ASO vs. BSO Calculations

There are a lot of reasons why Essbase owners should have the majority (or all) of their cubes as ASO now. ASO loads faster, calcs faster, have a smaller footprint, allow for far more dimensions, and a few other things that others have already written a lot about. Prior to the current version of Essbase there were some concerns and it wasn’t quite as user friendly, but the Fusion edition (11.x) has addressed many of those concerns. Now with incremental loads, partial data clears, and ability to write back to level 0 members there is a lot more flexibility.

The reason why I write this today though is because I found another great reason to have ASO cubes instead of BSO. Some have written that BSO cubes allow for more complex calculations, which may be true in some regards. I have found that MDX in ASO cubes provides greater flexibility and allows writing of complex calculations in far few lines of code in a member formula.

For example, we have one BSO cube remaining that we use for planning purposes. A recent report request required a formula be added to the cube. The formula in and of itself is not complex. What is complex is that there are multiple IF scenarios that have to be embedded to ensure that the right calculation takes place for the right period of time. While writing this formula I received the following error message:

I never knew I was limited to a formula size. It makes obvious sense; I had just never run up against the limit before. I ended up having to remove some of my IF scenarios to get the formula down to the appropriate size. It’s not a huge deal as I guess no one is likely looking at the period over period growth rate from 3 years ago, but it was frustrating none the less.

So this got me thinking, we have this same formula in other cubes, ASO cubes. I was curious how they compared because I know it wasn’t as painful to write the ASO version as what I went through writing the BSO version. This is what I found:

• A fully written BSO formula was 1242 lines and 75,493 bytes
• A fully written ASO formula was 78 lines and 4,445 bytes

(I won’t bother showing you the 2 formulas as who wants to look at that many lines of code if they don’t have to)

And I think it is interesting to point out the BSO formula was written to calculate at the Month, Quarter, and Year level only. The ASO formula is written to calculate the Week, Quarter, Month, and Year levels. So technically, the ASO formula is doing even more than the BSO formula.

The difference is that in MDX there are some wonderful functions that allow you to select your data more succinctly and apply the desired calculation. I will be the first to admit, MDX isn’t always the easiest to read and sometimes building a complex calculation using multiple MDX functions embedded with each other can be frustrating to put together, but in the end I find that almost always my formula is shorter and therefore easier to maintain.

SQL and PL SQL Loading Via EAS

We have been doing quite a bit of SQL and PL SQL loading using EAS as of late. I have found the user interface can be confusing and the user guide to not be of much assistance. Below is what we have found to work for our needs.

First step is to get the ODBC set up, which the user guide can walk you through if you aren’t aware how to.

Once that is set up, within EAS you create a new load rule or modify and existing load rule if you prefer. Then navigate to File->Open SQL. You will first be prompted to select your Essbase Server, Application, and Database.

At first the next screen looks straight forward, but really there are a lot of extra fields that you may or may not need to use.

 
For instance to load via PL SQL, from a source such as PeopleSoft, you will want to select the Oracle Wire Protocol option from the SQL data sources section. You will enter your SQL statement by either using the boxes provided or by entering the entire statement into the Select section. Either of these methods will work. The next step is to select OK/Retrieve at the bottom of the screen. Note: You do not need to use the Connect section at all. Trying to fill in the Server, Application, Database, or Dictionary path in the Connect section will result in an error stating “Failed to Establish Connection With SQL Database Server. See log for more information.”
 
To load via SQL, you will want to select the SQLServer Wire Protocol option from the SQL data source section and enter your SQL statement into the provided boxes or into the Select section. Depending on how you have identified the tables in the from section of your query, you may have to provide the database name in the Connect section. If the database is included in the table description (ex: <>.dbo.<<>>) you will likely be able to move straight to selecting the OK/Retrieve button without issues. If you have not identified the database name in the table description, place the database name in the Connect section to move forward.  
Once you have selected OK/Retrieve, you will be prompted with the SQL Connect box where you are prompted for a user name and password, which will be your PL SQL or SQL user name and password. As a note, we found we had to have SQL authentication for this to work. Using Windows authentication produced errors and we were unable to connect. The Essbase Server, Application, and Database should default to your previous selection.

After selecting OK, your data will populate into your Data Prep Editor screen. From here you can create a load rule as you normally would. You can create both load and build load rules to run off of these data sources.

If you still receive a Failure to Establish Connection error message and you are sure of the passwords you are using, then you will want to look at the SQL next. Here are things to look for:

• Make sure you have not placed the word “Select” into the SQL box – It utilize the Select from the header on the box
• Remove table and column aliases – If you have multiple tables that share fields, you will need to put the entire table name in front of the field throughout your query
• Check your more complex SQL functions to make sure they are compatible with the SQL loader within EAS – Try removing the complex statements and see if you can connect
• Remove anything you have commented out – Leave the SQL statement as purely the SQL statement to be executed

When I have had an issue with my query I have stripped the SQL down to the most simple statement first. Sometimes, I have even gone so far as to have it be Select * from <>. Then adding each piece back in until I get the entire statement in place. It helps in identifying which part of the code EAS is having problems with.

MDX - Layering Formulas

As most Essbase users know, ASO has become the future of Essbase. There are some great advantages of ASO over BSO, but it also means having to learn MDX to create member formulas. MDX can be daunting at first, but with practice and persistence, formulas can be created to reflect almost anything that needs to be calculated. You can create a more complex formula by layering formulas together, but to do this you need to know what formulas are available. Fortunately, Oracle does a pretty good job of listing the available formulas and their syntax in their Technical Reference Guide. The 11.1.1 version can be found at: http://download.oracle.com/docs/cd/E12825_01/epm.111/esb_techref/frameset.htm?mdx_grammar_rules.htm.

Below is an example of a fairly complex formula that was created using MDX.

For this example, the Sample Basic database has been converted to an ASO database. Dimension changes include the addition of weeks for each month, using a 4-4-5 calendar, Work Days was added as a member within the Measures dimension, and Fiscal Year was added as a dimension. This is what the new outline looks like:

Let’s say for budgeting or trending purposes you need to need to look at the 4 week average of Sales, but Sales is impacted by the number of work days in the week. You want to exclude any weeks that were not full 5 day work weeks for your calculation. Add a member to the Measures dimension called 4 Wk Avg Sales with the following formula to get the correct calculation.

Case
  When IsEmpty(([Year].CurrentMember,[Measures].[Profit],[Product].[Product],[Market].[Market]))
    Then 0
  Else
  (
  Case
    When (IS([Year].CurrentMember, WK1) OR
               IS([Year].CurrentMember, WK2) OR
               IS([Year].CurrentMember, WK3) OR
               IS([Year].CurrentMember, WK4) OR
               IS([Year].CurrentMember, WK5) )
      Then Avg (Tail(Filter(Crossjoin (Union (Crossjoin (MemberRange([Year].[WK48],
                     [Year].[WK52]),
                     {[Fiscal Year].CurrentMember.Lag(-1)}), Crossjoin (MemberRange([Year].Wk1,
                       [Year].CurrentMember),{[Fiscal Year].CurrentMember})),{[Measures].[Sales]}),
                      ([Market].[No Market],[Product].[No Product],[Work Days]) = 5),4))
    Else Avg (Tail(Filter(Crossjoin (MemberRange([Year].Wk1,[Year].CurrentMember),
                {[Measures].[Sales]}), ([Market].[No Market],[Product].[No Product],[Work Days]) = 5),4))
    End
    )
End

So what does this formula do exactly?  Let's break it down into pieces.

The first part of the formula is a test to see if there is Profit at the very highest levels. If Profit is zero, then it will bring back zero as the 4 Wk Avg. This will prevent the formula for calculating for future weeks or prevent it from not calculating at a lower level, when there is no Profit at that lower level.

    Case
      When IsEmpty(([Year].CurrentMember,[Measures].[Profit],[Product].[Product],
         [Market].[Market]))
        Then 0

The next part is the calculation that will be performed whenever there is Profit at the highest level. The first part of this piece looks at the first 5 weeks of the year and the second part looks at the remaining weeks in the year.

Although it is a little backwards let’s look at the second part of the Else statement first. So for all weeks that not WK1 through WK5 we have the following formula.

    Else Avg (Tail(Filter(Crossjoin(MemberRange([Year].Wk1,[Year].CurrentMember),
                  {[Measures].[Sales]}),
                  ([Market].[No Market],[Product].[No Product],[Work Days]) = 5),4))

This statement is filtering WK1 through the current week Sales based upon where there are 5 Work Days and averaging the last 4 weeks.

The Crossjoin gives us a set of all the weeks Sales.

   Crossjoin(MemberRange([Year].Wk1,[Year].CurrentMember), {[Measures].[Sales]}

The Filter gives us a set where there Work Days is set to 5 for the week.

    Filter(Crossjoin(MemberRange([Year].Wk1,[Year].CurrentMember),
          {[Measures].[Sales]}),
          ([Market].[No Market],[Product].[No Product],[Work Days]) = 5),

The Tail gives us the last 4 members of the set where there Work Days is set to 5 for the week.

    Tail(Filter(Crossjoin(MemberRange([Year].Wk1,[Year].CurrentMember),
          {[Measures].[Sales]}),
          ([Market].[No Market],[Product].[No Product],[Work Days]) = 5),4)

The logic is similar for the first 5 weeks of the year, except we have to look at both current year and prior year to determine our 4 weeks.

    Case
      When (IS([Year].CurrentMember, WK1) OR
                 IS([Year].CurrentMember, WK2) OR
                 IS([Year].CurrentMember, WK3) OR
                 IS([Year].CurrentMember, WK4) OR
                 IS([Year].CurrentMember, WK5) ) 
        Then Avg (Tail(Filter(Crossjoin (Union (Crossjoin (MemberRange([Year].[WK48],
                  [Year].[WK52]), {[Fiscal Year].CurrentMember.Lag(-1)}),
                  Crossjoin (MemberRange([Year].Wk1,[Year].CurrentMember),
                  {[Fiscal Year].CurrentMember})), {[Measures].[Sales]}),
                  ([Market].[No Market],[Product].[No Product],[Work Days]) = 5),4))

This time we first want to Crossjoin the weeks to the Fiscal Year for both current year and prior year and since we want to look at both, we are going to use Union to join these two sets together.

    Union(Crossjoin (MemberRange([Year].[WK48],[Year].[WK52]),
             {[Fiscal Year].CurrentMember.Lag(-1)}),
             Crossjoin (MemberRange([Year].Wk1,[Year].CurrentMember),{[Fiscal Year].CurrentMember}))

Now we can Crossjoin the Unioned sets to Sales.

    Crossjoin (Union (Crossjoin (MemberRange([Year].[WK48],[Year].[WK52]),
             {[Fiscal Year].CurrentMember.Lag(-1)}),
             Crossjoin (MemberRange([Year].Wk1,[Year].CurrentMember),
             {[Fiscal Year].CurrentMember})),
             {[Measures].[Sales]})

From here we apply the same Filter, Tail, and Average logic to finish the statement.

Here is sample output showing the formula results:

Note:  A similar formula can be used in the time dimension Year, but it would only be for the current week, with no historical values stored.  The formula would also have to be modified for the current year to be from WK1 to a substation variable that is set up to be the current week.

Identifying Descendants with MDX? Use IsAncestor

There were many times when I found myself wondering why there wasn’t an ISDESC or IsDescendants function for MDX. Then one day I found the IsAncestor function. With this function, a descendants function is completely unnecessary, although it is a little counterintuitive when you are used to the BSO world of formulas.

The formatting of this function is: IsAncestor (member1, member2 [,INCLUDEMEMBER]).

The trick to this function is to ask yourself each time you use it “Is the first member the ancestor of the second member?”

For the examples, I will use the Sample ASO application and focus on the Market dimension.

So, if you wanted to see all of the descendants of East in the Market dimension your formula would be IsAncestor([East], [Market].CurrentMember) with the result set being New York, Massachusetts, Florida, Connecticut, and New Hampshire.

If you wanted to see all descendants of East in the Market dimension including East, your formula would be IsAncestor([East], [Market].CurrentMember, INCLUDEMEMBER) and your result set would be East, New York, Massachusetts, Florida, Connecticut, and New Hampshire.

You can also use the function to test and see if a member is a descendant of another member. An example of this would be IsAncestor([Market].CurrentMember, [Florida]). The result set would be true for the East and Market members and false for all other Market members. If you add INCLUDEMEMBER in the function your result set would also include the member Florida.

It would be far easier if there were a descendant function in MDX, but once you get used to using IsAncestor, you will find it will do the job every time.