VLookup kind of Dynamic Custom Group in Dashboard/Dossier

Custom groups enable users to view specific elements based on a metric or specification. For example, you may want to see all the customers in a retail store that bring in over $1,000k in revenue per month, or a teach may want to only view data on students who scored over 2000 on their SATs.

The Scenario

Let's assume you have a table that clusters your Employees by the Cost brackets. Based on those brackets a Rating is defined (like A, B, C...). This table can be imported from Excel file or from a table in relational database. You will notice there is a flag column that contains value '1' for each row. If you don't have this column in your data don't worry! Just use the Upper column instead in the formula (see formula of 'Rating Metric' below). Continue on with the process.

User-added image

Methods for creating a custom group

Currently, your Dashboard or Dossier displays Cost per Employee, but it is missing Rating information. Continue on through the numbered steps that are labeled with images to help you along the way.

The images will act as a guide through the process.

User-added image

As a first step import your Rating table.

Import Rating as an attribute.

Create a metric 'Rating Metric' with the following formula:

Max(IF(((Cost>Lower)And(Cost<Upper)),Flag,0)){~+}

User-added image

Create a grid that contains Employee, Rating (attribute) and Cost.
The data comes from two unrelated data sets so you will get a cross join of data.

Add "Rating Metric" to Filter Pane and set a filter 'Greater than or Equal to" 1. You will see a proper Rating assignment and you don't even need to display 'Rating Metric" on the grid.

Final Report

User-added image

Note: This assignment is dynamic, meaning that if you change the Rating brackets in your data set the new Rating rules will be applied automatically (assuming, you are using a live connection to a database).

You may need to change Level of your metrics if there are more attributes in your initial data set.

Comments

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 Prompts) in Microstrategy

Prompt-in-prompt(Nested Prompts) in Microstrategy Nested prompts allows you to create one prompt based on the other and other bases on another, nested prompts allows us to prompt the highest level(Like year) to middle level(like Quarter, then to the low level(like Month). Here you can see how to create a 3-level deep nested prompt that will prompt the user to select a year, then a quarter within that year, then a month within that quarter. Prompt-in-prompt is a feature in which the answer to one prompt is used to define another prompt. This feature is only implemented for element list prompts . The following procedure describes how to achieve this: Create the highest level filter. This is a filter which contains a prompt on an attribute element list. Create a filter on the attribute "Year." Click "prompt on attribute element list" and click "Next" through the rest of the screens to accept the default values. Do not set any additio...

Slowly Changing Dimension Types 0, 4, 5, 6 and 7

Slowly Changing Dimension Types 0, 4, 5, 6 and 7 Ralph introduced the concept of slowly changing dimension (SCD) attributes in 1996. Dimensional modelers, in conjunction with the business’s data governance representatives, must specify the data warehouse’s response to operational attribute value changes. Core SCD approaches: Type 1 (overwrite), Type 2 (add a row), and Type 3 (add a column). Since legibility is a key component of the Kimball mantra, we sometimes wish Ralph had given these techniques more descriptive names, such as “overwrite” instead of “type 1.” But at this point, the SCD type numbers are part of our industry’s vernacular. We have written about more advanced SCD patterns, such as the 2005 article entitled “ Slowly Changing Dimensions are Not Always as Easy as 1, 2, 3. ” However, we’ve not consistently named the more advanced and hybrid techniques. With the third edition of The Data Warehouse Toolkit (Wiley, 201...

Internationalization Design Technics

Microstrategy Internationalization Design Technics MicroStrategy supports data internationalization through two different techniques. You can either provide translated data through the use of extra tables and columns, or you can provide separate databases to store your translated data. These techniques are described below: You can support data internationalization in your database by using separate tables and columns to store your translated data. You can use various combinations of tables and columns to support and identify the translated data in your database. To support displaying the name of each month in multiple languages, you can include the translated names in a separate column, one for each required language, within the same table. Each column can use a suffix to identify that the column contains translated data for a certain language. The same LU_MONTH_OF_YEAR table with translated data for the Spanish and German langua...

Personalizing file locations, email and file subscriptions using macros in Microstrategy

Personalizing file locations MSTr allows to dynamically specify the File Location and Backup File Location in a file device using macros. For example, if you specify the File Location as C:\Reports\{&RecipientName}\ , all subscriptions using that file device are delivered to subfolders of C:\Reports\ . Subscribed reports or documents for each recipient are delivered to a subfolder with that recipient’s name, such as C:\Reports\Jane Smith\ or C:\Reports\Hiro Protagonist\ . The table below lists the macros that can be used in the File Location and Backup File Location fields in a file device: Description Macro Date on which the subscription is sent {&Date} Time at which the subscription is sent {&Time} Name of the recipient {&RecipientName} User ID (32-character GUID) of the recipient {&RecipientID} Distribution Services add...

The logical table size calculation in Microstrategy

The logical table size calculation in Microstrategy The logical table size is an integer number that represents the granularity or level of aggregation of a particular table. It is called 'logical' because it is not related to the physical size of the tables (number of rows). It is calculated according to the attribute IDs that are present in the table and their level in the system hierarchy. Even though, the number does not reveal the actual number of rows in the table, it is an accurate way of measuring a table size without having to access its contents. MicroStrategy Engine utilizes an algorithm based on attribute keys to calculate the Logical Table Size (LTS): Given the following tables: The algorithm that calculates the table sizes performs the following steps: Calculate the number of levels per hierarchy: Hierarchy 1: 3 Hierarchy 2: 4 Calculate each attribute individual weight according to the level in the hierarchy (level in hierarchy/number of ...

Uniquely identifying data using Compound Key in Microstrategy

Uniquely identifying data in tables with Compound Key attribute: The types of keys that can be assigned to a table include: • Simple key requires only one column to identify a record uniquely within a table. • Compound key requires multiple columns to identify a unique record. . The following diagram shows how the different key structures can be used to identify a cal...

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...

Activate MicroStrategy Geospatial Services

Activate MicroStrategy Geospatial Services MicroStrategy 10.11 introduces our new mapping capability: MicroStrategy Geospatial Services, powered by Mapbox. This enhanced map visualization is available for dossiers on all interfaces including MicroStrategy Desktop, Workstation, Web and Library (Mobile included). With MicroStrategy Geospatial Services, MicroStrategy now offers advanced geospatial analytics features that allow users to get more out of their location data. This new feature is available in addition to the out-of-the-box ESRI maps. MicroStrategy Geospatial Services allows users to: Plot polygon shapes for most countries, down to the zip code level Perform powerful interaction between layers (progressively hide or show data layers as zoom levels change) Identify and resolve location name conflicts Add thresholds to data points, size markers for metrics, and color by for both attributes and metrics Fine tune clustering behavior when aggregating data on a ma...

Star schemas and aggregate (or summary) fact tables Aggregate tables can further improve query performance by reducing the number of rows over which higher-level metrics must be aggregated. However, the use of aggregate tables with dimension tables is not a valid physical modeling strategy. Whenever aggregation is performed over fact data, it is a general requirement that tables joined to the fact table must be at the same attribute level or at a higher level. If the auxiliary table is at a lower level, fact rows will be replicated prior to aggregation and this will result in inflated metric values (also known as "multiple counting"). With the above Time dimension table, a fact table at the level of Day functions correctly because there is exactly one row in DIM_TIME for each day. To aggregate the facts to the level of Quarter, it is valid to join the fact table to the dimension table and group by the quarter ID from the dimension table. Sql select DT...

Microstrategy Analytics

Search This Blog