Microsoft certification
MCSA Solutions Associate
MCSA - SQL Server 2016
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Oslo 5 dager 24 000 kr
25 Nov
The course will very likely be well attended by SQL power users who are not necessarily database-focused; namely, report writers, business analysts and client application... [+]
This course is designed to introduce students to Transact-SQL. It is designed in such a way that the first three days can be taught as a course to students requiring the knowledge for other courses in the SQL Server curriculum. Days 4 & 5 teach the remaining skills required to take exam 70-761.    After completing this course, students will be able to: Describe key capabilities and components of SQL Server 2016. Describe T-SQL, sets, and predicate logic. Write a single table SELECT statement. Write a multi-table SELECT statement. Write SELECT statements with filtering and sorting. Describe how SQL Server uses data types. Write DML statements. Write queries that use built-in functions. Write queries that aggregate data. Write subqueries. Create and implement views and table-valued functions. Use set operators to combine query results. Write queries that use window ranking, offset, and aggregate functions. Transform data by implementing pivot, unpivot, rollup and cube. Create and implement stored procedures. Add programming constructs such as variables, conditions, and loops to T-SQL code. Read the official course description here  [-]
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Oslo 5 dager 24 000 kr
25 Nov
This 4-day instructor led course describes how to implement a data warehouse platform to support a BI solution. [+]
Students will learn how to create a data warehouse with Microsoft® SQL Server® 2016 and with Azure SQL Data Warehouse, to implement ETL with SQL Server Integration Services, and to validate and cleanse data with SQL Server Data Quality Services and SQL Server Master Data Services. After completing this course, students will be able to: Describe the key elements of a data warehousing solution Describe the main hardware considerations for building a data warehouse Implement a logical design for a data warehouse Implement a physical design for a data warehouse Create columnstore indexes Implementing an Azure SQL Data Warehouse Describe the key features of SSIS Implement a data flow by using SSIS Implement control flow by using tasks and precedence constraints Create dynamic packages that include variables and parameters Debug SSIS packages Describe the considerations for implement an ETL solution Implement Data Quality Services Implement a Master Data Services model Describe how you can use custom components to extend SSIS Deploy SSIS projects Describe BI and common BI scenarios 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 DataLab : 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 DataLab : 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 [-]
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Oslo 5 dager 24 000 kr
This five-day instructor-led course teaches students how to implement a SQL Server 2016 Reporting Services solution for data analysis in an organization. [+]
The course discusses how to use the Reporting Services development tools to create and manage reports and implement self-service BI solutions.    After completing this course, students will be able to: Describe key features of data modelling within business intelligence Describe various report services data sources and how these are configured Create reports with report designer Configure reports with report designer and/or report builder Create SQL Server mobile reports Module 1: Introduction to Business Intelligence and Data Modelling In this module students will be introduced to the key concepts in business intelligence, and the Microsoft BI product suite. Lessons Introduction to business intelligence The Microsoft business intelligence platform Introduction to reporting services Lab : Exploring an enterprise BI solution After completing this module, you will be able to: Describe key concepts in business intelligence Describe the Microsoft BI platform Describe key concepts in reporting services Module 2: Reporting Services Data Describe various Report Services data sources and how these are configured. Lessons Data connections Connection strings Datasets Filters and parameters Lab : Configuring a data connection After completing this module, you will be able to: Describe data connections and connection strings Describe filters and parameters Module 3: Implementing reports Create reports with report designer or report builder. Lessons Creating a report with the report wizard Creating a report Showing data graphically in a report Lab : Creating a report After completing this module, you will be able to: Create a report using the report wizard Show data graphically Module 4: Configuring reports This module describes how to configure reports with report builder or report designer. Lessons Implementing filters and parameters Implementing sorting and grouping Publishing a report Lab : Create and Publish reports that include parameters After completing this module, you will be able to: Implement filters and parameters Implement sorting and grouping Publish a report Module 5: Creating Mobile Reports This module describes how to create SQL Server mobile reports. Lessons Overview of SQL Server mobile reports Preparing data for mobile reports Mobile report publisher Lab : Mobile reports After completing this module, you will be able to: Describe SQL Server mobile reports Prepare data for mobile reports Publish mobile reports Read the official course description here  [-]
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Oslo 3 dager 16 000 kr
This three-day instructor-led course is aimed at database professionals who fulfil a Business Intelligence (BI) developer role. [+]
This course looks at implementing multidimensional databases by using SQL Server Analysis Services (SSAS), and at creating tabular semantic data models for analysis with SSAS. After completing this course, students will be able to: Describe the components, architecture, and nature of a BI solution Create a multidimensional database with analysis services Implement dimensions in a cube Implement measures and measure groups in a cube Use MDX syntax Customize a cube Implement a tabular database Use DAX to query a tabular model Use data mining for predictive analysis 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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