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Features

One note to the experts: Palo is an OLAP Server, more particular a MOLAP Server which should not be used if you are actually looking for a ROLAP Server. Below you will find a short overview on the most important features of Palo and MOLAP:

What do these terms really mean?

Write-Back

In addition to providing multi-dimensional data analysis of existing data, Palo also allows inputting of new data directly into the cube and facilitates both top-down as well as bottom-up planning. This important characteristic differentiates Palo from relational OLAP servers.

User Rights

The Managing User Rights function is a new feature in Palo 1.5. It enables you to manage access rights for databases, cubes, dimensions and dimension elements, users, user groups, cell data and selected system operations. Five different rights can be defined: Splash (writing into consolidated cells), Delete, Writing, Read, None. These rights are assigned to the various user groups.

Palo is Cell-based

If you do a query in a relational database, the smallest result you will get is one record (usually consisting of several fields). If you do a query in Palo, your result is a single cell value. So Palo thinks in cells, not in records. This is what makes it so compatible with Microsoft Excel, because Excel is also cell-based.

Palo is multidimensional

Multidimensionality is alternative way to organize data in a database. In a relational database you are used to structures like tables, records and fields. In a multidimensional database you are thinking in terms of cubes and dimensions and cells. You know what a cell is, but what is a dimension and a cube? To answer the question it makes sence to have another look at Microsoft Excel. In the screenshot below you find a list of row titles in Excel.

In Palo this list is called a dimension. So basically a dimension is a list of categories that has some contextual relationship like a list of products, regions, customers or months. In Palo the above Excel list this would be modelled as a dimension with the name “Products”.

So far in our Excel sample we have one dimension on the sheet. Now lets add another “dimension” on the Excel sheet. It will be a horizontal list of months and quarters like you can see on the following screenshot. In Palo this dimension would be called “Months”.

Now there is an interesting point. What do you do in Excel if you want to organize your data in more than two dimensions? Yes, you can start to use the sheet tabs to create a third dimension, but what comes after that? Experience shows, that large organisation usually require 5-10 dimensions to store their data according to their needs. An Excel Workbook only supports 3 dimensions.

This is one of the reasons why Palo was created. Palo supports up to 256 Dimensions. It allows to structure data much more detailed as pure Excel. In order to do that, another thing is needed apart from the dimensions and that is called a “cube”. Now lets learn what a cube is.

Lets look at the two-dimensional model that we created in Excel so far. There is a cell range which is defined by the two dimensions “Products” and “Months” (Range C3:J11). This range consists of cells and each cell has a cell address (like D4 for example). In Palo this cell range would be called a two-dimensional cube.

So basically a cube is a collection of cells that is defined by 2 dimensions or more. Again Excel supports only 2-3 dimensions, Palo supports many more dimensions. With Palo you can build data cubes that typically consist of 5-10 dimensions. Now the question remains, how to you access and display data from a multidimensional cube if Excel is only capable of displaying two dimensions on a sheet?

To answer the question, we first have to look at the way a cell is referenced in Excel. Excel uses a simple naming scheme for cells, its called the A1-Style. So the “Product B” value for “February” is stored in cell D4. In a Palo data cube the value would be stored in a cell that does not use Letters and numbers as cell address, but the real-life description of the data instead. In our example the address of the cell would be “Product B”, “Feb”.

To display data from a Palo cube in Excel, a special database function is used. It is called “PALO.DATAC”. The following formula would pull a value from the multidimensional data cube into an Excel cell (ignore Servername and Cubename at this time)

=PALO.DATAC("Servername","Cubename","Product B","Feb").

It is easy to see, that this data formula could hold more than two dimension coordinates, for example a syntax like this to access a 5-dimensional cube.

=PALO.DATAC("Servername","Cubename","Product B","Feb", "2006","Europe","Units").

In the following screenshot you see how a 5-dimensional cube is displayed on an Excel spreadsheet using a 5-dimensional data formula.

If you follow the references in the data formula (in the formula bar) you will discover that the data formula references the strings in the row and column titles to get some of the coordinates, but it also references cells which are on the top of the page (cell A3, A4, A5). These cells contain the coordinates for those dimensions that could not be displayed as row or column titles. Using these “page selectors” is one way how you display views on a multi-dimensional database in a two-dimensional spreadsheet grid.

Keep in mind that you only have to change the content of cell A3 or A4 to see the data for a different year or different region. So you can view a lot of data just with one Excel sheet. Think of how many sheets you would need if you wanted to manage the same amount of data just using Excel.

A final question might be how you enter values in the database. This is actually very easy. You simply overwrite the formula in the spreadsheet (for example cell C9) with a value. The Palo Excel Add-In will then make sure, that the value is automatically saved to the specified cell in the cube. After that has happened, Palo will restore the original formula which then shows the new value.

Hierarchies

Looking at the last screenshot you might wonder, why the value for Productgroup1 and Total Products is also displaying the value 123, although we only entered a value for Product B. The answer to this question is hierarchical aggregation. The dimension Product is actually not a flat list. When we defined this dimension in the Palo database modeler, we added a hierarchy to the list, which looks like this.

Using hierarchies when defining a dimension adds a lot of power to the Palo data cubes. With hierarchical dimensions, the cube is able to do multidimensional aggregations in the cube. So you don’t have to do this calculations with Excel formulas, instead you directly pull the aggregated values form the cube.

Memory-based & Real-time

Palo is memory-based. This basically means speed. Data retrieval of base cells and also of aggregated cells is done real time. No time consuming queries to run, results should be displayed with milliseconds (or seconds at the longest).

There are other multidimensional databases on the market which are based on a relational technology (ROLAP databases). They have their advantages in terms of capacity, but they are usually slower and they usually do not support write-back of data in the cubes.

Server-Based

Palo can be installed locally or in a company network. In network mode all users work with the same data, changes in one spreadsheet are immediately visible on the other workstations in the intranet.

Subsets

A subset is a set within a dimension. With a subset you can select elements or subsets of elements and sort them according to certain criteria. Example: you would like to get the Top 10 items of a list of products and you would like for the results to be within defined marginal values.

Rules

In previous Palo versions, the consolidation factor of elements was used to carry out simple calculations – this included additions and subtractions. Palo Enterprise Rules enhance this functionality and enable you to execute complex calculations (division/multiplication, logical and various functions).