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Microsoft certification
MCSA Solutions Associate
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3 treff ( i Bergen ) i MCSA Solutions Associate
 

Oslo 5 dager 22 500 kr
11 Sep
16 Oct
20 Nov
Upgrading Your Skills to Windows Server 2016 MCSA [+]
This five-day, instructor-led course explains how to implement and configure new Windows Server 2016 features and functionality. This course is for information technology (IT) professionals who want to upgrade their technical skills from Windows Server 2008 or Windows Server 2012 to Windows Server 2016. This course presumes a high level of knowledge about previous Windows Server technologies and skills equivalent to the Microsoft Certified Solutions Associate (MCSA): Windows Server 2008 or Windows Server 2012 credential.   This course is not a product-upgrade course, detailing considerations for migrating and upgrading students’ specific environment to Windows Server 2016. Rather, this course provides updates to students' existing Windows Server knowledge and skills, as they pertain to Windows Server 2016. [-]
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Oslo 5 dager 22 500 kr
18 Sep
06 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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Bergen Og 3 andre steder 3 dager 15 000 kr
28 Aug
04 Sep
11 Sep
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... [+]
The main purpose of this 5 day instructor led course is to give students a good understanding of the Transact-SQL language which is used by all SQL Server-related disciplines; namely, Database Administration, Database Development and Business Intelligence. As such, the primary target audience for this course is: Database Administrators, Database Developers and BI professionals.    After completing this course, students will be able to: Describe the basic architecture and concepts of Microsoft SQL Server 2016. Understand the similarities and differences between Transact-SQL and other computer languages. Write SELECT queries Query multiple tables Sort and filter data Describe the use of data types in SQL Server Modify data using Transact-SQL Use built-in functions Group and aggregate data Use subqueries Use table expressions Use set operators Use window ranking, offset and aggregate functions Implement pivoting and grouping sets Execute stored procedures Program with T-SQL Implement error handling Implement transactions Module 1: Introduction to Microsoft SQL Server 2016 This module introduces SQL Server, the versions of SQL Server, including cloud versions, and how to connect to SQL Server using SQL Server Management Studio. Lessons The Basic Architecture of SQL Server SQL Server Editions and Versions Getting Started with SQL Server Management Studio Lab : Working with SQL Server 2016 Tools After completing this module, you will be able to: Describe the architecture and editions of SQL Server 2012. Work with SQL Server Management Studio. Module 2: Introduction to T-SQL Querying This module introduces the elements of T-SQL and their role in writing queries, describes the use of sets in SQL Server, describes the use of predicate logic in SQL Server, and describes the logical order of operations in SELECT statements. Lessons Introducing T-SQL Understanding Sets Understanding Predicate Logic Understanding the Logical Order of Operations in SELECT statements Lab : Introduction to Transact-SQL Querying After completing this module, you will be able to: Describe the elements of T-SQL and their role in writing queries Describe the use of sets in SQL Server Describe the use of predicate logic in SQL Server Describe the logical order of operations in SELECT statements Module 3: Writing SELECT Queries This module introduces the fundamentals of the SELECT statement, focusing on queries against a single table. Lessons Writing Simple SELECT Statements Eliminating Duplicates with DISTINCT Using Column and Table Aliases Writing Simple CASE Expressions Lab : Writing Basic SELECT Statements After completing this module, you will be able to: Write simple SELECT statements. Eliminate duplicates using the DISTINCT clause. Use column and table aliases. Write simple CASE expressions. Module 4: Querying Multiple Tables This module explains how to write queries which combine data from multiple sources in SQL Server. The module introduces the use of JOINs in T-SQL queries as a mechanism for retrieving data from multiple tables. Lessons Understanding Joins Querying with Inner Joins Querying with Outer Joins Querying with Cross Joins and Self Joins Lab : Querying Multiple Tables After completing this module, you will be able to: Describe how multiple tables may be queried in a SELECT statement using joins. Write queries that use inner joins. Write queries that use outer joins. Write queries that use self-joins and cross joins. Module 5: Sorting and Filtering Data This module explains how to enhance queries to limit the rows they return, and to control the order in which the rows are displayed. The module also discusses how to resolve missing and unknown results. Lessons Sorting Data Filtering Data with Predicates Filtering with the TOP and OFFSET-FETCH Options Working with Unknown Values Lab : Sorting and Filtering Data After completing this module, you will be able to: Filter data with predicates in the WHERE clause. Sort data using ORDER BY. Filter data in the SELECT clause with TOP. Filter data with OFFSET and FETCH. Module 6: Working with SQL Server 2016 Data Types This module explains the data types SQL Server uses to store data. It introduces the many types of numeric and special-use data types. It also explains conversions between data types, and the importance of type precedence. Lessons Introducing SQL Server 2016 Data Types Working with Character Data Working with Date and Time Data Lab : Working with SQL Server 2016 Data Types After completing this module, you will be able to: Describe numeric data types, type precedence and type conversions. Write queries using character data types. Write queries using date and time data types. Module 7: Using DML to Modify Data This module describes the use of Transact-SQL Data Manipulation Language to perform inserts, updates, and deletes to your data. Lessons Inserting Data Modifying and Deleting Data Lab : Using DML to Modify Data After completing this module, you will be able to: Insert new data into your tables. Update and delete existing records in your tables. Module 8: Using Built-In Functions This module introduces the use of functions that are built in to SQL Server Denali, and will discuss some common usages including data type conversion, testing for logical results and nullability. Lessons Writing Queries with Built-In Functions Using Conversion Functions Using Logical Functions Using Functions to Work with NULL Lab : Using Built-In Functions After completing this module, you will be able to: Write queries with built-in scalar functions. Use conversion functions. Use logical functions. Use functions that work with NULL. Module 9: Grouping and Aggregating Data This module introduces methods for grouping data within a query, aggregating the grouped data and filtering groups with HAVING. The module is designed to help the student grasp why a SELECT clause has restrictions placed upon column naming in the GROUP BY clause as well as which columns may be listed in the SELECT clause. Lessons Using Aggregate Functions Using the GROUP BY Clause Filtering Groups with HAVING Lab : Grouping and Aggregating Data After completing this module, you will be able to: Write queries which summarize data using built-in aggregate functions. Use the GROUP BY clause to arrange rows into groups. Use the HAVING clause to filter out groups based on a search condition. Module 10: Using Subqueries This module will introduce the use of subqueries in various parts of a SELECT statement. It will include the use of scalar and multi-result subqueries, and the use of the IN and EXISTS operators. Lessons Writing Self-Contained Subqueries Writing Correlated Subqueries Using the EXISTS Predicate with Subqueries Lab : Using Subqueries After completing this module, you will be able to: Describe the uses of queries which are nested within other queries. Write self-contained subqueries which return scalar or multi-valued results. Write correlated subqueries which return scalar or multi-valued results. Use the EXISTS predicate to efficiently check for the existence of rows in a subquery. Module 11: Using Set Operators This module introduces the set operators UNION, INTERSECT, and EXCEPT to compare rows between two input sets. Lessons Writing Queries with the UNION Operator Using EXCEPT and INTERSECT Using APPLY Lab : Using SET Operators After completing this module, you will be able to: Write queries using UNION, EXCEPT, and INTERSECT operators. Use the APPLY operator.   [-]
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