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.

Highlights:   Works with most version of Microsoft Access databases - 97/2000/2002/2003/2007 (*.mdb),  2007/20101 (*.accdb) Save OLAP cube schema (*.olapschema) and re-use it for subsequent operations to generate cube from the database. Support almost all data types in MS Access. Choose your own fields from the fact/transaction table and their related tables and set them as measures or dimensions for the OLAP cube. Supports the following functions for Measures - Count, Distinct Count, Max, Min, Average, Sum etc. Supports most of the common OLAP operations including slice and dice, drill down, roll up, and pivoting on the cube. Supports date/time fields to be summarized or broken down to year, month, day, week, hours, minutes etc. Create your own composite hierarchy. Eg. Country > State > City Create your own calculated member involving computational relationship. Eg. Total Sales = (UnitPrice X Quantity) + Freight OLAP Grid and Chart with highly interactive, customizable and user friendly interface. Save the pivot details to file (*.olapreport) to make it easy for later retrieval and use without requiring to start from scratch. Support offline cube (to *.offlinecube in compressed or uncompressed format)  for use in disconnected mode. Complete control over the export settings of the grid/chart reports. Export grid/chart reports as BMP, GIF, JPEG, PNG, TIFF, TXT, CSV2, PDF3, HTML, XML, XLS4 Share pivot details, reports, offline cube, cube schema files among team members to facilitate collaboration. Unicode Support Print Preview tool No requirement of Microsoft Excel® , Microsoft Access® or Analysis Server.   1Requires installation of Data Connectivity Components' drivers for 'Office System 2007'. The software will automatically take you to the download site if it is not installed on the system. 2Comma Separated Values 3Adobe Portable Document 4Microsoft Excel Document

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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 2008?

• 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 managers.

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 measure field.

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 Access can   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 data 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 data Easily create your own analytic views. OLAP Statistics makes it very easy to create new "views" of the data. There are no complex joins to create. Combine your data in any order, at any level of summarization, and over several time periods. Enable you to perform Market Basket Analysis. Eg. How many customers who bought product A also bought product B?