MCSA SQL Server 2016 Business Intelligence Development (70-767 & 70-768)

  • Jan 15
    Monday 15/01/2018 - Wednesday 07/02/2018
    09:00 AM - 17:00 PM Horsens
    Hold-info
    Hold
    70-767
    Mon 15 Jan 09:00 - Wed 17 Jan 17:00 Horsens
    70-768
    Mon 05 Feb 09:00 - Wed 07 Feb 17:00 Horsens
    • Pakketilbud - Kr.28,695.00 ekskl. MOMS
    • Kr.37,390.00 ekskl. MOMS
    Ekskl. moms
  • Jan 15
    Monday 15/01/2018 - Wednesday 07/02/2018
    09:00 AM - 17:00 PM Værløse
    Hold-info
    Hold
    70-767
    Mon 15 Jan 09:00 - Wed 17 Jan 17:00 Værløse
    70-768
    Mon 05 Feb 09:00 - Wed 07 Feb 17:00 Værløse
    • Pakketilbud - Kr.28,695.00 ekskl. MOMS
    • Kr.37,390.00 ekskl. MOMS
    Ekskl. moms
  • Feb 26
    Monday 26/02/2018 - Wednesday 21/03/2018
    09:00 AM - 17:00 PM Værløse
    Hold-info
    Hold
    70-767
    Mon 26 Feb 09:00 - Wed 28 Feb 17:00 Værløse
    70-768
    Mon 19 Mar 09:00 - Wed 21 Mar 17:00 Værløse
    • Pakketilbud - Kr.28,695.00 ekskl. MOMS
    • Kr.37,390.00 ekskl. MOMS
    Ekskl. moms
  • Feb 26
    Monday 26/02/2018 - Wednesday 21/03/2018
    09:00 AM - 17:00 PM Horsens
    Hold-info
    Hold
    70-767
    Mon 26 Feb 09:00 - Wed 28 Feb 17:00 Horsens
    70-768
    Mon 19 Mar 09:00 - Wed 21 Mar 17:00 Horsens
    • Pakketilbud - Kr.28,695.00 ekskl. MOMS
    • Kr.37,390.00 ekskl. MOMS
    Ekskl. moms
  • Apr 09
    Monday 09/04/2018 - Wednesday 02/05/2018
    09:00 AM - 17:00 PM Horsens
    Hold-info
    Hold
    70-767
    Mon 09 Apr 09:00 - Wed 11 Apr 17:00 Horsens
    70-768
    Mon 30 Apr 09:00 - Wed 02 May 17:00 Horsens
    • Pakketilbud - Kr.28,695.00 ekskl. MOMS
    • Kr.37,390.00 ekskl. MOMS
    Ekskl. moms
  • Apr 09
    Monday 09/04/2018 - Wednesday 02/05/2018
    09:00 AM - 17:00 PM Værløse
    Hold-info
    Hold
    70-767
    Mon 09 Apr 09:00 - Wed 11 Apr 17:00 Værløse
    70-768
    Mon 30 Apr 09:00 - Wed 02 May 17:00 Værløse
    • Pakketilbud - Kr.28,695.00 ekskl. MOMS
    • Kr.37,390.00 ekskl. MOMS
    Ekskl. moms
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Kursusinfo

  • Dette kursus varer 6 dage
  • Der medfølger kursusmateriale til dette kursus
  • Dette kursus koster 8 klip på dit klippekort.
  • Fuld forplejning (Morgenmad, frokost, kage, kaffe og sodavand ad libitum)
  • Fuld beståelsesgaranti er inkluderet i prisen - Læs mere her
  • Eksamen er inkluderet i prisen
  • Med i prisen hører Practice Test
  • Du har i alt adgang til din kursus-pc i 3 uger

Varighed

Dette kursus varer 6 dage

Materialer

Der medfølger kursusmateriale til dette kursus

Klip på klippekort

Dette kursus koster 8 klip på dit klippekort.

Forplejning

Fuld forplejning (Morgenmad, frokost, eftermiddagskage samt kaffe og sodavand ad libitum)

Garanti for beståelse

Fuld beståelsesgaranti er inkluderet i prisen - Læs mere her

Eksamen

Alle eksamensforsøg er inkluderet i prisen

Practice Tests

Med i prisen hører Practice Test

Remote adgang

Du har i alt adgang til din kursus-pc i 3 uger

Download PDF

Hen PDF om kurset her

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Vi har hos Skillshouse udviklet et spændende MCSA SQL Server 2016 kursusforløb, som betyder at du sparer tid i forhold til de traditionelle kurser og samtidigt foregår undervisningen via masser af hands-on og best practices, som sikrer, bedre indlærring og derved bedre brug af dine nye færdigheder. 

Kort fortalt:

  • Du sparer mere end 8.000,-
  • Du sparer kursusdage
  • Garanteret beståelse og alle de forsøg du skal bruge 
  • Alt er inkluderet inkl. autoriseret Microsoft kursusmateriale.
  • Undervisningen foretages af Microsoft Certified Trainer (MCT)
  • Fuld forplejning og selvfølgelig alle de colaer og Red Bull du kan drikke 🙂

Undervisningen er fra 09.00 til 17.00

Microsoft MCSA SQL Server 2016 Business Intelligence Development titlen består af 2 eksamener/kurser:

- Implementing a SQL Data Warehouse (eksamen 70-767)
- Developing SQL Data Models (eksamen 70-768)

Nedenstående er beskrivelser af de 2 kurser, som indgår i MCSA SQL Server 2016 kursusforløbet.

NOTE: Cert Kit inkl. MeasureUp test er endnu ikke frigivet til eksamen: 70-767

Course Outline for Implementing a SQL Data Warehouse

Module 1: Introduction to Data Warehousing
Describe data warehouse concepts and architecture considerations.

Lessons
Overview of Data Warehousing
Considerations for a Data Warehouse Solution

Lab : Exploring a Data Warehouse Solution
After completing this module, you will be able to:
Describe the key elements of a data warehousing solution
Describe the key considerations for a data warehousing solution

Module 2: Planning Data Warehouse Infrastructure
This module describes the main hardware considerations for building a data warehouse.

Lessons
Considerations for Building a Data Warehouse
Data Warehouse Reference Architectures and Appliances

Lab : Planning Data Warehouse Infrastructure
After completing this module, you will be able to:
Describe the main hardware considerations for building a data warehouse
Explain how to use reference architectures and data warehouse appliances to create a data warehouse

Module 3: Designing and Implementing a Data Warehouse
This module describes how you go about designing and implementing a schema for a data warehouse.

Lessons
Logical Design for a Data Warehouse
Physical Design for a Data Warehouse

Lab : Implementing a Data Warehouse Schema
After completing this module, you will be able to:
Implement a logical design for a data warehouse
Implement a physical design for a data warehouse

Module 4: Columnstore Indexes
This module introduces Columnstore Indexes.

Lessons
Introduction to Columnstore Indexes
Creating Columnstore Indexes
Working with Columnstore Indexes

Lab : Using Columnstore Indexes
After completing this module, you will be able to:
Create Columnstore indexes
Work with Columnstore Indexes

Module 5: Implementing an Azure SQL Data Warehouse
This module describes Azure SQL Data Warehouses and how to implement them.

Lessons
Advantages of Azure SQL Data Warehouse
Implementing an Azure SQL Data Warehouse
Developing an Azure SQL Data Warehouse
Migrating to an Azure SQ Data Warehouse

Lab : Implementing an Azure SQL Data Warehouse
After completing this module, you will be able to:
Describe the advantages of Azure SQL Data Warehouse
Implement an Azure SQL Data Warehouse
Describe the considerations for developing an Azure SQL Data Warehouse
Plan for migrating to Azure SQL Data Warehouse

Module 6: Creating an ETL Solution
At the end of this module you will be able to implement data flow in a SSIS package.

Lessons
Introduction to ETL with SSIS
Exploring Source Data
Implementing Data Flow

Lab : Implementing Data Flow in an SSIS Package
After completing this module, you will be able to:
Describe ETL with SSIS
Explore Source Data
Implement a Data Flow

Module 7: Implementing Control Flow in an SSIS Package
This module describes implementing control flow in an SSIS package.

Lessons
Introduction to Control Flow
Creating Dynamic Packages
Using Containers

Lab : Implementing Control Flow in an SSIS Package
Lab : Using Transactions and Checkpoints
After completing this module, you will be able to:
Describe control flow
Create dynamic packages
Use containers

Module 8: Debugging and Troubleshooting SSIS Packages
This module describes how to debug and troubleshoot SSIS packages.

Lessons
Debugging an SSIS Package
Logging SSIS Package Events
Handling Errors in an SSIS Package

Lab : Debugging and Troubleshooting an SSIS Package
After completing this module, you will be able to:
Debug an SSIS package
Log SSIS package events
Handle errors in an SSIS package

Module 9: Implementing an Incremental ETL Process
This module describes how to implement an SSIS solution that supports incremental DW loads and changing data.

Lessons
Introduction to Incremental ETL
Extracting Modified Data
Temporal Tables

Lab : Extracting Modified Data
Lab : Loading Incremental Changes
After completing this module, you will be able to:
Describe incremental ETL
Extract modified data
Describe temporal tables

Module 10: Enforcing Data Quality
This module describes how to implement data cleansing by using Microsoft Data Quality services.

Lessons
Introduction to Data Quality
Using Data Quality Services to Cleanse Data
Using Data Quality Services to Match Data

Lab : Cleansing Data
Lab : De-duplicating Data
After completing this module, you will be able to:
Describe data quality services
Cleanse data using data quality services
Match data using data quality services
De-duplicate data using data quality services

Module 11: Using Master Data Services
This module describes how to implement master data services to enforce data integrity at source.

Lessons
Master Data Services Concepts
Implementing a Master Data Services Model
Managing Master Data
Creating a Master Data Hub

Lab : Implementing Master Data Services
After completing this module, you will be able to:
Describe the key concepts of master data services
Implement a master data service model
Manage master data
Create a master data hub

Module 12: Extending SQL Server Integration Services (SSIS)
This module describes how to extend SSIS with custom scripts and components.

Lessons
Using Custom Components in SSIS
Using Scripting in SSIS

Lab : Using Scripts and Custom Components
After completing this module, you will be able to:
Use custom components in SSIS
Use scripting in SSIS

Module 13: Deploying and Configuring SSIS Packages
This module describes how to deploy and configure SSIS packages.

Lessons
Overview of SSIS Deployment
Deploying SSIS Projects
Planning SSIS Package Execution

Lab : Deploying and Configuring SSIS Packages
After completing this module, you will be able to:
Describe an SSIS deployment
Deploy an SSIS package
Plan SSIS package execution

Module 14: Consuming Data in a Data Warehouse
This module describes how to debug and troubleshoot SSIS packages.

Lessons
Introduction to Business Intelligence
Introduction to Reporting
An Introduction to Data Analysis
Analyzing Data with Azure SQL Data Warehouse

Lab : Using Business Intelligence Tools
After completing this module, you will be able to:
Describe at a high level business intelligence
Show an understanding of reporting
Show an understanding of data analysis
Analyze data with Azure SQL data warehouse

Course Outline for Developing SQL Data Models

Module 1: Introduction to Business Intelligence and Data Modeling
This module introduces key BI concepts and the Microsoft BI product suite.

Lessons
Introduction to Business Intelligence
The Microsoft business intelligence platform

Lab : Exploring a Data Warehouse
After completing this module, you will be able to:
Describe the concept of business intelligence
Describe the Microsoft business intelligence platform

Module 2: Creating Multidimensional Databases
This module describes the steps required to create a multidimensional database with analysis services.

Lessons
Introduction to multidimensional analysis
Creating data sources and data source views
Creating a cube
Overview of cube security

Lab : Creating a multidimensional database
After completing this module, you will be able to:
Use multidimensional analysis
Create data sources and data source views
Create a cube
Describe cube security

Module 3: Working with Cubes and Dimensions
This module describes how to implement dimensions in a cube.

Lessons
Configuring dimensions
Define attribute hierarchies
Sorting and grouping attributes

Lab : Working with Cubes and Dimensions
After completing this module, you will be able to:
Configure dimensions
Define attribute hierarchies.
Sort and group attributes

Module 4: Working with Measures and Measure Groups
This module describes how to implement measures and measure groups in a cube.

Lessons
Working with measures
Working with measure groups

Lab : Configuring Measures and Measure Groups
After completing this module, you will be able to:
Work with measures
Work with measure groups

Module 5: Introduction to MDX
This module describes the MDX syntax and how to use MDX.

Lessons
MDX fundamentals
Adding calculations to a cube
Using MDX to query a cube

Lab : Using MDX
After completing this module, you will be able to:
Describe the fundamentals of MDX
Add calculations to a cube
Query a cube using MDX

Module 6: Customizing Cube Functionality
This module describes how to customize a cube.

Lessons
Implementing key performance indicators
Implementing actions
Implementing perspectives
Implementing translations

Lab : Customizing a Cube
After completing this module, you will be able to:
Implement key performance indicators
Implement actions
Implement perspectives
Implement translations

Module 7: Implementing a Tabular Data Model by Using Analysis Services
This module describes how to implement a tabular data model in PowerPivot.

Lessons
Introduction to tabular data models
Creating a tabular data model
Using an analysis services tabular model in an enterprise BI solution

Lab : Working with an Analysis services tabular data model
After completing this module, you will be able to:
Describe tabular data models
Create a tabular data model
Be able to use an analysis services tabular data model in an enterprise BI solution

Module 8: Introduction to Data Analysis Expression (DAX)
This module describes how to use DAX to create measures and calculated columns in a tabular data model.

Lessons
DAX fundamentals
Using DAX to create calculated columns and measures in a tabular data model

Lab : Creating Calculated Columns and Measures by using DAX
After completing this module, you will be able to:
Describe the fundamentals of DAX
Use DAX to create calculated columns and measures in a tabular data model

Module 9: Performing Predictive Analysis with Data Mining
This module describes how to use data mining for predictive analysis.

Lessons
Overview of data mining
Using the data mining add-in for Excel
Creating a custom data mining solution
Validating a data mining model
Connecting to and consuming a data mining model

Lab : Perform Predictive Analysis with Data Mining
After completing this module, you will be able to:
Describe data mining
Use the data mining add-in for Excel
Create a custom data mining solution
Validate a data mining solution
Connect to and consume a data mining solution

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