumbersome,
and present a learning curve, for average workers and
OLAP Statistics & Reporting is perfectly suited
for this purpose, and allows you to define any field
as the measure with different function - sum, count,
distinct count, maximum, minimum etc, against which
statistics is to be executed. Now it’s easier than
ever to spot new trends and discover unknown
problems in your data flow.
How does it work?
From the OLAP Statistics Manager, you can connect
to an Access database (*.mdb, *.accdb) and then
select a particular table, typically, a fact or
transaction table, to show up all the available
fields defined for that table (and their related
source tables via the foreign key).
For this example, we are connecting to the 'Order
Details' transaction table of the
Northwind Traders sample database (nwin.mdb),
the schema of which is given on the right:
In the OLAP Access Manager (below), notice that all other fields from
related tables (linked through foreign keys) such as
Orders, Products, Categories etc. are automatically
pulled out, for inclusion into the cube.
Once you have chosen which fields or dimensions to
include in the statistic, you can select functions for those
numeric/currency fields to act as 'measures' in the OLAP
cube, such that, statistics can be generated across other
fields, based on the value of the 'measure' fields. Selected
fields and defined functions are saved for that specific
table (in the favorites) so that when you come connect back
to this database table the next time, it will show the same
selected fields, and other composite/calculated fields, if
you have added any.
A cube schema file is then created and feed to the OLAP
client to process and extract the cube from the database.
This tool, consists of the Grid and Chart Views. On
the left is the Cube structure - measures and hierarchies as
a tree. The measures are grouped in the set, displayed in
the branch. All the rest of the tree nodes are the
dimensions that contain hierarchies. You can then drag
dimensions (fields) from the cube structure to the pivot
areas (Columns and Rows areas), and then select a measure or
two from the cube, and drag it to the values area to
generate the statistics.
Screenshot: OLAP Grid View - Country/Region/City wise sales
data for 2009:
Screenshot: OLAP Chart view -
Country/Region/City wise sales data for 2009:
You navigate through these
dimensions by drilling down, rolling up, or drilling across.
You can drill down to access the detailed level of data, or
roll up to see the summarized data. You can roll up through
the hierarchy levels of dimensions or to specific
characteristics or data elements (columns) of the
dimensions. You can also drill across dimensions to access
the data of interrelated dimensions. In addition, you can
set one of these powerful computational functions such as
sum, averages, distinct count, maximum, minimum etc. for the
After a particular snapshot of the statistics is achieved,
you have the options to save the pivot settings to file, for
accessing the same snapshot in future. If you need to share
or publish the statistical findings, export it to image,
PDF, Excel etc, or print it. If your database is located on
a network, you can also save the cube data to file such that
you can work offline with the cube, even when the database
is not available, or when the network is disconnected.
To put in perspective,
OLAP Statistics & Reporting for Microsoft
Put information into the hands of
the decision makers - Interact
with your data and investigate
relationships within the data with
simple navigation tools. OLAP
Statistics also provides context,
relevance and visualization of the
Ask questions of the database
- Run query and get the result
within seconds. OLAP Statistics
usually provides for very fast query
performance. The usual OLAP query is
returned in within 4 seconds.
Run complex calculations on
the OLAP cube to provide aggregated
create your own
analytic views. OLAP
Statistics makes it very easy to
create new "views" of the data.
There are no complex joins to
your data in any order, at any level
of summarization, and over several
to perform Market Basket
Eg. How many
customers who bought product A also
bought product B?
Similar and related products from AssistMyTeam SMB