B5280G IBM Cognos Data Manager: Build Data Marts with Enterprise Data (V10.2)

Overnet Education
A Segrate

2.250 
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Informazione importanti

  • Corso
  • Segrate
  • Durata:
    5 Giorni
Descrizione

A continuazione troverai il programma di questo corso disegnato per migliorare le tue competenze e permetterti di realizzare gli obiettivi stabiliti.
IBM Cognos Data Manager: Build Data Marts with Enterprise Data (V10.2) is a five-day, instructor-led course that teaches participants how to move, merge, consolidate, and transform data from a range of data sources to build and maintain subject-area data marts. In the process, students will create a catalog and add connections to data sources and targets. They will also deliver fact and dimension data to a data mart through the use of builds and the dimensional framework. In addition, students will learn how to automate common functionality and handle complex data issues, such as unbalanced hierarchical structures.

Informazione importanti
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Dove e quando

Inizio Luogo
Consultare
Segrate
Via Cassanese, 224, Palazzo Mantegna, Scala A, 20090, Milano, Italia
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Programma

Il centro presenta a continuazione il programma pensato per migliorare le tue competenze e permetterti di realizzare gli obiettivi stabiliti. Nel corso della formazione si alterneranno differenti moduli che ti permetteranno di acquisire le conoscenze sulle differenti tematiche proposte. Inscriviti per poter accedere alle seguenti materie.


  • Identify the purpose of IBM Cognos Data Manager
  • Define data warehousing and its key underlying concepts
  • Identify how Data Manager creates data warehouses
  • Examine the Data Manager architecture and user interface
  • Examine the purpose and contents of Data Manager catalogs
  • Create a catalog
  • Define connections to source and target data
  • Access data using SQLTerm
  • Configure flat data source files using SQLTXT
  • Examine the role of the dimensional framework in Data Manager
  • Examine hierarchies and their data sources
  • Identify how to create hierarchies from the columns of one table, the rows of one table, and from multiple tables
  • Test and view hierarchies
  • Create a hierarchy of static date values
  • Handle weeks in a date hierarchy
  • Examine Data Manager builds and build-related terminology
  • Create a dimension build using the Dimension Build wizard
  • Create a fact build using the Fact Build wizard
  • Test and execute a fact build
  • Document a catalog
  • Create catalog schema
  • Examine derivations
  • Apply operators and functions to derivations
  • Examine the derivation timing model
  • Add derivations to a fact build
  • Examine conformed dimensions and their advantages
  • Design conformed dimensions
  • Create conformed dimensions
  • Create data integrity lookups that use conformed dimensions
  • Create hierarchies manually using different approaches
  • Examine the features of a hierarchy
  • Examine literals
  • Set data access for hierarchy levels
  • Examine static and dynamic members
  • Examine fostering
  • Use derivations in a hierarchy
  • Examine slowly changing dimensions (SCDs)
  • Use surrogate keys in SCDs
  • Manage type 1 and type 2 changes to dimensional data
  • Load historical data for a dimension
  • Examine late arriving facts
  • Process late arriving facts in a fact build
  • Identify when to use lookups
  • Identify the requirements for a lookup
  • Create a translation lookup
  • Create an optional lookup
  • Add derived dimensions to fact builds
  • Configure fact and dimension delivery modules
  • Create indexes on fact and dimension tables
  • Update fact data using keys
  • Filter fact data
  • Merge duplicate fact data
  • Examine fact data integrity checking
  • Reject fact data
  • Aggregate fact data
  • Examine aggregate rules
  • Vertically restrict fact data
  • Horizontally restrict fact data
  • Partition fact data
  • Examine where job control fits into the data warehouse lifecycle
  • Create a JobStream
  • Add, link, and reposition nodes
  • Execute a JobStream and view the results
  • Differentiate between the Command Line Interface (CLI) and Data Manager Designer
  • Identify common commands
  • Use commands in a batch file
  • Examine variables
  • Examine user defined functions (UDFs)
  • Create an internal UDF
  • Create a user-defined variable
  • Examine balanced, unbalanced, and ragged hierarchies
  • Add a recursive level to a hierarchy
  • Identify ways to balance a hierarchy and delivered flattened data
  • Examine circular references
  • Examine pivoting
  • Use the single pivot technique
  • Use the advanced pivot technique
  • Examine reverse pivoting
  • Identify data quality and cleansing issues
  • Handle fostered and unmatched members
  • Perform debugging using SQLTerm and functions
  • Assess the quality of output data
  • Use build logging to ensure that data marts are being loaded properly
  • Perform dimension breaking
  • Manage memory and resources
  • Export DDL statements
  • Export and import components using packages
  • Search for components in a catalog using Navigator
  • Examine IBM Cognos BI
  • Identify the role of metadata dimensions, metadata collections, and metadata stars
  • Export Data Manager metadata to XML
  • Import Data Manager XML into Framework Manager
  • Use Data Manager metadata with IBM Cognos BI
  • Publish a data movement task to IBM Cognos Connection
  • Examine collaborative development support
  • Examine the source code repository
  • Examine the component dependency model
  • Identify planning considerations
  • Data warehouse design
  • The purpose of Data Manager components
  • Development steps in Data Manager to create data marts
  • Track dimensional changes and late arriving facts
  • Identify how to access SAP R/3 data sources using the IBM Cognos Data Manager Connector for SAP R/3 tool

Dotazione:
Each participant will have a station set up with operating systems and software needed for the exercises.


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