BI Architect Master's Program

·      This Lecture 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 Tools

·       Working with SQL Server Management Studio

·       Creating and Organizing T-SQL Scripts

·       Using Books Online

·       After completing this Lecture, you will be able to:

·       Describe relational databases and Transact-SQL queries.

·       Describe the on-premise and cloud-based editions and versions of SQL Server.

·       Describe how to use SQL Server Management Studio (SSMS) to connect to an instance of SQL Server, explore the databases contained in the instance, and work with script files that contain T-SQL queries.

·       This Lecture describes 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.

·       Lessons

·       Introducing T-SQL

·       Understanding Sets

·       Understanding Predicate Logic

·       Understanding the Logical Order of Operations in SELECT statements

·       Lab : Introduction to T-SQL Querying

·       Executing Basic SELECT Statements

·       Executing Queries that Filter Data using Predicates

·       Executing Queries That Sort Data Using ORDER BY

·       After completing this Lecture, you will be able to:

·       Describe the role of T-SQL in writing SELECT statements.

·       Describe the elements of the T-SQL language and which elements will be useful in writing queries.

·       Describe the concepts of the set theory, one of the mathematical underpinnings of relational databases, and to help you apply it to how you think about querying SQL Server

·       Describe predicate logic and examine its application to querying SQL Server.

·       Explain the elements of a SELECT statement, delineate the order in which the elements are evaluated, and then apply this understanding to a practical approach to writing queries.

·       This Lecture 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

·       Writing Simple SELECT Statements

·       Eliminating Duplicates Using DISTINCT

·       Using Column and Table Aliases

·       Using a Simple CASE Expression

·       After completing this Lecture, you will be able to:

·       Describe the structure and format of the SELECT statement, as well as enhancements that will add functionality and readability to your queries

·       Describe how to eliminate duplicates using the DISTINCT clause

·       Describe the use of column and table aliases

·       Understand and use CASE expressions

·       This Lecture describes how to write queries that combine data from multiple sources in Microsoft SQL Server.

·       Lessons

·       Understanding Joins

·       Querying with Inner Joins

·       Querying with Outer Joins

·       Querying with Cross Joins and Self Joins

·       Lab : Querying Multiple Tables

·       Writing Queries that use Inner Joins

·       Writing Queries that use Multiple-Table Inner Joins

·       Writing Queries that use Self-Joins

·       Writing Queries that use Outer Joins

·       Writing Queries that use Cross Joins

·       After completing this Lecture, you will be able to:

·       Explain the fundamentals of joins in SQL Server

·       Write inner join queries

·       Write queries that use outer joins

·       Use additional join types

·       This Lecture describes how to implement sorting and filtering.

·       Lessons

·       Sorting Data

·       Filtering Data with Predicates

·       Filtering Data with TOP and OFFSET-FETCH

·       Working with Unknown Values

·       Lab : Sorting and Filtering Data

·       Writing Queries that Filter Data using a WHERE Clause

·       Writing Queries that Sort Data Using an ORDER BY Clause

·       Writing Queries that Filter Data Using the TOP Option

·       Write Queries that filter data using the OFFSET-FETCH clause

·       After completing this Lecture, you will be able to:

·       Explain how to add an ORDER BY clause to your queries to control the order of rows displayed in your query's output

·       Explain how to construct WHERE clauses to filter out rows that do not match the predicate.

·       Explain how to limit ranges of rows in the SELECT clause using a TOP option.

·       Explain how to limit ranges of rows using the OFFSET-FETCH option of an ORDER BY clause.

·       Explain how three-valued logic accounts for unknown and missing values, how SQL Server uses NULL to mark missing values, and how to test for NULL in your queries.

·       This Lecture introduces the data types SQL Server uses to store data.

·       Lessons

·       Introducing SQL Server Data Types

·       Working with Character Data

·       Working with Date and Time Data

·       Lab : Working with SQL Server Data Types

·       Writing Queries that Return Date and Time Data

·       Writing Queries that use Date and Time Functions

·       Writing Queries That Return Character Data

·       Writing Queries That Return Character Functions

·       After completing this Lecture, you will be able to:

·       Explore many of the data types SQL Server uses to store data and how data types are converted between types

·       Explain the SQL Server character-based data types, how character comparisons work, and some common functions you may find useful in your queries

·       Describe data types that are used to store temporal data, how to enter dates and times so they will be properly parsed by SQL Server, and how to manipulate dates and times with built-in functions.

·       This Lecture describes how to create DML queries, and why you would want to.

·       Lessons

·       Adding Data to Tables

·       Modifying and Removing Data

·       Generating automatic column values

·       Lab : Using DML to Modify Data

·       Inserting Records with DML

·       Updating and Deleting Records Using DML

·       After completing this Lecture, you will be able to:

·       Use INSERT and SELECT INTO statements

·       Use UPDATE, MERGE, DELETE, and TRUNCATE.

·       This Lecture introduces some of the many built in functions in SQL Server.

·       Lessons

·       Writing Queries with Built-In Functions

·       Using Conversion Functions

·       Using Logical Functions

·       Using Functions to Work with NULL

·       Lab : Using Built-In Functions

·       Writing Queries That Use Conversion Functions

·       Writing Queries that use Logical Functions

·       Writing Queries that Test for Nullability

·       After completing this Lecture, you will be able to:

·       Describe the types of functions provided by SQL Server, and then focus on working with scalar functions

·       Explain how to explicitly convert data between types using several SQL Server functions

·       Describe how to use logical functions that evaluate an expression and return a scalar result.

·       Describe additional functions for working with NULL

·       This Lecture describes how to use aggregate functions.

·       Lessons

·       Using Aggregate Functions

·       Using the GROUP BY Clause

·       Filtering Groups with HAVING

·       Lab : Grouping and Aggregating Data

·       Writing Queries That Use the GROUP BY Clause

·       Writing Queries that Use Aggregate Functions

·       Writing Queries that Use Distinct Aggregate Functions

·       Writing Queries that Filter Groups with the HAVING Clause

·       After completing this Lecture, you will be able to:

·       Describe the built-in aggregate function in SQL Server and write queries using it.

·       Write queries that separate rows using the GROUP BY clause.

·       Write queries that use the HAVING clause to filter groups.

·       This Lecture describes several types of subquery and how and when to use them.

·       Lessons

·       Writing Self-Contained Subqueries

·       Writing Correlated Subqueries

·       Using the EXISTS Predicate with Subqueries

·       Lab : Using Subqueries

·       Writing Queries That Use Self-Contained Subqueries

·       Writing Queries That Use Scalar and Multi-Result Subqueries

·       Writing Queries That Use Correlated Subqueries and an EXISTS Clause

·       After completing this Lecture, you will be able to:

·       Describe where subqueries may be used in a SELECT statement.

·       Write queries that use correlated subqueries in a SELECT statement

·       Write queries that use EXISTS predicates in a WHERE clause to test for the existence of qualifying rows

·       Use the EXISTS predicate to efficiently check for the existence of rows in a subquery.

·      Previously in this course, you learned about using subqueries as an expression that returned results to an outer calling query. Like subqueries, table expressions are query expressions, but table expressions extend this idea by allowing you to name them and to work with their results as you would work with data in any valid relational table. Microsoft SQL Server supports four types of table expressions: derived tables, common table expression (CTEs), views, and inline table-valued functions (TVFs). In this Lecture, you will learn to work with these forms of table expressions and learn how to use them to help create a modular approach to writing queries.

·       Lessons

·       Using Views

·       Using Inline Table-Valued Functions

·       Using Derived Tables

·       Using Common Table Expressions

·       Lab : Using Table Expressions

·       Writing Queries That Use Views

·       Writing Queries That Use Derived Tables

·       Writing Queries That Use Common Table Expressions (CTEs)

·       Writing Queries That Use Inline Table-Valued Expressions (TVFs)

·       After completing this Lecture, you will be able to:

·       Write queries that return results from views.

·       Use the CREATE FUNCTION statement to create simple inline TVFs.

·       Write queries that create and retrieve results from derived tables.

·       Write queries that create CTEs and return results from the table expression.

·       This Lecture introduces how to use 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

·       Writing Queries That Use UNION Set Operators and UNION ALL

·       Writing Queries That Use CROSS APPLY and OUTER APPLY Operators

·       Writing Queries That Use the EXCEPT and INTERSECT Operators

·       After completing this Lecture, students will be able to:

·       Write queries that use UNION to combine input sets.

·       Write queries that use UNION ALL to combine input sets

·       Write queries that use the EXCEPT operator to return only rows in one set but not another.

·       Write queries that use the INTERSECT operator to return only rows that are present in both sets

·       Write queries using the CROSS APPLY operator.

·       Write queries using the OUTER APPLY operator

·    This Lecture describes the benefits to using window functions. Restrict window functions to rows defined in an OVER clause, including partitions and frames. Write queries that use window functions to operate on a window of rows and return ranking, aggregation, and offset comparison results.

·       Lessons

·       Creating Windows with OVER

·       Exploring Window Functions

·       Lab : Using Windows Ranking, Offset, and Aggregate Functions

·       Writing Queries that use Ranking Functions

·       Writing Queries that use Offset Functions

·       Writing Queries that use Window Aggregate Functions

·       After completing this Lecture, students will be able to:

·       Describe the T-SQL components used to define windows, and the relationships between them.

·       Write queries that use the OVER clause, with partitioning, ordering, and framing to define windows

·       Write queries that use window aggregate functions.

·       Write queries that use window ranking functions.

·       Write queries that use window offset functions

·       This Lecture describes write queries that pivot and unpivot result sets. Write queries that specify multiple groupings with grouping sets

·       Lessons

·       Writing Queries with PIVOT and UNPIVOT

·       Working with Grouping Sets

·       Lab : Pivoting and Grouping Sets

·       Writing Queries that use the PIVOT Operator

·       Writing Queries that use the UNPIVOT Operator

·       Writing Queries that use the GROUPING SETS CUBE and ROLLUP Subclauses

·       After completing this Lecture, students will be able to:

·       Describe how pivoting data can be used in T-SQL queries.

·       Write queries that pivot data from rows to columns using the PIVOT operator.

·       Write queries that unpivot data from columns back to rows using the UNPIVOT operator.

·       Write queries using the GROUPING SETS subclause.

·       Write queries that use ROLLUP AND CUBE.

·       Write queries that use the GROUPING_ID function.

·   This Lecture describes how to return results by executing stored procedures. Pass parameters to procedures. Create simple stored procedures that encapsulate a SELECT statement. Construct and execute dynamic SQL with EXEC and sp_executesql.

·       Lessons

·       Querying Data with Stored Procedures

·       Passing Parameters to Stored procedures

·       Creating Simple Stored Procedures

·       Working with Dynamic SQL

·       Lab : Executing Stored Procedures

·       Using the EXECUTE statement to Invoke Stored Procedures

·       Passing Parameters to Stored procedures

·       Executing System Stored Procedures

·       After completing this Lecture, students will be able to:

·       Describe stored procedures and their use.

·       Write T-SQL statements that execute stored procedures to return data.

·       Write EXECUTE statements that pass input parameters to stored procedures.

·       Write T-SQL batches that prepare output parameters and execute stored procedures.

·       Use the CREATE PROCEDURE statement to write a stored procedure.

·       Create a stored procedure that accepts input parameters.

·       Describe how T-SQL can be dynamically constructed.

·       Write queries that use dynamic SQL.

·       This Lecture describes how to enhance your T-SQL code with programming elements.

·       Lessons

·       T-SQL Programming Elements

·       Controlling Program Flow

·       Lab : Programming with T-SQL

·       Declaring Variables and Delimiting Batches

·       Using Control-Of-Flow Elements

·       Using Variables in a Dynamic SQL Statement

·       Using Synonyms

·       After completing this Lecture, students will be able to:

·       Describe how Microsoft SQL Server treats collections of statements as batches.

·       Create and submit batches of T-SQL code for execution by SQL Server.

·       Describe how SQL Server stores temporary objects as variables.

·       Write code that declares and assigns variables.

·       Create and invoke synonyms

·       Describe the control-of-flow elements in T-SQL.

·       Write T-SQL code using IF...ELSE blocks.

·       Write T-SQL code that uses WHILE.

·       This Lecture introduces error handling for T-SQL.

·       Lessons

·       Implementing T-SQL error handling

·       Implementing structured exception handling

·       Lab : Implementing Error Handling

·       Redirecting errors with TRY/CATCH

·       Using THROW to pass an error message back to a client

·       After completing this Lecture, students will be able to:

·       Implement T-SQL error handling.

·       Implement structured exception handling.

·       This Lecture describes how to implement transactions.

·       Lessons

·       Transactions and the database engines

·       Controlling transactions

·       Lab : Implementing Transactions

·       Controlling transactions with BEGIN, COMMIT, and ROLLBACK

·       Adding error handling to a CATCH block

·       After completing this Lecture, students will be able to:

·       Describe transactions and the differences between batches and transactions.

·       Describe batches and how they are handled by SQL Server.

·       Create and manage transactions with transaction control language (TCL) statements.

·       Use SET XACT_ABORT to define SQL Servers handling of transactions outside TRY/CATCH blocks.

·     Before beginning to work with Microsoft SQL Server in either a development or an administration role, it is important to understand the scope of the SQL Server platform. In particular, it is useful to understand that SQL Server is not just a database engine—it is a complete platform for managing enterprise data.SQL Server provides a strong data platform for all sizes of organizations, in addition to a comprehensive set of tools to make development easier, and more robust.

·       Lessons

·       Introduction to the SQL Server Platform

·       SQL Server Database Development Tasks

·       After completing this Lecture, you will be able to:

·       Describe the SQL Server platform.

·       Use SQL Server administration tools.

·       In a relational database management system (RDBMS), user and system data is stored in tables. Each table consists of a set of rows that describe entities and a set of columns that hold the attributes of an entity. For example, a Customer table might have columns such as CustomerName and CreditLimit, and a row for each customer. In Microsoft SQL Server data management software tables are contained within schemas that are very similar in concept to folders that contain files in the operating system. Designing tables is one of the most important tasks that a database developer undertakes, because incorrect table design leads to the inability to query the data efficiently.After an appropriate design has been created, it is important to know how to correctly implement the design.

·       Lessons

·       Designing Tables

·       Data Types

·       Working with Schemas

·       Creating and Altering Tables

·       Lab : Designing and Implementing Tables

·       Designing Tables

·       Creating Schemas

·       Creating Tables

·       After completing this Lecture, you will be able to:

·       Design tables using normalization, primary and foreign keys.

·       Work with identity columns.

·       Understand built-in and user data types.

·       Use schemas in your database designs to organize data, and manage object security.

·       Work with computed columns and temporary tables.

·       The physical design of a database can have a significant impact on the ability of the database to meet the storage and performance requirements set out by the stakeholders. Designing a physical database implementation includes planning the file groups, how to use partitioning to manage large tables, and using compression to improve storage and performance. Temporal tables are a new feature in SQL Server and offer a straightforward solution to collecting changes to your data.

·       Lessons

·       Partitioning Data

·       Compressing Data

·       Temporal Tables

·       Lab : Using Advanced Table Designs

·       Partitioning Data

·       Compressing Data

·       After completing this Lecture, you will be able to:

·       Describe the considerations for using partitioned tables in a SQL Server database.

·       Plan for using data compression in a SQL Server database.

·       Use temporal tables to store and query changes to your data.

·       The quality of data in your database largely determines the usefulness and effectiveness of applications that rely on it—the success or failure of an organization or a business venture could depend on it. Ensuring data integrity is a critical step in maintaining high-quality data. You should enforce data integrity at all levels of an application from first entry or collection through storage. Microsoft SQL Server data management software provides a range of features to simplify the job.

·       Lessons

·       Enforcing Data Integrity

·       Implementing Data Domain Integrity

·       Implementing Entity and Referential Integrity

·       Lab : Using Data Integrity Through Constraints

·       Add Constraints

·       Test the Constraints

·       After completing this Lecture, you will be able to:

·       Describe the options for enforcing data integrity, and the levels at which they should be applied.

·       Implement domain integrity through options such as check, unique, and default constraints.

·       Implement referential integrity through primary and foreign key constraints.

·       An index is a collection of pages associated with a table. Indexes are used to improve the performance of queries or enforce uniqueness. Before learning to implement indexes, it is helpful to understand how they work, how effective different data types are when used within indexes, and how indexes can be constructed from multiple columns. This Lecture discusses table structures that do not have indexes, and the different index types available in Microsoft SQL Server.

·       Lessons

·       Core Indexing Concepts

·       Data Types and Indexes

·       Heaps, Clustered, and Nonclustered Indexes

·       Single Column and Composite Indexes

·       Lab : Implementing Indexes

·       Creating a Heap

·       Creating a Clustered Index

·       Creating a Covered Index

·       After completing this Lecture, you will be able to:

·       Explain core indexing concepts.

·       Evaluate which index to use for different data types.

·       Describe the difference between single and composite column indexes.

·       Indexes play an important role in enabling SQL Server to retrieve data from a database quickly and efficiently. This Lecture discusses advanced index topics including covering indexes, the INCLUDE clause, query hints, padding and fill factor, statistics, using DMOs, the Database Tuning Advisor, and Query Store.

·       Lessons

·       Index Strategies

·       Managing Indexes

·       Execution Plans

·       The Database Engine Tuning Advisor

·       Query Store

·       Lab : Optimizing Indexes

·       Using Query Store

·       Heaps and Clustered Indexes

·       Creating a Covered Index

·       After completing this Lecture, you will be able to:

·       What a covering index is, and when to use one.

·       The issues involved in managing indexes.

·       Actual and estimated execution plans.

·       How to use Database Tuning Advisor to improve the performance of queries.

·       How to use Query Store to improve query performance.

·       Introduced in Microsoft SQL Server 2012, columnstore indexes are used in large data warehouse solutions by many organizations. This Lecture highlights the benefits of using these indexes on large datasets; the improvements made to columnstore indexes in SQL Server 2016; and the considerations needed to use columnstore indexes effectively in your solutions.

·       Lessons

·       Introduction to Columnstore Indexes

·       Creating Columnstore Indexes

·       Working with Columnstore Indexes

·       Lab : Using Columnstore Indexes

·       Creating a Columnstore Index

·       Create a Memory Optimized Columnstore Table

·       After completing this Lecture, you will be able to:

·       Describe columnstore indexes and identify suitable scenarios for their use.

·       Create clustered and nonclustered columnstore indexes.

·       Describe considerations for using columnstore indexes.

·       This Lecture describes the design and implementation of views. A view is a special type of query—one that is stored and can be used in other queries—just like a table. With a view, only the query definition is stored on disk; not the result set. The only exception to this is indexed views, when the result set is also stored on disk, just like a table.Views simplify the design of a database by providing a layer of abstraction, and hiding the complexity of table joins. Views are also a way of securing your data by giving users permissions to use a view, without giving them permissions to the underlying objects. This means data can be kept private, and can only be viewed by appropriate users.

·       Lessons

·       Introduction to Views

·       Creating and Managing Views

·       Performance Considerations for Views

·       Creating Standard Views

·       Creating an Updateable view

·       After completing this Lecture, you will be able to:

·       Understand the role of views in database design.

·       Create and manage views.

·       Understand the performance considerations with views.

·       This Lecture describes the design and implementation of stored procedures.

·       Lessons

·       Introduction to Stored Procedures

·       Working with Stored Procedures

·       Implementing Parameterized Stored Procedures

·       Controlling Execution Context

·       Lab : Designing and Implementing Stored Procedures

·       Create Stored procedures

·       Create Parameterized Stored procedures

·       Changes Stored Procedure Execution Context

·       After completing this Lecture, you will be able to:

·       Understand what stored procedures are, and what benefits they have.

·       Design, create, and alter stored procedures.

·       Control the execution context of stored procedures.

·       Implement stored procedures that use parameters.

·      Functions are routines that you use to encapsulate frequently performed logic. Rather than having to repeat the function logic in many places, code can call the function. This makes code more maintainable, and easier to debug. In this Lecture, you will learn to design and implement user-defined functions (UDFs) that enforce business rules or data consistency. You will also learn how to modify and maintain existing functions.

·       Lessons

·       Overview of Functions

·       Designing and Implementing Scalar Functions

·       Designing and Implementing Table-Valued Functions

·       Considerations for Implementing Functions

·       Alternatives to Functions

·       Lab : Designing and Implementing User-Defined Functions

·       Format Phone numbers

·       Modify an Existing Function

·       After completing this Lecture, you will be able to:

·       Describe different types of functions.

·       Design and implement scalar functions.

·       Design and implement table-valued functions (TVFs).

·       Describe considerations for implementing functions.

·       Describe alternatives to functions.

·       Data Manipulation Language (DML) triggers are powerful tools that you can use to enforce domain, entity, referential data integrity and business logic. The enforcement of integrity helps you to build reliable applications. In this Lecture, you will learn what DML triggers are, how they enforce data integrity, the different types of trigger that are available to you, and how to define them in your database.

·       Lessons

·       Designing DML Triggers

·       Implementing DML Triggers

·       Advanced Trigger Concepts

·       Lab : Responding to Data Manipulation by Using Triggers

·       Create and Test the Audit Trigger

·       Improve the Audit Trigger

·       After completing this Lecture, you will be able to:

·       Design DML triggers

·       Implement DML triggers

·       Explain advanced DML trigger concepts, such as nesting and recursion.      

·       Microsoft SQL Server 2014 data management software introduced in-memory online transaction processing (OLTP) functionality features to improve the performance of OLTP workloads. SQL Server adds several enhancements, such as the ability to alter a memory-optimized table without recreating it. Memory-optimized tables are primarily stored in memory, which provides the improved performance by reducing hard disk access. Natively compiled stored procedures further improve performance over traditional interpreted Transact-SQL.

·       Lessons

·       Memory-Optimized Tables

·       Natively Compiled Stored Procedures

·       Lab : Using In-Memory Database Capabilities

·       Using Memory-Optimized Tables

·       Using Natively Compiled Stored procedures

·       After completing this Lecture, you will be able to:

·       Use memory-optimized tables to improve performance for latch-bound workloads.

·       Use natively compiled stored procedures.

·     As a SQL Server professional, you are likely to be asked to create databases that meet business needs. Most requirements can be met using Transact-SQL. However, occasionally you may need additional capabilities that can only be met by using common language runtime (CLR) code. As functionality is added to SQL Server with each new release, the necessity to use managed code decreases. However, there are times when you might need to create aggregates, stored procedures, triggers, user-defined functions, or user-defined types. You can use any .NET Framework language to develop these objects. In this Lecture, you will learn how to use CLR managed code to create user-defined database objects for SQL Server.

·       Lessons

·       Introduction to CLR Integration in SQL Server

·       Implementing and Publishing CLR Assemblies

·       Lab : Implementing Managed Code in SQL Server

·       Assessing Proposed CLR Code

·       Creating a Scalar-Valued CLR Function

·       Creating a Table Valued CLR Function

·       After completing this Lecture, you will be able to:

·       Explain the importance of CLR integration in SQL Server.

·       Implement and publish CLR assemblies using SQL Server Data Tools (SSDT).

·     XML provides rules for encoding documents in a machine-readable form. It has become a widely adopted standard for representing data structures, rather than sending unstructured documents. Servers that are running Microsoft SQL Server data management software often need to use XML to interchange data with other systems; many SQL Server tools provide an XML-based interface. SQL Server offers extensive handling of XML, both for storage and querying. This Lecture introduces XML, shows how to store XML data within SQL Server, and shows how to query the XML data. The ability to query XML data directly avoids the need to extract data into a relational format before executing Structured Query Language (SQL) queries. To effectively process XML, you need to be able to query XML data in several ways: returning existing relational data as XML, and querying data that is already XML.

·       Lessons

·       Introduction to XML and XML Schemas

·       Storing XML Data and Schemas in SQL Server

·       Implementing the XML Data Type

·       Using the Transact-SQL FOR XML Statement

·       Getting Started with XQuery

·       Shredding XML

·       Lab : Storing and Querying XML Data in SQL Server

·       Determining when to use XML

·       Testing XML Data Storage in Variables

·       Using XML Schemas

·       Using FOR XML Queries

·       Creating a Stored Procedure to Return XML

·       After completing this Lecture, you will be able to:

·       Describe XML and XML schemas.

·       Store XML data and associated XML schemas in SQL Server.

·       Implement XML indexes within SQL Server.

·       Use the Transact-SQL FOR XML statement.

·       Work with basic XQuery queries.

·       This Lecture describes spatial data and how this data can be implemented within SQL Server.

·       Lessons

·       Introduction to Spatial Data

·       Working with SQL Server Spatial Data Types

·       Using Spatial Data in Applications

·       Lab : Working with SQL Server Spatial Data

·       Become Familiar with the Geometry Data Type

·       Add Spatial Data to an Existing Table

·       Find Nearby Locations

·       After completing this Lecture, you will be able to:

·       Describe how spatial data can be stored in SQL Server

·       Use basic methods of the GEOMETRY and GEOGRAPHY data types

·       Query databases containing spatial data

·       Traditionally, databases have been used to store information in the form of simple values—such as integers, dates, and strings—that contrast with more complex data formats, such as documents, spreadsheets, image files, and video files. As the systems that databases support have become more complex, administrators have found it necessary to integrate this more complex file data with the structured data in database tables. For example, in a product database, it can be helpful to associate a product record with the service manual or instructional videos for that product. SQL Server provides several ways to integrate these files—that are often known as Binary Large Objects (BLOBs)—and enable their content to be indexed and included in search results. In this Lecture, you will learn how to design and optimize a database that includes BLOBs.

·       Lessons

·       Considerations for BLOB Data

·       Working with FILESTREAM

·       Using Full-Text Search

·       Lab : Storing and Querying BLOBs and Text Documents in SQL Server

·       Enabling and Using FILESTREAM Columns

·       Enabling and Using File Tables

·       Using a Full-Text Index

·       After completing this Lecture, you will be able to:

·       Describe the considerations for designing databases that incorporate BLOB data.

·       Describe the benefits and design considerations for using FILESTREAM to store BLOB data on a Windows file system.

·       Describe the benefits of using full-text indexing and Semantic Search, and explain how to use these features to search SQL Server data, including unstructured data

·      This Lecture explains how to name, declare, assign values to, and use variables. It also describes how to store data in an array. Concurrency control is a critical feature of multiuser database systems; it allows data to remain consistent when many users are modifying data at the same time. This Lecture covers the implementation of concurrency in Microsoft SQL Server. You will learn about how SQL Server implements concurrency controls, and the different ways you can configure and work with concurrency settings.

·       Lessons

·       Concurrency and Transactions

·       Locking Internals

·       Lab : SQL Server Concurrency

·       Implement Snapshot Isolation

·       Implement Partition Level Locking

·       After completing this Lecture, you will be able to:

·       Describe concurrency and transactions in SQL Server.

·       Describe SQL Server locking.

·      This Lecture explains how to name, declare, assign values to, and use variables. It also describes how to store data in an array. This Lecture looks at how to measure and monitor the performance of your SQL Server databases. The first two Lessons look at SQL Server Extended Events, a flexible, lightweight event-handling system built into the Microsoft SQL Server Database Engine. These Lessons focus on the architectural concepts, troubleshooting strategies and usage scenarios.

·       Lessons

·       Extended Events

·       Working with extended Events

·       Live Query Statistics

·       Optimize Database File Configuration

·       Metrics

·       Lab : Monitoring, Tracing, and Baselining

·       Collecting and Analyzing Data Using Extended Events

·       Implementing Baseline Methodology

·       After completing this Lecture, you will be able to:

·       Understand Extended Events and how to use them.

·       Work with Extended Events.

·       Understand Live Query Statistics.

·       Optimize the file configuration of your databases.

·       Use DMVs and Performance Monitor to create baselines and gather performance metrics.

Tableau Desktop is a business intelligence and data visualization tool that can be used by anyone. It specializes in transforming boring tabulated data into eye-candy graphs and representations. With tableau desktop, you can enjoy real-time data analytics by directly connecting to data from your data warehouse.

·       What is data visualization?

·       Comparison and benefits against reading raw numbers

·       Real use cases from various business domains

·       Some quick and powerful examples using Tableau without going into the technical details of Tableau

·       Installing Tableau

·       Tableau interface

·       Connecting to DataSource

·       Tableau data types

·       Data preparation

·       Practical Exercise

·       Installation of Tableau Desktop

·       Architecture of Tableau

·       Tableau Layout

·       Tableau Toolbars

·       Tableau Data Pane

·       Tableau Analytics Pane

·       How to start with Tableau

·       The ways to share and export the work done in Tableau

·       Practical Exercise

·       Connection to Excel

·       Cubes and PDFs

·       Management of metadata and extracts

·       Data preparation

·       Joins and Union

·       Dealing with NULL values

·       Cross-database joining

·       Data extraction

·       Data blending

·       Refresh extraction

·       Incremental extraction

·       How to build extract

·       Practical Exercise

·       Mark

·       Highlight

·       Sort

·       Group, and use sets

·       Creating and editing sets

·       IN/OUT

·       Sets in hierarchies

·       Constant sets

·       Computed sets

·       Bins

·       Filters

·       Filtering continuous dates

·       Dimensions, and measures

·       Interactive filters

·       Marks card

·       Hierarchies

·       How to create folders in Tableau

·       Sorting in Tableau

·       Types of sorting

·       Filtering in Tableau

·       Types of filters

·       Filtering the order of operations

·       Practical Exercise

·       Using Formatting Pane to work with menu, fonts, alignments, settings, and copy-paste

·       Formatting data using labels and tooltips

·       Edit axes and annotations

·       K-means cluster analysis

·       Trend and reference lines

·       Visual analytics in Tableau

·       Forecasting

·       Confidence interval

·       Reference lines

·       Bands

·       Practical Exercise

·       Working on coordinate points

·       Plotting longitude and latitude

·       Editing unrecognized locations

·       Customizing geocoding, polygon maps

·       WMS: web mapping services

·       Working on the background image, including add image

·       Plotting points on images and generating coordinates from them

·       Map visualization

·       Custom territories

·       Map box

·       WMS map

·       How to create map projects in Tableau

·       Creating dual axes maps and editing locations

·       Calculation syntax and functions in Tableau

·       Various types of calculations, including Table, String, Date, Aggregate, Logic, and Number

·       LOD expressions, including concept and syntax

·       Aggregation and replication with LOD expressions

·       Nested LOD expressions

·       Fixed level

·       Lower level

·       Higher level

·       Quick table calculations

·       The creation of calculated fields

·       Predefined calculations

·       How to validate

·       Creating parameters

·       Parameters in calculations

·       Using parameters with filters

·       Column selection parameters

·       Chart selection parameters

·       How to use parameters in the filter session

·       How to use parameters in calculated fields

·       How to use parameters in the reference line

·       Practical Exercise

·       Dual axes graphs

·       Histograms

·       Single and dual axes

·       Box plot

·       Motion Charts

·       Pareto Charts

·       Funnel Charts

·       Pie Charts

·       Bar Charts

·       Line Charts

·       Bubble Charts

·       Bullet Charts

·       Scatter Charts

·       Waterfall charts

·       Tree Maps

·       Heat Maps

·       Market basket analysis (MBA)

·       Using Show me

·       Text table and highlighted table

·       Building and formatting a dashboard using size, objects, views, filters, and legends

·       Best practices for making creative as well as interactive dashboards using the actions

·       Creating stories, including the intro of story points

·       Creating as well as updating the story points

·       Adding catchy visuals in stories

·       Adding annotations with descriptions; dashboards and stories

·       What is dashboard?

·       Highlight actions, URL actions, and filter actions

·       Selecting and clearing values

·       Best practices to create dashboards

·       Dashboard examples; using Tableau workspace and Tableau interface

·       Learning about Tableau joins

·       Types of joins

·       Tableau field types

·       Saving as well as publishing data source

·       Live vs extract connection

·       Various file types

·       Practical Exercise

·       Introduction to Tableau Prep

·       How Tableau Prep helps quickly combine join, shape, and clean data for analysis

·       Creation of smart examples with Tableau Prep

·       Getting deeper insights into the data with great visual experience

·       Making data preparation simpler and accessible

·       Integrating Tableau Prep with Tableau analytical workflow

·       Understanding the seamless process from data preparation to analysis with Tableau Prep

·       Practical Exercise

Power BI is a suite of apparatuses for Business Analytics that enables corporate clients to dissect information and get bits of knowledge that can help in settling on right business choices. This Power BI preparing covers most recent devices to screen business development and quickly find solutions on any gadget through rich announcing components and dashboards.

·    Business intelligence (BI) is a term that has become increasingly common over recent years.  Reporting and analysis is certainly not a new concept to business, but the difference between how  data analysis is done today, compared with five or 10 years ago, is immense. Nowadays,  organizations need BI to see not only what was done in the past, but also more of what is to come.

·       Lessons

·       Introduction to Business Intelligence

·       Introduction to Data Analysis

·       Introduction to Data Visualization

·       Overview of Self-Service BI

·       Considerations for Self-Service BI

·       Microsoft Tools for Self-Service BI

·       Lab: Exploring an Enterprise BI Solution

·       Viewing Reports

·       Creating a Power BI Report

·       Creating a Power BI Dashboard

·       After completing this module, students will be able to:

·       Describe the trends in BI.

·       Describe the process of data analysis in Power BI.

·       Use the key visualizations in Power BI.

·       Describe the rationale for self-service BI.

·       Describe considerations for self-service BI.

·       Understand how you can use Microsoft products to implement a BI solution.

·   This module introduces Power BI, and explores the features that enable the rapid creation and publication of sophisticated data visualizations. Using Power BI eliminates complications and barriers with a simple integrated user interface, and has the ability to publish rapidly to either a cloud-based or an on-premise portal to share reports easily.

·       Lessons

·       Power BI

·       The Power BI Service

·       The key features of Power BI workflow

·       Desktop application

·       BI service

·       File data sources

·       Sourcing data from web (OData, Azure)

·       Building dashboard

·       Data visualization

·       Publishing to cloud

·       DAX data computation

·       Row context

·       Filter context

·       Analytics Pane

·       Creating columns and measures

·       Data drill down and drill up

·       Creating tables

·       Binned tables

·       Data modeling and relationships

·       The Power BI components like Power View, Map, Query, Pivot

·       Understanding advanced visualization

·       Lab: Creating a Power BI Dashboard

·       Connecting to Power BI Data

·       Create a Power BI Dashboard

·       After completing this module, students will be able to:

·       Develop reports using the Power BI Desktop app.

·       Use report items to create dashboards on the Power BI portal.

·       Understand the components of the Power BI service, including licensing and tenant management.

·       Power BI offers a straightforward approach to report creation, and the ability to create and share dashboards without dependency on a report developer, or the need for Microsoft SharePoint. Power BI easily cooperates with Excel, and many other data sources. It’s this ability to create reports rapidly, by using data from a combination of sources, that really puts the power into Power BI.

·       Lessons

·       Using Excel as a Data Source for Power BI

·       The Power BI Data Model

·       Using Databases as a Data Source for Power BI

·       The Power BI Service

·       Learning about Power Query for self-service ETL functionalities

·       Data mashup

·       Working with Excel data

·       Learning about Power BI Personal Gateway

·       Extracting data from files, folders and databases

·       Working with Azure SQL database and database source

·       Connecting to Analysis Services

·       SaaS functionalities of Power BI

·       Lab: Importing Data into Power BI

·       Importing Excel files into Power BI

·       Viewing Reports from Excel Files

·       Connect to a database

·       Import data from an excel file

·       Connect to SQL Server

·       Analysis Service

·       Connect to Power Query

·       Connect to SQL Azure

·       Connect to Hadoop

·       After completing this module, students will be able to:

·       Describe the data model and know how to optimize your data within the model.

·       Connect to Excel files and import data.

·       Use on-premises & cloud SQL Server databases as data sources, with the R script data connector.

·       Take advantage of the features of the Power BI service.

·       Use Q&A to ask questions in natural query language and create apps.

·       Power BI Desktop offers a self-service solution for creating visual, interactive reports and dashboards. Users can connect to a wide variety of data sources, combining data from on-premises databases, Software as a Solution (SaaS) providers, cloud-based services, and local files such as Microsoft Excel, into one report.

·       Lessons

·       Power BI Desktop Queries

·       Introduction to Query Editor

·       Installing Power BI

·       The various requirements and configuration settings

·       Data transformation – column, row, text, data type, adding & filling columns and number column, column formatting, transpose table, appending, splitting, formatting data, Pivot and UnPivot, Merge Join, relational operators, date, time calculations, working with M functions, lists, records, tables, data types, and generators

·       Shaping Data

·       Combining Data

·       Filters & Slicers

·       Index and Conditional Columns

·       Summary Tables

·       Writing custom functions and error handling

·       M advanced data transformations

·       Lab: Shaping and Combining Data

·       Shape Power BI Data

·       Combine Power BI Data

·       After completing this module, students will be able to:

·       Perform a range of query editing tasks in Power BI.

·       Shape data, using formatting and transformations.

·       Combine data together from tables in your dataset.

·      This module goes behind the scenes of the visualizations, and explores the techniques and features on offer to shape and enhance your data. With automatic relationship creation, a vast library of DAX functions, and the ability to add calculated columns, tables, and measures quickly, you will see how Power BI creates attractive reports, while helping you find hidden insights into data.

·       Lessons

·       Relationships

·       DAX Queries

·       Calculations and Measures

·       Introduction to Power Pivot

·       Learning about the xVelocity engine

·       Advantages of Power Pivot

·       Various versions and relationships

·       Strongly typed datasets

·       Data Analysis Expressions

·       Measures, Calculated Members, Row, Filter & Evaluation Context, Context Interactions, Context over Relations, Schema Relations

·       Learning about Table, Information, Logical, Text, Iterator, Table, and Time Intelligence Functions

·       Cumulative Charts, Calculated Tables, ranking and rank over groups

·       Power Pivot advanced functionalities

·       Date and time functions

·       DAX advanced features

·       Embedding Power Pivot in Power BI Desktop

·       Lab: Modelling Data

·       Create Relationships

·       Calculations

·       Create a Power Pivot Apply filters

·       Use advanced functionalities like date and time functions

·       Embed Power Pivot in Power BI Desktop

·       Create DAX queries for calculate column, tables and measures

·       After completing this module, students will be able to:

·       Describe relationships between data tables.

·       Understand the DAX syntax and use DAX functions to enhance your dataset.

·       Create calculated columns, calculated tables, and measures.

·       This approach enables business users to access corporate data, and create and share reports and key performance indicators (KPIs) without dependency on a dedicated report developer. These include the main industry-standard databases, Microsoft cloud-based services—Microsoft Azure SQL Database, Azure Data Lake, and Azure Machine Learning—alongside Microsoft Excel and other files, and software as a service (SaaS) providers such as Microsoft Bing, Facebook, and MailChimp.

·       Lessons

·       Creating Power BI Reports

·       Managing a Power BI Solution

·       Deep dive into Power BI data visualization

·       Understanding Power View and Power Map

·       Power BI Desktop visualization

·       Formatting and customizing visuals

·       Visualization interaction

·       SandDance visualization

·       Deploying Power View on SharePoint and Excel

·       Top down and bottom up analytics

·       Comparing volume and value-based analytics

·       Working with Power View to create Reports, Charts, Scorecards, and other visually rich formats

·       Categorizing, filtering and sorting data using Power View

·       Hierarchies

·       Mastering the best practices

·       Custom Visualization

·       Authenticate a Power BI web application

·       Embedding dashboards in applications

·       Lab: Creating a Power BI Report

·       Connecting to Power BI Data

·       Building Power BI Reports

·       Creating a Power BI Dashboard

·       Create a Power View and a Power Map

·       Format and customize visuals

·       Deploy Power View on SharePoint and Excel

·       Implement top-down and bottom-up analytics

·       Create Power View reports, Charts, Scorecards

·       Add a custom visual to report

·       Authenticate a Power BI web application

·       Embed dashboards in applications

·       Categorize, filter and sort data using Power View

·       Create hierarchies

·       Use date hierarchies

·       Use business hierarchies

·       Resolve hierarchy issues

·       After completing this module, students will be able to:

·       Use Power BI Desktop to create interactive data visualizations.

·       Manage a Power BI solution.

·   Power BI service supports live direct connections to Azure SQL Database, Azure SQL Data Warehouse, big data sources such as Spark on Azure HDInsight, and SQL Server Analysis Services. DirectQuery means that whenever you slice data or add another field to a visualization, a new query is issued directly to the data source. Power BI works with SQL Server Analysis Services models that are running in multidimensional mode, so that you can use OLAP cubes and models in reports and dashboards.

·       Lessons

·       Cloud Data

·       Connecting to Analysis Services

·       Lab: Direct Connectivity

·       Direct Connections to Power BI

·       After completing this module, students will be able to:

·       Use Power BI direct connectivity to access data in Azure SQL Database and Azure SQL Data Warehouse

·       Use Power BI direct connectivity to access data in big data sources, such as Hadoop.

·       Use Power BI with SQL Server Analysis Services data.

·       Use Analysis Services models running in multidimensional mode.

·       The Power BI API is a REST-based API that developers use to access programmatically datasets, tables, and rows in Power BI. Using this API, you push data from an application into Power BI and integrate Power BI visualizations into an application. You can also add custom visuals to your applications and to Power BI dashboards and reports. In this module, you will learn how to use the Power BI API to embed content in your applications and how to use custom visuals in your reports.

·       Lessons

·       The Power BI API

·       Custom Visuals

·       Lab: Using Marketplace Visualizations

·       Using a Custom Visualization

·       After completing this module, students will be able to:

·       Describe the Power BI Developer API.

·       List the steps for creating custom visualizations.

·       Import custom visuals into Power BI for use in Power BI reports.

·    Power BI mobile apps enable you to access and use Power BI information on a mobile device, including iOS (iPad, iPhone, iPod Touch, Apple Watch), Android phone or tablet, and Windows 10 devices. Power BI reports and dashboards are designed to work on a mobile device without modification. However, you can also create specific optimized reports and report layouts for display on mobile devices. The Power BI mobile apps support the sharing and annotation of dashboards, and you can use Power BI data on mobile devices even when you are not connected to a network. Power BI alerts and notifications also work across the Power BI service, including on mobile devices.

·       Lessons

·       Power BI Mobile Apps

·       Using the Power BI Mobile App

·       After completing this module, students will be able to:

·       Create dashboards and reports for mobile devices.

·       Use the Power BI Mobile app.

Microsoft Business Intelligence i.e., MSBI enables you to master MSBI tools like SSIS, SSRS, and SSAS using SQL Server. As part of this, you will learn data integration and the creation of reports, dashboards, and cubes for faster report generation. As a part of online classroom training, you will receive an additional course from Microsoft, Analyzing Data with SQL Server Reporting Services. This training injects you the required knowledge on ETL Solutions, SSIS packages, OLTP, OLAP, how to configure SSRS, etc. With the MSBI tools, companies can make the right decisions and can implement their plans immediately.

·       Lessons

·       Overview of Data Warehousing

·       Considerations for a Data Warehouse Solution

·       Lab

·       Exploring a Data Warehousing Solution

·       Lessons

·       Considerations for Data Warehouse Infrastructure

·       Planning Data Warehouse Hardware

·       Lab

·       Planning Data Warehouse Infrastructure

·       Lessons

·       Data Warehouse Design Overview

·       Designing Dimension Tables

·       Designing Fact Tables

·       Physical Design for a Data Warehouse

·       Lab

·       Implementing a Data Warehouse

·       Lessons

·       Introduction to Column store Indexes

·       Creating Column store Indexes

·       Working with Column store Indexes

·       Lab

·       Using Column store Indexes

·       Lessons

·       Advantages of Azure SQL Data Warehouse

·       Implementing an Azure SQL Data Warehouse Database

·       Developing an Azure SQL Data Warehouse

·       Migrating to an Azure SQL Data Warehouse

·       Copying Data with the Azure Data Factory

·       Lab

·       Implement an Azure SQL Data Warehouse

·       Lessons

·       Introduction to ETL with SSIS

·       Exploring Source Data

·       Implementing Data Flow

·       Lab

·       Implementing Data Flow in an SSIS Package

·       Lessons

·       Introduction to ETL with SSIS

·       Exploring Source Data

·       Implementing Data Flow

·       Lab

·       Implementing Data Flow in an SSIS Package

·       Lessons

·       Debugging an SSIS Package

·       Logging SSIS Package Events

·       Handling Errors in an SSIS Package

·       Lab

·       Debugging and Troubleshooting an SSIS Package

·       Lessons

·       Introduction to Incremental ETL

·       Extracting Modified Data

·       Loading Modified Data

·       Temporal Tables

·       Lab

·       Extracting Modified Data

·       Loading a Data Warehouse

·       Lessons

·       Introduction to Data Quality

·       Using Data Quality Services to Cleanse Data

·       Using Data Quality Services to Match Data

·       Lab

·       Cleansing Data

·       Duplicating Data

·       Lessons

·       Introduction to Master Data Services

·       Implementing a Master Data Services Model

·       Hierarchies and Collections

·       Creating a Master Data Hub

·       Lab

·       Implementing Master Data Services Model

·       Lessons

·       Using Scripts in SSIS

·       Using Custom Components in SSIS

·       Lab

·       Using Custom Scripts

·       Lessons

·       Overview of SSIS Development 13-2

·       Deploying SSIS Projects 13-5

·       Planning SSIS Package Execution 13-14

·       Lab

·       Deploying and Configuring SSIS Packages

·       Lessons

·       Introduction to Business Intelligence

·       Introduction to Data Analysis

·       Introduction to Reporting

·       Analysing Data with Azure SQL Data Warehouse

·       Lab

·       Using a Data Warehouse

·       In this Lecture 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 Lecture, you will be able to:

·       Describe key concepts in business intelligence

·       Describe the Microsoft BI platform

·       Describe key concepts in reporting services

·       Describe various Report Services data sources and how these are configured.

·       Lessons

·       Data sources

·       Connection strings

·       Datasets

·       Filters and parameters

·       Lab : Configuring a data connection

·       After completing this Lecture, you will be able to:

·       Describe data connections and connection strings

·       Describe filters and parameters

·       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 Lecture, you will be able to:

·       Create a report using the report wizard

·       Show data graphically

·       This Lecture 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 Lecture, you will be able to:

·       Implement filters and parameters

·       Implement sorting and grouping

·       Publish a report

·       This Lecture describes how to create SQL Server mobile reports.

·       Lessons

·       Overview of SQL Server mobile reports

·       Preparing data for mobile reports

·       SQL Server Mobile report publisher

·       Lab : Working with mobile reports

·       After completing this Lecture, you will be able to:

·       Describe SQL Server mobile reports

·       Prepare data for mobile reports

·       Publish mobile reports

·       This Lecture 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 Lecture, you will be able to:

·       Describe the concept of business intelligence

·       Describe the Microsoft business intelligence platform

·       This Lecture describes the steps required to create a multidimensional database with analysis services.

·       Lessons

·       Introduction to multidimensional analysis

·       Course details

·       Creating data sources and data source views

·       Creating a cube

·       Overview of cube security

·       Lab : Creating a multidimensional database

·       After completing this Lecture, you will be able to:

·       Use multidimensional analysis

·       Create data sources and data source views

·       Create a cube

·       Describe cube security

·       This Lecture 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 Lecture, you will be able to:

·       Configure dimensions

·       Define attribute hierarchies.

·       Sort and group attributes

·       This Lecture 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 Lecture, you will be able to:

·       Work with measures

·       Work with measure groups

·       This Lecture 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 Lecture, you will be able to:

·       Describe the fundamentals of MDX

·       Add calculations to a cube

·       Query a cube using MDX

·       This Lecture describes how to customize a cube.

·       Lessons