MicroStrategy Intelligent Cubes – Learn MicroStrategy starting from Overview, Environment Setup, Desktop, Architecture, Components Overview, Importing data . You can create Intelligent Cubes and publish them as a shared data source for the users to build reports from. Intelligent Cubes provide the fast response time. Intelligent cubes are multi-dimensional, in-memory copies of data that can be queried and accessed by many different documents and reports. Basically, the.
View Reports are a similar jntelligent. Generally MicroStrategy follows 3 kinds of architectures. Edit and enter the report editor. Share Facebook Email Twitter Reddit.
MicroStrategy – Intelligent Cubes
Other advantage is the fact that the redundant data is not transferred across the network. Over new eBooks and Videos added each month. All subsequent requests for the same report are processed using the saved report cache, given that certain criteria are met such as matching report ID, filter ID, security ID, and so on. How do you feel about the new design? Time-based and other comparisons Year-to-date transformation example Transformation metrics in the Metric Editor Compound metrics Compound metric example Smart subtotals Formula join type for compound metrics Creating metrics by combining metrics, filters, and transformations Metric subtotals Displaying subtotals on reports Defining subtotal defaults Disabling subtotals Metric functions Rank Count Running and moving sums and averages N-tile First and Last Creating your own plug-in functions Integrating R analytics into MicroStrategy Apply functions: Le istruzioni non hanno dato il risultato previsto.
Intelligent Cubes: Dynamic Sourcing vs View Reports
Report Data and Calculations Before you begin Level metrics: Drilling up, down, across, or to a template Drill path settings Drill map association: Customers who live in the same city as call centers Example: These reports allow data to be returned from the data warehouse, stored in Intelligence Server memory, and then shared among multiple reports.
No grouping Using a hierarchy as the target of micgostrategy metric level Level metrics: Join the lookup tables including its description forms columns with the fact table and filter it with the report filter, and then normalize this last table into a fact table with fact columns plus all the attribute ID columns, and into different lookup table, one for each attribute.
The internal testing shows that this method is in general better than any other method, and that is why this method is the default one.
MicroStrategy 9 introduced a game changing feature in Intelligent Cubes. When the specific cases specified in the other methods are meet. Just like Derived Metrics, these are Attribute Elements think Consolidations that can be defined and used at run time or saved as Report Objects.
Subsequent requests for the same report take advantage of the personal Intelligent Cube without having to ij the report against the data warehouse.
Rather than returning data from the data warehouse for a single report, you can return sets of data from your data warehouse and save them directly to Intelligence Server memory.
One of the most common use case – which is used in MicroStrategy – to apply left outer join at specific levels i. Merci de vos commentaires. Microstraregy instructions ne fonctionnaient pas. Grouping elements from multiple attributes Prompted filters: If we have small lookup table the processing power and processing time needed to generate the resulting relationship tables will be minimal.
The logic to match subsequent report requests with the appropriate personal Intelligent Cube is automatically handled within the MicroStrategy platform. Getting certified to the highest level in the technology that i work is always a dream and it had become true for me in 3 yrs of experience that i gained so far.
Whenever a report executes against a data warehouse and returns a new set of data, a personal Intelligent Cube is created automatically. You’re currently viewing a course logged out Sign In.
Updating an Intelligent Cube is incredibly easy. Data versus display Intelligent Cubes Totaling and subtotaling data on reports About subtotals Custom inteligent subtotals Subtotals and memory usage Sorting data on reports Formatting a report Formatting report cell data Understanding how formatting impacts report display Order of layers Autostyles: Standard grouping Level metrics review: Make sure intellignt report designers are familiar with the Intelligent Cube design best practices found in Governing Intelligent Cube Memory Usage.
A practical overview About the report level of a metric Specifying metric levels Displaying expression syntax: Mastering Business Intelligence with MicroStrategy. Exporting documents as PDFs Opening documents in separate browser windows: Level metrics Elements of a metric level Level metrics: The process of this method is the following: Overview Approaches for data mining with MicroStrategy The Data Mining Services workflow Predictive metrics and performance Creating a dataset report Data mining dataset reports Guidelines for creating a dataset report Inputs for predictive metrics Using non-MicroStrategy dataset reports Creating a predictive model Using MicroStrategy Using third-party data mining applications Importing the predictive model Importing predictive models for MDX cubes Aggregating predictive metrics Using the predictive metric Using the predictive metric in reports and documents Using the predictive metric in other objects Predictive Model Viewer Data mining examples Revenue forecasting example using linear and seasonal regression Campaign management example using logistic regression Segmentation example using cluster analysis Microstrrategy churn example using decision tree analysis Campaign management example: Redundancy on the intslligent affects several processes later on: When to use each population method summary table:.
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