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Developing SQL Data Models 2017

training code: AA_20768 / ENG DL 3d / EN
Equivalent of authorized MS 20768 course.
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For more information, please contact the sales department. For more information, please contact the sales department.
3,000.00 PLN 3,690.00 PLN with TAX

The training is addressed to architects, designers and database developers responsible for designing, implementing and maintenance of Business Intelligence solutions based on SQL Server 2017.

Knowledge and practical skills related to design, developing, maintenance and optimising analytical database solutions based on MS SQL Server 2017.

Practical knowledge related to Transact-SQL, relational databases, basic knowledge from Microsoft Windows operational system and its key functions or knowledge from previous training. An ability to use English materials.

  • Training: English
  • Materials: English
  1. Introduction to Business Intelligence and data modelling

    • Introduction to business analysis
    • Microsoft business analysis platform
  2. Developing multi-level databases

    • Introduction to multi-level analysis
    • Developing data sources and data source views
    • Creating cubes
    • A review of cube securities
  3. Working with cubes and dimensions

    • Configuring dimensions
    • Defining hierarchy attributes
    • Sorting and grouping hierarchy
  4. Working with measures and groups

    • Working with measures
    • Working with group of measures
  5. Introduction to MDX

    • MDX fundamentals
    • Adding calculated elements to the cube
    • Using MDX language to cube query
  6. Expanding the cube

    • The use of Key Performance Indicators
    • The use of actions
    • The use of persperctives
    • The use of translations
  7. Implementing array data model in Analysis Services

    • Introduction to array data model
    • Developing array data model
    • The use of array data model in company
  8. Introduction to Data Analysis Expressions (DAX)

    • DAX fundamentals
    • The use of DAX to create calculated columns and measures in array data model
  9. Performing predictive analysis with Data Mining

    • A review of Data Mining
    • The use of data mining add-on to Excel
    • Creating your own Data Mining solution
    • Data Mining model validation
    • Mreging and consuming data with data mining model