Joint child relationships in MSTR

Joint child relationships

Some attributes exist at the intersection of other indirectly related attributes. Such attributes are called joint children.

Joint child relationships connect special attributes that are sometimes called cross-dimensional attributes, text facts, or qualities. They do not fit neatly into the modeling schemes you have learned about thus far. These relationships can be modeled and conceptualized like traditional attributes but, like facts, they exist at the intersection of multiple attribute levels.

Many source systems refer to these special attributes as flags. Therefore, if flags are referenced in your source system documentation, these are likely candidates for joint child relationships.

Joint child relationships are really another type of many-to-many relationship where one attribute has a many-to-many relationship to two otherwise unrelated attributes. For example, consider the relationship between three attributes: Promotion, Item, and Quarter. In this case, Promotion has a many-to-many relationship to both Item and Quarter, as shown in the following diagram.

An example of a promotion might be a “Red Sale” where all red items are on sale. A business might run this promotion around Valentine's Day and again at Christmas time.

Supporting joint child relationships

One way to resolve a many-to-many relationship is to have a relationship table for the attributes involved in the many-to-many relationships. In this case, you might create two relationship tables, one to relate Promotion and Item. The second relates Promotion and Quarter as shown in the following diagram.

These two tables are sufficient to answer questions such as:

•

What items have been in what promotions?

•

What quarters have had what promotions?

However, these tables are not sufficient to answer the following more detailed and insightful questions:

•

What items were in what promotions in a given quarter?

•

In what quarters was a certain item involved in a certain type of promotion?

To answer these questions, you must combine the two relationship tables, creating one table to relate all three attributes.

The relationship in the distinct relationship table must exist for a joint child relationship to be properly defined. However, it does not necessarily have to be in its own, distinct relationship table. Defining the relationship directly in the lookup table for the parent of the joint child—in this case, Promotion—would be fine. Alternatively, you can build the relationship directly into the fact table.

In these examples, it is important to notice the relationship between the three attributes. The Promotion attribute is related to a particular Item-Quarter pair, as opposed to it being related to Item and Quarter separately. This is the essence of a joint child relationship and is shown in the following diagram.

Notice that a joint child relationship can be one-to-many or many-to-many. The issues with many-to-many relationships, including loss of analytical capability and multiple counting, also apply to many-to-many joint child relationships.

If you have a joint child relationship in your data, it is important for you to define it in MicroStrategy so that you get the correct data for reports that use the parent attribute in a joint child attribute. This ensures that when you need to join the fact table to the parent attribute of a joint child relationship (for example, to see sales by promotion) the join will always use both joint children rather than just one or the other.

Comments

URL API connection mode parameters

URL API connection mode parameters When using the URL API, to denote which type of Authentication to use, developers can use the connMode parameter. The following values are used for this parameter: Standard = 1 LDAP Authentication = 16 Database Authentication = 32 Guest = 8 Windows Authentication = 2 Trusted Authentication = 64 Integrated Authentication = 128

Level metrics in Microstartegy/MSTR

Level Metrics Level metrics allows the users to choose the right combination of level target, filtering, and grouping (referred to as elements) to achieve your desired results. The elements of a metric level are described below: • Target : The target is the attribute level at which the metric calculation groups. For a more detailed description, see Target: The context of a calculation . • Grouping : Grouping determines how the metric aggregates. For a more detailed description, see Grouping: How aggregation is performed . • Filtering : Filtering governs how the report filter interacts with the metric calculation. For a more detailed description, see Filtering: Interaction with report filters . The level is indicated between the curly braces ({ }) in the metric definition shown below: Sum(Revenue) {~, Product} The tilde (~) represents the report level with standard filtering, denoted by the plus sign (+). If you add item as a level, th...

Create a transaction services photo uploader

Create a transaction services photo uploader 1. Create a new table "photo_upload" in Tutorial warehouse database (the default location: C:\Program Files\MicroStrategy\Tutorial Reporting\TUTORIAL_DATA_7200.mdb), as shown below: 2. The 'photo_upload' table has to be pre-populated with *exactly* 10 rows of data, the values for the 'ID' column should be 1-10 and the values for the 'uploaded' column should all be 0 3. In MicroStrategy Desktop, create a freeform report "R1" based on the new table "photo_upload" in Tutorial data created at step 1, as shown below: SELECT Location, Description, ID, uploaded, numbers FROM PHOTO_UPLOAD 4. Create another table for transaction insert SQL. Make sure to create an 'autonumber' type ID as primary key for this table, or auto_increment ID for different DBs. 5. Create...

Case functions Microstrategy

Ca se functions Microstrategy Case functions return specified data in a SQL query based on the evaluation of user-defined conditions. In general, a user specifies a list of conditions and corresponding return values. Case This function evaluates multiple expressions until a condition is determined to be true, then returns a corresponding value. If all conditions are false, a default value is returned. Case can be used for categorizing data based on multiple conditions. This is a single-value function. Syntax Case ( Condition1 , ReturnValue1 , Condition2 , ReturnValue2 ,..., DefaultValue ) Example Case(([Total Revenue] < 300000), 0, ([Total Revenue] < 600000), 1, 2) sum(Case (Day@DESC in (“Sat”,”Sun”), Sales, 0) {~+} Sum(Case(Category@DESC In("Books","Electronics"),Revenue,0)){~+} CaseV (case vector) CaseV evaluates a single metric and returns different values according to the results. It can be used to perfo...

Configure Connection Mapping in Microstrategy

Configure Connection Mapping in Microstrategy The following steps demonstrate the second scenario where two different data warehouses are used within the same project: Create two different database connections - One that points to the data warehouse for the European users and the other that points to the data warehouse for USA users as shown below: Select Europe as the default database connection for the database Instance as seen below: Go to P...

MicroStrategy URL API Parameters

MicroStrategy URL Structure The following table summarizes the root URL structure used for every request to MicroStrategy Web. Environment Main Application URL Administration URL J2EE http://webserver/MicroStrategy/servlet/mstrWeb http://webserver/MicroStrategy/servlet/mstrWebAdmin .NET http://webserver/MicroStrategy/asp/Main.aspx http://webserver/MicroStrategy/asp/Admin.aspx Every request sent to MicroStrategy Web calls a central controller. Parameters are appended to Main.aspx or mstrWeb (in a .NET and J2EE environment, respectively) to indicate to the controller how the request should be internally forwarded and handled. The following examples show a URL for accessing a MicroStrategy folder when the user does not have an existing session. The URL contains not only the parameters needed to connect to MicroStrategy Web, but also the parameters needed to log on and create a session. J2EE environment: <a href="http:...

Microstrategy Removing sections that do not have metric data

Removing sections that do not have metric data This is an interesting feature which might not be explored by many of us and it comes us handy. A cross join between datasets can result in rows or Group Header/Footer sections that do not have metric data. For example, a document contains two datasets. Dataset 1 contains Year and Revenue, with data for three years (2007-2009). Dataset 2 contains Year and Profit, filtered to return data for only two years (2008 and 2009). If you place Year and Profit in the Details and execute the document, it displays three rows, although no profit data exists for 2007. This is a product of the cross join between the two datasets. You do not want to see the blank line for 2007 since it does not give you any data for profit. You can select the Trim sections for which no metric value data is available check box. This removes the row for 2007, since no metric data for Profit is available for 2007. The results are shown below: ...

Types of filters in Microstrategy

Types of filters in Microstrategy Below are the types of filters: 1. Attribute qualification filter These types of qualifications restrict data related to attributes on the report. a) Attribute form qualification Filters data related to a business attribute’s form(s), such as ID or description. • For example, the attribute Customer has the forms ID, First Name, Last Name, Address, and Birth Date. An attribute form qualification might filter on the form Last Name, the operator Begins With, and the letter H. The results show a list of customers whose last names start with the letter H. b) Attribute element list qualification Filters data related to a business attribute’s elements, such as New York, Washington, and San Francisco, which are elements of the attribute City. • For example, the attribute Customer has the elements John Smith, Jane Doe, William Hill, and so on. An attribute element list qualification can filter data to display only those customer...

Microstrategy Custom number formatting symbols

Custom number formatting symbols If none of the built-in number formats meet your needs, you can create your own custom format in the Number tab of the Format Cells dialog box. Select Custom as the Category and create the format using the number format symbols listed in the table below. Each custom format can have up to four optional sections, one each for: Positive numbers Negative numbers Zeros Text Each section is optional. Separate the sections by semicolons, as shown in the example below: #,###;(#,###);0;"Error: Entry must be numeric" For more examples, see Custom number formatting examples . To jump to a section of the formatting symbol table, click one of the following: Numeric symbols Character/text symbols Date and time symbols Text color symbols Currency symbols Conditional symbols Numeric symbols For details on how numeric symbols apply to the Big Decimal data type, refer to the Project Design Guide . ...

Prompt-in-prompt (Nested prompt) feature in a FreeForm SQL Report

Prompt-in-prompt (Nested prompt) feature in a FreeForm SQL Report In some business scenarios, it is required to implement prompt-in-prompt (nested prompt) feature to use the answer of one prompt to qualify on the elements of another prompt in Freefrom SQL reports in MicroStrategy Developer 9.4.x-10.x. The following procedure describes how to achieve prompt-in-prompt in a Freeform SQL report in MicroStrategy Tutorial project: Create a new filter, select Add an Attribute qualification and choose the highest level attribute Country. Make sure to Qualify On: Elements. Click Prompt as the image shown below. Accept all the default values without any changes in the popped up window after clicking on "Prompt" as shown below. Save the filter as "Country Filter". Click "Prompt", choose "Use a filter to reduce the number of elements" option and select Country Filter created in last step, as shown below. Save the filter as "Region Filter...

Microstrategy Analytics

Search This Blog