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Azure SQL Data Warehouse Architecture and SQL

Course content updated by LearnQuest
Price
3,060 USD
4 Days
MSSQ-205
Classroom Training, Online Training
Microsoft
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Course Description

Overview

This Azure SQL Data Warehouse Architecture and SQL course is designed to provide students with a deeper knowledge and understanding of the architecture of Microsoft’s Azure SQL Data Warehouse. Students will also attain a deep understanding of the Azure SQL Data Warehouse T-SQL and how to write it. This course begins with a focus on the Azure SQL Data Warehouse, and then dives into T-SQL at a basic level and continues to an advanced level, providing students with many examples along the way. In addition, students will gain practical experience with hands-on exercises.
 

Objectives

Upon completion of the Azure SQL Data Warehouse Architecture and SQL course, students will be able to:
  • Understand the Microsoft Azure SQL Data Warehouse
  • Summarize the Microsoft Azure SQL Data Warehouse Table Structure
  • Utilize Hashing and Data Distribution
  • Apply CREATE Statistics
  • Understand Basic SQL Functions
  • Use the WHERE Clause
  • Demonstrate Distinct Vs. Group By
  • Utilize the Aggregation Function
  • Apply Join, Date, Format, and OLAP Functions
  • Understand Temporary Tables
  • Use Sub-query Functions
  • Apply Substrings and Positioning Functions
  • Interrogate Data
  • Use View Functions
  • Set Operators Functions
  • Create Tables
  • Summarize Data Manipulation Language (DML)

Audience

  • IT Professionals

Prerequisites

    • None

Topics

  • Introduction to the Azure SQL Data Warehouse
    • Introduction to the Family of SQL Server Products
    • Introduction to the Family Continued
    • Microsoft Azure SQL Data Warehouse
    • Symmetric Multi-Processing (SMP)
    • What is Parallel Processing?
    • The Basics of a Single Computer
    • Data in Memory is Fast as Lightning
    • Parallel Processing of Data
    • A Table has Columns and Rows
    • The Azure SQL Data Warehouse has Linear Scalability
    • The Architecture of the Azure SQL Data Warehouse
    • Nexus is now Available on the Microsoft Azure Cloud
    • The MPP Engine is the Optimizer
    • The Azure SQL Data Warehouse System
    • The Azure SQL Data Warehouse System is Scalable
    • The Control Node
    • The Data Rack
    • The Landing Zone
    • The Backup Node
    • Software as a Service (SaaS) and the Elastic Database
    • Azure Data Lake
    • Azure Disaster Recovery
    • Security and Compliance
    • How to Get an EXPLAIN Plan
  • The Azure SQL Data Warehouse Table Structures
    • The 5 Concepts of Azure SQL Data Warehouse Tables
    • Tables are Either Distributed by Hash or Replicated (1 of 5)
    • Table Rows are Either Sorted or Unsorted (2 of 5)
    • Tables are Stored in Either Row or Columnar Format (3 of 5)
    • Tables can be Partitioned (4 of 5)
    • There are Permanent, Temporary and External Tables (5 of 5)
    • Creating a Table With a Distribution Key
    • Creating a Table that is Replicated
    • Distributed by Hash vs. Replication
    • The Concept is All About the Joins
    • Creation of a Hash Distributed Table with a Clustered Index
    • A Clustered Index Sorts the Data Stored on Disk
    • Each Node Has 8 Distributions
    • How Hashed Tables are Stored Among a Single Node
    • Hashed Tables Will Be Distributed Among All Distributions
    • Creation of a Replicated Table
    • How Replicated Tables are Stored Among a Single Node
    • Replicated Table will be Duplicated among Each Node
    • Distributed by Replication
    • How Hashed and Replicated Tables Work Together
    • Tables are Stored as Row-based or Column-based
    • Creation of a Columnar Table that is Hashed
    • How Hashed Columnar Tables are Stored on a Single Node
    • How Hashed Columnar Tables are Stored on All Distributions
    • Comparing Normal Table Vs. Columnar Tables
    • Columnar can move just One Segment to Memory
    • Segments on Distributions are Aligned to Rebuild a Row
    • Why Columnar?
    • Columnar Tables Store Each Column in Separate Pages
    • Visualize the Data – Rows vs. Columns
    • Creation of a Columnar Table that is Replicated
    • Creating a Partitioned Table Per Month
    • A Visual of One Year of Data with Range Per Month
    • Another Create Example of a Partitioned Table
    • Creating a Partitioned Table Per Month That is a Columnstore
    • Visual of Row Partitioning and Columnar Storage
    • CREATE TABLE AS (CTAS) Example
    • Creating a Temporary Table
    • Facts About Tables
  • Hashing and Data Distribution
    • Distribution Keys Hashed on Unique Values Spread Evenly
    • Distribution Keys With Non-Unique Values Spread Unevenly
    • Best Practices for Choosing a Distribution Key
    • The Hash Map Determines which Distribution owns the Row
    • The Hash Map Determines which Node will Own the Row
    • A Review of the Hashing Process
    • Non-Unique Distribution Keys have Skewed Data
  • The Technical Details
    • Every Node has the Exact Same Tables
    • Hashed Tables are spread across All Distributions
    • The Table Header and the Data Rows are Stored Separately
    • A Distribution Stores the Rows of a Table inside a Data Block
    • To Read a Data Block a Node Moves the Block into Memory
    • A Full Table Scan Means All Nodes Must Read All Rows
    • Rows are Organized inside a Page
    • Moving Data Blocks is Like Checking In Luggage
    • As Row-Based Tables Get Bigger, the Page Splits
    • Data Pages are Processed One at a Time Per Unit
    • Creating a Table that is a Heap
    • Heap Page
    • Extents
    • Creating a Table that has a Clustered Index
    • Clustered Index Page
    • The Row Offset Array is the Guidance System for Every Row
    • The Row Offset Array Provides Two Search Options
    • The Row Offset Array Helps With Inserts
    • B-Trees
    • The Building of a B-Tree for a Clustered Index
    • When Do I Create a Clustered Index?
    • When Do I Create a Non Clustered Index?
    • B-Tree for Non Clustered Index on a Clustered Table
    • Adding a Non Clustered Index To A Heap
    • B-Tree for Non Clustered Index on a Heap Table
    • Max Levels on the Azure SQL Data Warehouse
    • Azure SQL Data Warehouse Data Types
    • Character Data Types for SQL Server
    • Numeric Data Types for SQL Server
    • Date and Time Data Types for SQL Server
    • Additional Data Types for SQL Server
  • CREATE Statistics
    • CREATE Statistics Syntax
    • CREATE Statistics on a Percentage of a Table
    • CREATE Statistics on a Sample by Using the System Default
    • CREATE Statistics on a Multi-Column Join Key
    • What to Column(s) to CREATE Statistics On
    • CREATE Statistics Using a WHERE Clause
    • Updating All Statistics on a Table
    • Updating Only Certain Statistics on a Table
    • Dropping Statistics on Certain Statistics on a Table
    • Showing the Statistics
    • DBCC SHOW_STATISTICS
    • DBCC SHOW_STATISTICS WITH HISTOGRAM
  • The Basics of SQL
    • Introduction
    • Naming of Objects
    • Setting Your Default Database
    • SELECT * (All Columns) in a Table
    • Fully Qualifying a Database, Schema and Table
    • SELECT Specific Columns in a Table
    • Commas in the Front or Back?
    • Place your Commas in front for better Debugging Capabilities
    • Sort the Data with the ORDER BY Keyword
    • ORDER BY Defaults to Ascending
    • Use the Name or the Number in your ORDER BY Statement
    • Two Examples of ORDER BY using Different Techniques
    • Changing the ORDER BY to Descending Order
    • NULL Values sort First in Ascending Mode (Default)
    • NULL Values sort Last in Descending Mode (DESC)
    • Major Sort vs. Minor Sorts
    • Multiple Sort Keys using Names vs. Numbers
    • Sorts are Alphabetical, NOT Logical
    • Using A CASE Statement to Sort Logically
    • An Order By That Uses an Expression
    • How to ALIAS a Column Name
    • Aliasing a Column Name with Spaces or Reserved Words
    • A Missing Comma can by Mistake become an Alias
    • Comments using Double Dashes are Single Line Comments
    • Comments for Multi-Lines
    • Comments for Multi-Lines as Double Dashes Per Line
    • A Great Technique for Comments to Look for SQL Errors
    • sp_help at the Database Level
    • sp_help at the Object Level
    • Getting System Information
    • Getting Additional System Information
  • The Where Clause
    • The WHERE Clause limits Returning Rows
    • Double Quoted Aliases are for Reserved Words and Spaces
    • Using A Column ALIAS in a WHERE Clause
    • Using A Column ALIAS in a ORDER BY Clause
    • In What Order Does SQL Server Process A Query?
    • Character Data needs Single Quotes in the WHERE Clause
    • Character Data needs Single Quotes, but Numbers Don’t
    • Declaring a Variable
    • Comparisons against a Null Value
    • NULL means UNKNOWN DATA so Equal (=) won’t Work
    • Use IS NULL or IS NOT NULL when dealing with NULLs
    • NULL is UNKNOWN DATA so NOT Equal won’t Work
    • Use IS NULL or IS NOT NULL when dealing with NULLs
    • Using Greater Than or Equal To (>=)
    • AND in the WHERE Clause
    • Troubleshooting AND
    • OR in the WHERE Clause
    • Troubleshooting Or
    • Troubleshooting Character Data
    • Using Different Columns in an AND Statement
    • Quiz – How many rows will return?
    • LIKE command Underscore is Wildcard for one Character
    • LIKE command using a Range of Values
    • LIKE command Using a NOT Range of Values
    • LIKE Command Works Differently on Char Vs Varchar
    • Troubleshooting LIKE Command on Character Data
    • Introducing the RTRIM Command
    • Quiz – What Data is Left Justified and What is Right?
    • Numbers are Right Justified and Character Data is Left
    • An Example of Data with Left and Right Justification
    • A Visual of CHARACTER Data vs. VARCHAR Data
    • RTRIM command Removes Trailing spaces on CHAR Data
    • Using Like with an AND Clause to Find Multiple Letters
    • Using Like with an OR Clause to Find Either Letters
    • Declaring a Variable and Using it with the LIKE Command
    • Escape Character in the LIKE Command changes Wildcards
    • Escape Characters Turn off Wildcards in the LIKE Command
    • Quiz – Turn off that Wildcard
  • Distinct, Group By and TOP
    • The Distinct Command
    • Distinct vs. GROUP BY
    • Quiz – How many rows come back from the Distinct?
    • TOP Command
    • TOP Command is brilliant when ORDER BY is used!
    • TOP Command with Ties
    • TOP Command Using a Variable
  • Aggregation
    • Quiz – You calculate the Answer Set in your own Mind
    • The 3 Rules of Aggregation
    • There are Five Aggregates
    • Quiz – How many rows come back?
    • Troubleshooting Aggregates
    • GROUP BY when Aggregates and Normal Columns Mix
    • GROUP BY delivers one row per Group
    • Count_Big
    • Limiting Rows and Improving Performance with WHERE
    • WHERE Clause in Aggregation limits unneeded Calculations
    • Keyword HAVING tests Aggregates after they are Totaled
    • Group By Grouping Sets
    • Group By Rollup
    • Answer Set for Group By Rollup Query
    • Creating a Cube
    • Answer Set for Cube Query
    • An Easy Example of Creating a Cube
    • Quiz - GROUP BY GROUPING SETS Challenge
    • Getting the Average Values Per Column
    • Average Values per Column for all Columns in a Table
  • Join Functions
    • The Azure SQL Data Warehouse Join Quiz
    • Redistribution
    • Big Table Small Table Join Strategy
    • Duplication of the Smaller Table across All-Distributions
    • If the Join Condition is the Distribution Key no Movement
    • Matching Rows That Are On The Same Node Naturally
    • What if the Join Condition Columns are Not Primary Indexes
    • Strategy 1 of 4 – The Merge Join
    • Quiz – Redistribute the Employees by their Dept_No
    • Quiz –Dept_No landed on Distribution with Matches
    • Quiz – Redistribute the Orders to the Proper Distribution
    • Strategy 2 of 4 – The Hash Join
    • Strategy 4 of 4 – The Product Join
    • A Two-Table Join Using Traditional Syntax
    • A two-table join using Non-ANSI Syntax with Table Alias
    • You Can Fully Qualify All Columns
    • A two-table join using ANSI Syntax
    • Both Queries have the same Results and Performance
    • Quiz – Can You Finish the Join Syntax?
    • Quiz – Can You Find the Error?
    • Super Quiz – Can You Find the Difficult Error?
    • Quiz – Which rows from both tables won’t Return?
    • LEFT OUTER JOIN
    • LEFT OUTER JOIN Results
    • RIGHT OUTER JOIN
    • RIGHT OUTER JOIN Example and Results
    • FULL OUTER JOIN
    • FULL OUTER JOIN Results
    • Which Tables are the Left and which Tables are Right?
    • INNER JOIN with Additional AND Clause
    • ANSI INNER JOIN with Additional AND Clause
    • ANSI INNER JOIN with Additional WHERE Clause
    • OUTER JOIN with Additional WHERE Clause
    • OUTER JOIN with Additional AND Clause
    • OUTER JOIN with Additional AND Clause Results
    • Quiz – Why is this considered an INNER JOIN?
    • Evaluation Order for Outer Queries
    • The DREADED Product Join
    • The DREADED Product Join Results
    • The Horrifying Cartesian Product Join
    • The ANSI Cartesian Join will ERROR
    • Quiz – Do these Joins Return the Same Answer Set?
    • The CROSS JOIN
    • The CROSS JOIN Answer Set
    • The Self Join
    • The Self Join with ANSI Syntax
    • Quiz – Will both queries bring back the same Answer Set?
    • Quiz – Will both queries bring back the same Answer Set?
    • How would you Join these two tables?
    • An Associative Table is a Bridge that Joins Two Tables
    • Quiz – Can you write the 3-Table Join?
    • Quiz – Can you write the 3-Table Join to ANSI Syntax?
    • Quiz – Can you Place the ON Clauses at the End?
    • The 5-Table Join – Logical Insurance Model
    • Quiz - Write a Five Table Join Using ANSI Syntax
    • Quiz - Write a Five Table Join Using Non-ANSI Syntax
    • Quiz –Re-Write this putting the ON clauses at the END
  • Date Function
    • Current_Timestamp
    • Getdate
    • Date and Time Keywords
    • SYSDATETIMEOFFSET Provides the Timezone Offset
    • Using Both CAST and CONVERT in Literal Values
    • The DATEADD Function
    • The DATEDIFF Function
    • DATEADD Function
    • A Real World Example for DateAdd Using the Order Table
    • DATEPART Function
    • DATEPART Function Examples
    • YEAR, MONTH, and DAY Functions
    • A Better Technique for YEAR, MONTH, and DAY Functions
    • DATENAME Function
    • ISDATE Function
  • Temporary Tables
    • Temporary Tables
    • CREATING A Derived Table
    • Naming the Derived Table
    • Aliasing the Column Names in the Derived Table
    • Multiple Ways to Alias the Columns in a Derived Table
    • CREATING a Derived Table using the WITH Command
    • The Same Derived Query shown Three Different Ways
    • MULTIPLE Derived Tables using the WITH Command
    • Column Alias Can Default For Normal Columns
    • Most Derived Tables Are Used To Join To Other Tables
    • A Join Example Showing Different Column Alias Styles
    • The Three Components of a Derived Table
    • Visualize This Derived Table
    • Our Join Example With The WITH Syntax
    • Quiz - Answer the Questions
    • Clever Tricks on Aliasing Columns in a Derived Table
    • A Derived Table lives only for the lifetime of a single query
    • An Example of Two Derived Tables in a Single Query
    • RECURSIVE Derived Table Hierarchy
    • RECURSIVE Derived Table Query
    • RECURSIVE Derived Table Definition
    • WITH RECURSIVE Derived Table Seeding
    • WITH RECURSIVE Derived Table Looping
    • RECURSIVE Derived Table Looping in Slow Motion
    • RECURSIVE Derived Table Looping Continued
    • Six rows are added in the third loop. RECURSIVE Derived Table Ends the Looping
    • RECURSIVE Derived Table Ends the Looping
    • RECURSIVE Derived Table Definition
    • RECURSIVE Derived Table Answer Set
    • What is TEMPDB?
    • Creating a Temporary Table
    • The Three Steps to Use a Private Temporary Table
    • Creating a Temporary Table With a Clustered Index
    • Creating a Columnstore Temporary Table From a CTAS
  • Sub-query Functions
    • An IN List is much like a Subquery
    • An IN List Never has Duplicates – Just like a Subquery
    • An IN List Ignores Duplicates
    • The Subquery
    • The Three Steps of How a Basic Subquery Works
    • These are Equivalent Queries
    • The Final Answer Set from the Subquery
    • Quiz- Answer the Difficult Question
    • Should you use a Subquery of a Join?
    • Quiz- Write the Subquery
    • Quiz- Write the More Difficult Subquery
    • Quiz – Write the Extreme Subquery
    • Quiz- Write the Subquery with an Aggregate
    • Quiz- Write the Correlated Subquery
    • The Basics of a Correlated Subquery
    • The Top Query always runs first in a Correlated Subquery
    • Correlated Subquery Example vs. a Join with a Derived Table
    • Quiz- A Second Chance to Write a Correlated Subquery
    • Quiz- A Third Chance to Write a Correlated Subquery
    • Quiz- Last Chance To Write a Correlated Subquery
    • Quiz – Write the Extreme Correlated Subquery
    • Quiz- Write the NOT Subquery
    • Quiz- Write the Subquery using a WHERE Clause
    • Quiz – Write the Triple Subquery
    • Quiz – How many rows return on a NOT IN with a NULL?
    • How to handle a NOT IN with Potential NULL Values
    • Using a Correlated Exists
    • How a Correlated Exists matches up
    • The Correlated NOT Exists
    • The Correlated NOT Exists Answer Set
    • Quiz – How many rows come back from this NOT Exists?
  • Window Functions OLAP
    • The Row_Number Command
    • Quiz – How did the Row_Number Reset?
    • Using a Derived Table and Row_Number
    • Ordered Analytics OVER
    • RANK and DENSE RANK
    • RANK Defaults to Ascending Order
    • Getting RANK to Sort in DESC Order
    • RANK() OVER and PARTITION BY
    • Cumulative Sum
    • The ANSI CSUM – Getting a Sequential Number
    • Troubleshooting The ANSI OLAP on a GROUP BY
    • Reset with a PARTITION BY Statement
    • PARTITION BY only Resets a Single OLAP not ALL of them
    • Sorting in DESC Order
    • Moving Average
    • Casting a Moving Average
    • Partition By Resets an ANSI OLAP
    • COUNT OVER for a Sequential Number
    • Quiz – What caused the COUNT OVER to Reset?
    • The MAX OVER Command
    • MAX OVER with PARTITION BY Reset
    • MAX OVER Without Rows Unbounded Preceding
    • The MIN OVER Command
    • Quiz – Fill in the Blank
    • How Ntile Works
    • Ntile
    • Ntile Continued
    • Ntile Percentile
    • Another Ntile Example
    • Using Quartiles (Partitions of Four)
    • NTILE Buckets
    • NTILE Using a Value of 10
    • NTILE With a Partition
    • Using LAG and LEAD
    • Using LEAD
    • Using LEAD With and Offset of 2
    • LEAD
    • LEAD With Partitioning
    • Using LAG
    • Using LAG With an Offset of 2
    • LAG
    • LAG with Partitioning
    • SUM(SUM(n))
  • Working with Strings
    • The ASCII Function
    • The CHAR Function
    • The UNICODE Function
    • The NCHAR Function
    • The LEN Function
    • The DATALENGTH Function
    • Concatenation
    • The RTRIM and LTRIM Command trims Spaces
    • The SUBSTRING Command
    • Using SUBSTRING to move Backwards
    • How SUBSTRING Works with a Starting Position of -1
    • How SUBSTRING Works with an Ending Position of 0
    • Concatenation and SUBSTRING
    • SUBSTRING and Different Aliasing
    • The LEFT and RIGHT Functions
    • Four Concatenations Together
    • The DATALENGTH Function and RTRIM
    • A Visual of the TRIM Command Using Concatenation
    • CHARINDEX Function Finds a Letter(s) Position in a String
    • The CHARINDEX Command is brilliant with SUBSTRING
    • The CHARINDEX Command Using a Literal
    • PATINDEX Function
    • PATINDEX Function to Find a Character Pattern
    • SOUNDEX Function to Find a Sound
    • DIFFERENCE Function to Quantile a Sound
    • The REPLACE Function
    • LEN and REPLACE Functions for Number of Occurrences
    • REPLICATE Function
    • STUFF Function
    • STUFF without Deleting Function
    • UPPER and lower Functions
  • Interrogating the Data
    • Quiz – What would the Answer be?
    • The NULLIF Command
    • Quiz – Fill in the Answers for the NULLIF Command
    • The COALESCE Command – Fill In the Answers
    • The COALESCE Answer Set
    • COALESCE is Equivalent to This CASE Statement
    • The Basics of CAST (Convert and Store)
    • Some Great CAST (Convert and Store) Examples
    • A Rounding Example
    • Quiz - CAST Examples
    • Quiz - The Basics of the CASE Statements
    • Using an ELSE in the Case Statement
    • Using an ELSE as a Safety Net
    • Rules For a Valued Case Statement
    • Rules for a Searched Case Statement
    • Valued Case Vs. A Searched Case
    • Quiz - Valued Case Statement
    • Quiz - Searched Case Statement
    • Quiz - When NO ELSE is present in CASE Statement
    • Quiz -When an Alias is NOT used in a CASE Statement
    • Combining Searched Case and Valued Case
    • A Trick for getting a Horizontal Case
    • Nested Case
    • Put a CASE in the ORDER BY
  • Table Create and Data Types
    • Creating a Database
    • Creating a Table that is a Heap
    • Heap Page
    • Extents
    • Creating a Table That Has a Clustered Index
    • Clustered Index Page
    • When Do I Create a Clustered Index?
    • B-Trees
    • The Building of a B-Tree for a Clustered Index
    • The Row Offset Array is the Guidance System For Every Row
    • The Row Offset Array Provides Two Search Options
    • The Row Offset Array Helps With Inserts
    • What is a Uniquefier?
    • Adding an Index
    • When Do I Create a Non Clustered Index?
    • B-Tree for Non Clustered Index on a Clustered Table
    • Adding a Non Clustered Index To A Heap
    • B-Tree for Non Clustered Index on a Heap Table
    • Default Values
  • View Functions
    • The Fundamentals of Views
    • Creating a Simple View to Restrict Sensitive Columns
    • Creating a Simple View to Restrict Rows
    • Basic Rules for Views
    • Two Exceptions to the ORDER BY Rule inside a View
    • Views sometimes CREATED for Row Security
    • Creating a View to Join Tables Together
    • You Select From a View
    • Another Way to Alias Columns in a View CREATE
    • The Standard Way Most Aliasing is done
    • What Happens When Both Aliasing Options Are Present
    • Resolving Aliasing Problems in a View CREATE
    • Answer to Resolving Aliasing Problems in a View CREATE
    • Aggregates on View Aggregates
    • Altering a Table
    • Altering a Table after a View has been Created
    • A View that Errors After an ALTER
    • Troubleshooting a View
    • Loading Data through a View
  • Data Manipulation Language (DML)
    • INSERT Syntax # 1
    • INSERT Example with Syntax 1
    • INSERT Syntax #2
    • INSERT Example with Syntax 2
    • INSERT/SELECT Command
    • INSERT/SELECT Example using All Columns (*)
    • INSERT/SELECT Example with Less Columns
    • The UPDATE Command Basic Syntax
    • Two UPDATE Examples
    • Subquery UPDATE Command Syntax
    • Example of Subquery UPDATE Command
    • Join UPDATE Command Syntax
    • Example of an UPDATE Join Command
    • The DELETE Command Basic Syntax
    • Two DELETE Examples to DELETE ALL Rows in a Table
    • To DELETE or to TRUNCATE
    • A DELETE Example Deleting only Some of the Rows
    • Subquery and Join DELETE Command Syntax
    • Example of Subquery DELETE Command
    • MERGE INTO
  • Set Operators Functions
    • Rules of Set Operators
    • INTERSECT Explained Logically
    • UNION Explained Logically
    • UNION ALL Explained Logically
    • EXCEPT Explained Logically
    • Another EXCEPT Example
    • EXCEPT Explained Logically in Reverse Order
    • An Equal Amount of Columns in both SELECT List
    • Columns in the SELECT list should be from the same Domain
    • The Top Query handles all Aliases
    • The Bottom Query does the ORDER BY
    • Great Trick: Place your Set Operator in a Derived Table
    • UNION Vs UNION ALL
    • Using UNION ALL and Literals
    • A Great Example of how EXCEPT works
    • USING Multiple SET Operators in a Single Request
    • Changing the Order of Precedence with Parentheses
    • Building Grouping Sets Using UNION
    • Three Grouping Sets Using a UNION
  • Stored Procedure Functions
    • Creating a Stored Procedure
    • Executing a Stored Procedure
    • There are Three Ways to Execute a Stored Procedure
    • Creating a Stored Procedure with a CASE Statement
    • Our Answer Set
    • Dropping a Stored Procedure
    • Passing an Input Parameter to a Stored Procedure
    • Executing With Positional Parameter vs. Named Parameters
    • Passing an Output Parameter to a Stored Procedure
    • Changing a Stored Procedure with an ALTER
    • Answer Set for the Altered Stored Procedure
    • Using a Stored Procedure to Delete a Row
    • A Different Method to Delete a Row
    • Deleting a Row Using an Input Parameter
    • Using Loops in Stored Procedures
    • Stored Procedure Workshop
    • Looping with a WHILE Statement
  • Statistical Aggregate Functions
    • The Stats Table
    • Above, is the Stats_Table data in which we will use in our statistical examples
    • The VAR and VARP Functions
    • A VAR Example
    • A VARP Example
    • The STDEV and STDEVP Functions
    • A STDEV Example
    • A STDEVP Example
  • Systems Views
    • System Views
    • sys.all_columns
    • sys.all_objects
    • sys.all_sql_modules
    • sys.all_views
    • sys.columns
    • sys.data_spaces
    • sys.database_files
    • sys.database_principals
    • sys.database_role_members
    • sys.databases
    • sys.filegroups
    • sys.identity_columns
    • sys.objects
    • sys.partition_range_values
    • sys.schemas
    • sys.server_role_members
    • sys.sql_logins
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