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Data Warehouse and Cubes Tips and Tricks - March 2017

19/3/2017

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Solutions:  
  • Set a default budget for Budget Amount
  • Invert the sign of Income Statement Accounts.

Why this blog series exists:
When you buy an out of the box data warehouse & cube solution like Jet Enterprise from Jet Reports, www.jetreports.com or ZapBI, it usually meets the 80/20 rule (the stock solution satisfies 80% of your reporting requirements, and you'll need further customizations to meet your remaining analytics requirements).  
​Client requests from customers like you inspire this blog series.

Set a Default Value for Budget Amount

Problem:  Some measures require filtering by a default value to show reasonable results.  

Consider the example of the company that creates and revises a new budget each quarter.  While it's perfectly reasonable to show the [Budget Amount] for March 2017 from the 'Initial 2017 Budget' or 'Q1 2017 Amended', it would be misleading to show the sum of both budgets for March 2017.  Similarly, if your organization uses a forecasting tool to calculate expected item consumption or sales, you may have multiple forecasts numbers for the same item and month. 

Solution:  To minimize the risk of 'double counting', we'll modify [Budget Amount] to always filter by a default [Budget Name].
In this solution, we hard-coded a budget into the Default Member as part of the dimension definition.  For improved maintenance, we could add an [IsDefaultBudget] attribute to the [Budget] dimension in our cube and data warehouse.  Then reference the new column when defining the Default Member.  Ideally our source ERP system can identify the current budget, or we can implement business processes and SQL code to auto-identify the correct budget.

Note:  Because we can have multiple concurrent budgets, but shouldn't sum [Budget Amount] across different budgets, the measure is a semi-additive fact -- in Business Intelligence nomenclature semi-additive facts cannot be summed across all dimensions.  Other common examples include balance, profit percent, average unit price, company consolidation, as well as most cost-allocation schemes.  When customizing our data warehouses and cubes, we must be careful where we implement the calculation to avoid reporting errors.

Non-additive facts cannot be summed (ex. [First Invoice Date]).  Fully-additive facts are 'normal' facts which can be summed across all dimensions.

Invert the sign of Income Statement Accounts

Problem:  Sometimes the dimension used affects how we want to calculate a measure.

In many ERP systems the [Amount] or [Quantity] column have counter-intuitive signs.  Consider G/L Entries which have negative signs for revenue and positive signs for expenses or inventory transactions which show a negative sign for item sales and shipments and positive signs for item purchases.  While the data makes sense to accountants and analysts, business users frequently appreciate seeing signs that intuitively make sense.

In cube-based reports, we'd like to invert the sign on [Amount] for all Income Statement accounts but not Balance Sheet accounts.  Note, it's arguably 'wrong' to invert the sign in the data warehouse because that would make our [Amount] column semi-additive, and potentially cause problems for our auditors!

Solution:  In the cube, use a SCOPE statements to assign a different calculation to [Amount] based on the [GL Account] dimension.
 Note:  in SSAS cube nomenclature we typically deal with two out of three measure types:  Standard and Calculated (avoid Derived measures when possible).

A Standard measure is typically a SUM or COUNT of a column that exists on the fact table in the data warehouse:  ex. sum(Amount) or sum(Quantity).

A Calculated measure is an expression that typically uses standard measures in conjunction with MDX expressions and functions.  Typical examples include division (profit margin percent or avg. daily sales) as well as all business functions (Year To Date, Balance, or  Previous Period). 

A Derived measure is a calculation based on fields from the same fact table -- ex. Profit Margin ([Sales Amount] - [Cost Amount])   When possible, avoid derived measures and use standard measures instead-- just add the calculation as a new column in the data warehouse.  Using standard instead of derived measures has two major advantages:  
  1. Users reporting directly against the data warehouse can use the predefined column.
  2. The cubes will process faster during their overnight load.

That's All Folks

Remember, out of the box solutions by definition are designed to work for ALL customers.  Further customization is expected, even required!  Onyx Reporting is available for development services, training and mentoring as you implement minor (if not major) customizations to your Jet Enterprise implementation.

For clients not using Jet Enterprise, please contact us to find out how data warehouse automation can cut your business intelligence implementation time from weeks and months into days.
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