Amazon Redshift SQL Training

In this training class, students will learn the Amazon Redshift SQL starting at the most basic level and going to the most advanced level with many examples.

  1. Learn to gain a deeper knowledge and understanding of the Amazon Redshift SQL and how to write it.
  1. Basic SQL Functions
    1. Finding the Current Schema on the Leader Node
    2. Getting Things Setup in Your Search Path
    3. Five Details You Need To Know About The Search_Path
    4. Introduction
    5. SELECT * (All Columns) in a Table
    6. SELECT Specific Columns in a Table
    7. Commas in the Front or Back?
    8. Place your Commas in front for better Debugging Capabilities
    9. Sort the Data with the ORDER BY Keyword
    10. ORDER BY Defaults to Ascending
    11. Use the Name or the Number in your ORDER BY Statement
    12. Two Examples of ORDER BY using Different Techniques
    13. Changing the ORDER BY to Descending Order
    14. NULL Values sort First in Ascending Mode (Default)
    15. NULL Values sort Last in Descending Mode (DESC)
    16. Major Sort vs. Minor Sorts
    17. Multiple Sort Keys using Names vs. Numbers
    18. Sorts are Alphabetical, NOT Logical
    19. Using A CASE Statement to Sort Logically
    20. How to ALIAS a Column Name
    21. A Missing Comma can by Mistake become an Alias
    22. Comments using Double Dashes are Single Line Comments
    23. Comments for Multi-Lines
    24. Comments for Multi-Lines As Double Dashes Per Line
    25. A Great Technique for Comments to Look for SQL Errors
  2. The WHERE Clause
    1. Using Limit to bring back a Sample
    2. Using Limit With an Order By Statement
    3. The WHERE Clause limits Returning Rows
    4. Using a Column ALIAS throughout the SQL
    5. Double Quoted Aliases are for Reserved Words and Spaces
    6. Character Data needs Single Quotes in the WHERE Clause
    7. Character Data needs Single Quotes, but Numbers Don’t
    8. NULL means UNKNOWN DATA so Equal (=) won’t Work
    9. Use IS NULL or IS NOT NULL when dealing with NULLs
    10. NULL is UNKNOWN DATA so NOT Equal won’t Work
    11. Use IS NULL or IS NOT NULL when dealing with NULLs
    12. Using Greater Than Or Equal To (>=)
    13. AND in the WHERE Clause
    14. Troubleshooting AND
    15. OR in the WHERE Clause
    16. Troubleshooting Or
    17. Troubleshooting Character Data
    18. Using Different Columns in an AND Statement
    19. What is the Order of Precedence?
    20. Using Parentheses to change the Order of Precedence
    21. Using an IN List in place of OR
    22. The IN List is an Excellent Technique
    23. IN List vs. OR brings the same Results
    24. Using a NOT IN List
    25. Null Values in a NOT IN List Bring Back No Rows
    26. Another Technique for Handling Nulls with a NOT IN List
    27. BETWEEN is Inclusive
    28. NOT BETWEEN is Also Inclusive
    29. LIKE uses Wildcards Percent ‘%’ and Underscore ‘_’
    30. LIKE command Underscore is Wildcard for one Character
    31. LIKE Command Works Differently on Char Vs Varchar
    32. The Ilike Command Is NOT Case Sensitive
    33. Troubleshooting LIKE Command on Character Data
    34. Introducing the TRIM Command
    35. Numbers are Right Justified and Character Data is Left
    36. An Example of Data with Left and Right Justification
    37. A Visual of CHARACTER Data vs. VARCHAR Data
    38. Use the TRIM command to remove spaces on CHAR Data
    39. Like and Your Escape Character of Choice
    40. Like and the Default Escape Character
    41. Similar To Operators
    42. Similar To Operators
    43. Similar To Example With Lower Case Letters
    44. Similar To Example With Lower and Upper Case Letters
    45. Similar To Example With Multiple Occurrences
    46. Multiple Occurrences Must Be Consecutive
  3. Distinct Vs Group By AND TOP
    1. The Distinct Command
    2. Distinct vs. GROUP BY
    3. TOP Command
    4. TOP Command is brilliant when ORDER BY is Used!
    5. What is the Difference Between TOP and LIMIT?
  4. Aggregation
    1. The Rules of Aggregation
    2. There are Five Aggregates
    3. Troubleshooting Aggregates
    4. GROUP BY when Aggregates and Normal Columns Mix
    5. GROUP BY Delivers one row per Group
    6. GROUP BY Dept_No or GROUP BY the same thing
    7. Limiting Rows and Improving Performance with WHERE
    8. WHERE Clause in Aggregation limits unneeded Calculations
    9. Keyword HAVING tests Aggregates after they are Totaled
    10. Keyword HAVING is like an Extra WHERE Clause for Totals
  5. Join Functions
    1. A Two-Table Join Using Traditional Syntax
    2. A two-table join using Non-ANSI Syntax with Table Alias
    3. You Can Fully Qualify All Columns
    4. A two-table join using ANSI Syntax
    5. Both Queries have the same Results and Performance
    7. LEFT OUTER JOIN Results
    8. Left Outer Joins Compatible with Oracle
    10. RIGHT OUTER JOIN Example and Results
    11. Right Outer Joins Compatible with Oracle
    13. FULL OUTER JOIN Results
    14. Which Tables are the Left and Which are the Right?
    15. INNER JOIN with Additional AND Clause
    16. ANSI INNER JOIN with Additional AND Clause
    17. ANSI INNER JOIN with Additional WHERE Clause
    18. OUTER JOIN with Additional WHERE Clause
    19. OUTER JOIN with Additional AND Clause
    20. OUTER JOIN with Additional AND Clause Results
    21. The DREADED Product Join
    22. The DREADED Product Join Results
    23. The Horrifying Cartesian Product Join
    24. The ANSI Cartesian Join will ERROR
    25. The CROSS JOIN
    26. The CROSS JOIN Answer Set
    27. The Self Join
    28. The Self Join with ANSI Syntax
    29. How would you Join these two tables?
    30. An Associative Table is a Bridge that Joins Two Tables
    31. The 5-Table Join – Logical Insurance Model
  6. Date Functions
    1. Current_Date
    2. TIMEOFDAY()
    3. SYSDATE Returns a Timestamp With Microseconds
    4. GETDATE Returns a Timestamp Without Microseconds
    5. Add or Subtract Days from a date
    6. The ADD_MONTHS Command Returns a Timestamp
    7. The ADD_MONTHS Command With Trunc Removes Time
    8. ADD_MONTHS Command to Add -Year or -Years
    9. Dateadd Function And Add_Months Function are Different
    10. The EXTRACT Command
    11. EXTRACT from DATES and TIME
    12. EXTRACT with DATE and TIME Literals
    13. EXTRACT of the Month on Aggregate Queries
    14. The Datediff command
    15. The Datediff Function on Column Data
    16. The Date_Part Function Using a Date
    17. The Date_Part Function Using a Time
    18. Date_Part Abbreviations
    19. The to_char command
    20. Conversion Functions
    21. Conversion Function Templates
    22. Conversion Function Templates Continued
    23. Formatting A Date
    24. A Summary of Math Operations on Dates
    25. Using a Math Operation to find your Age in Years
    26. Date Related Functions
    27. A Side Title example with Reserved Words as an Alias
    28. Implied Extract of Day, Month and Year
    29. DATE_PART Function
    30. DATE_PART Function using an ALIAS
    31. DATE_TRUNC Function
    32. DATE_TRUNC Function using TIME
    33. MONTHS_BETWEEN Function
    34. MONTHS_BETWEEN Function in Action
    35. ANSI TIME
    37. Redshift TIMESTAMP Function
    38. Redshift TO_TIMESTAMP Function
    39. Redshift NOW() Function
    40. Redshift TIMEOFDAY Function
    41. Redshift AGE Function
    42. Time Zones
    43. Setting Time Zones
    44. Using Time Zones
    45. Intervals for Date, Time and Timestamp
    46. Using Intervals
    47. Troubleshooting The Basics of a Simple Interval
    48. Interval Arithmetic Results
    49. A Date Interval Example
    50. A Time Interval Example
    51. A DATE Interval Example
    52. A Complex Time Interval Example using CAST
    53. A Complex Time Interval Example using CAST
    54. The OVERLAPS Command
    55. An OVERLAPS Example that Returns No Rows
    56. The OVERLAPS Command using TIME
    57. The OVERLAPS Command using a NULL Value
  7. Window Functions
    1. Cumulative Sum (CSUM)
    2. CSUM – The Sort Explained
    3. CSUM – Rows Unbounded Preceding Explained
    4. CSUM – Making Sense of the Data
    5. CSUM – Making Even More Sense of the Data
    6. CSUM – The Major and Minor Sort Key(s)
    7. Reset with a PARTITION BY Statement
    8. PARTITION BY only Resets a Single OLAP not ALL of them
    9. ANSI Moving Window is Current Row and Preceding n Rows
    10. How ANSI Moving SUM Handles the Sort
    11. Moving SUM every -rows Vs a Continuous Average
    12. Partition By Resets an ANSI OLAP
    13. Moving Average
    14. The Moving Window is Current Row and Preceding
    15. How Moving Average Handles the Sort
    16. Moving Average every -rows Vs a Continuous Average
    17. Partition By Resets an ANSI OLAP
    18. RANK Defaults to Ascending Order
    19. Getting RANK to Sort in DESC Order
    21. RANK() OVER And LIMIT
    23. PERCENT_RANK() OVER with rows in Calculation
    24. PERCENT_RANK() OVER with rows in Calculation
    25. COUNT OVER for a Sequential Number
    26. The MAX OVER Command
    27. MAX OVER with PARTITION BY Reset
    28. The MIN OVER Command
    29. The Row_Number Command
    30. Standard Deviation Functions Using STDDEV / OVER
    31. Standard Deviation Functions and STDDEV / OVER Syntax
    32. STDDEV / OVER Example
    33. VARIANCE / OVER Syntax
    34. Variance Functions Using VARIANCE / OVER
    35. Using VARIANCE with PARTITION BY Example
    36. Using FIRST_VALUE and LAST_VALUE
    37. Using FIRST_VALUE
    39. FIRST_VALUE After Sorting by the Highest Value
    40. FIRST_VALUE with Partitioning
    41. FIRST_VALUE Combined with Row_Number
    42. FIRST_ FIRST_VALUE And Row_Number with Different Sort
    43. Using LAG and LEAD
    44. Using LEAD
    45. Using LEAD with a PARTITION Statement
    46. Using LEAD With an Offset of
    47. Using LEAD With an Offset of and a PARTITION
    48. Using LAG
    49. Using LAG with a PARTITION Statement
    50. Using LAG With an Offset of
    51. Using LAG With an Offset of and a PARTITION
    52. CUME_DIST
    53. CUME_DIST With a Partition
    54. RANK and DENSE RANK
    55. LISTAGG Function
    56. LISTAGG Basic Example
    57. Another Example of LISTAGG
    58. LISTAGG With a Pipe-Separated List
    59. LISTAGG With a Comma-Separated List in Groups
    60. MEDIAN Function
    61. MEDIAN Example
    62. MEDIAN with Partitioning and a WHERE Clause
    63. MEDIAN with Partitioning
    64. NTILE Function
    65. How Ntile Works
    66. Ntile
    67. Ntile Continued
    68. Ntile Percentile
    69. Another Ntile Example
    70. Using Tertiles (Partitions of Four)
    71. NTILE
    72. NTILE Using a Value of
    73. NTILE With a Partition
    74. NTH_VALUE Function and Syntax
    75. NTH_VALUE Arguments
    76. NTH_VALUE
    77. NTH_VALUE With Partition
    78. NTH_VALUE With Partition
    79. PERCENTILE_CONT Function Description and Syntax
    80. Final Result Information About PERCENTILE_CONT
    81. PERCENTILE_CONT Function Arguments
    82. PERCENTILE_CONT Example
    83. PERCENTILE_CONT Example with Percentage Change
    85. PERCENTILE_CONT With PARTITION and ( . )
    86. PERCENTILE_DISC Function Description and Syntax
    87. PERCENTILE_DISC Function Arguments
    88. PERCENTILE_DISC Example
    89. PERCENTILE_DISC Example with Percentage Change
    91. PERCENTILE_DISC With PARTITION and ( . )
    92. RATIO_TO_REPORT Function
    93. RATIO_TO_REPORT Example
    94. RATIO_TO_REPORT Example with Partitioning
  8. Temporary Tables
    1. CREATING A Derived Table
    2. The Three Components of a Derived Table
    3. Naming the Derived Table
    4. Aliasing the Column Names in The Derived Table
    5. Visualize This Derived Table
    6. Most Derived Tables Are Used To Join To Other Tables
    7. Multiple Ways to Alias the Columns in a Derived Table
    8. Our Join Example With A Different Column Aliasing Style
    9. Column Aliasing Can Default For Normal Columns
    10. CREATING A Derived Table using the WITH Command
    11. A Join Using the WITH Syntax
    12. WITH
    13. A WITH Clause That Produces Two Tables
    14. Finding the First Occurrence of a Row using WITH
    15. Finding the First Occurrence of a Row using a Derived Table
    16. Finding the Last Occurrence Using a WITH Derived Table
    17. Finding the Last Occurrence Using a Derived Table
    18. The Same Derived Query shown Three Different Ways
    19. Clever Tricks on Aliasing Columns in a Derived Table
    20. A Derived Table lives only for the lifetime of a single query
    21. An Example of Two Derived Tables in a Single Query
    22. Create Table Syntax
    23. Basic Temporary Table Examples
    24. More Advanced Temporary Table Examples
    25. Advanced Temporary Table Examples
    26. Performing a Deep Copy
    27. Deep Copy Using the Original DDL
    28. Deep Copy Using A CTAS
    29. Deep Copy Using A Create Table LIKE
    30. Deep Copy By Creating a Temp Table and Truncating Original
  9. Sub-query Functions
    1. An IN List is much like a Subquery
    2. An IN List Never has Duplicates – Just like a Subquery
    3. An IN List Ignores Duplicates
    4. The Subquery
    5. The Three Steps of How a Basic Subquery Works
    6. These are Equivalent Queries
    7. The Final Answer Set from the Subquery
    8. The Basics of a Correlated Subquery
    9. The Top Query always runs first in a Correlated Subquery
    10. Correlated Subquery Example vs. a Join with a Derived Table
    11. How to handle a NOT IN with Potential NULL Values
    12. Using a Correlated Exists
    13. How a Correlated Exists matches up
    14. The Correlated NOT Exists
    15. Substrings and Positioning Functions
    16. The TRIM Command trims both Leading and Trailing Spaces
    17. A Visual of the TRIM Command Using Concatenation
    18. Trim and Trailing is Case Sensitive
    19. How to TRIM Trailing Letters
    20. The SUBSTRING Command
    22. Using SUBSTRING to move Backwards
    23. How SUBSTRING Works with a Starting Position of -
    24. How SUBSTRING Works with an Ending Position of
    25. The POSITION Command finds a Letters Position
    26. Using the SUBSTRING to Find the Second Word On
    27. Concatenation
    28. Concatenation and SUBSTRING
    29. Four Concatenations Together
    30. Troubleshooting Concatenation
    31. Declaring a Cursor
  10. Interrogating the Data
    1. The NULLIFZERO Command
    2. The ZEROIFNULL Command
    3. The COALESCE Command
    4. The COALESCE Answer Set
    5. The Coalesce Quiz
    6. The Basics of CAST (Convert And STore)
    7. Some Great CAST (Convert And STore) Examples
    8. Some Great CAST (Convert And STore) Examples
    9. Some Great CAST (Convert And STore) Examples
    10. The Basics of the CASE Statements
    11. The Basics of the CASE Statement
    12. Valued Case Vs. A Searched Case
    13. Combining Searched Case and Valued Case
    14. Nested Case
    15. Put a CASE in the ORDER BY
  11. View Functions
    1. Creating a Simple View to Restrict Sensitive Columns
    2. Creating a Simple View to Restrict Sensitive Columns
    3. Creating a Simple View to Restrict Rows
    4. Creating a View to Join Tables Together
    5. You Select From a View
    6. Basic Rules for Views
    7. An ORDER BY Example Inside of a View
    8. An ORDER BY Inside of a View That is Queried Differently
    9. Creating a View With Ordered Analytics
    10. Creating a View With The TOP Command
    11. Creating a View With The LIMIT Command
    12. Altering A Table
    13. Altering A Table After a View has been Created
    14. A View that Errors After An ALTER
    15. Troubleshooting a View
    16. Updating Data in a Table through a View
  12. Set Operators Functions
    1. Rules of Set Operators
    2. INTERSECT Explained Logically
    3. INTERSECT Explained Logically
    4. UNION Explained Logically
    5. UNION Explained Logically
    6. UNION ALL Explained Logically
    7. UNION Explained Logically
    8. EXCEPT Explained Logically
    9. EXCEPT Explained Logically
    10. Minus Explained Logically
    11. Minus Explained Logically
    12. Testing Your Knowledge
    13. Testing Your Knowledge
    14. An Equal amount of Columns in both SELECT List
    15. Columns in the SELECT list should be from the same Domain
    16. The Top Query handles all Aliases
    17. The Bottom Query does the ORDER BY (a Number)
    18. Great Trick: Place your Set Operator in a Derived Table
    19. UNION vs. UNION ALL
    20. A Great Example of how EXCEPT works
  13. Statistical Aggregate Functions
    1. The Stats Table
    2. STDDEV
    3. Casting STDDEV_SAMP and SQRT (VAR_SAMP)
    4. The STDDEV_POP Function
    5. A STDDEV_POP Example
    6. The STDDEV_SAMP Function
    7. A STDDEV_SAMP Example
    8. The VAR_POP Function
    9. A VAR_POP Example
    10. The VAR_SAMP Function
    11. A VAR_SAMP Example
Class Materials

Each student in our Live Online and our Onsite classes receives a comprehensive set of materials, including course notes and all the class examples.

Training for your Team

Length: 2 Days
  • Private Class for your Team
  • Online or On-location
  • Customizable
  • Expert Instructors

What people say about our training

I now love Excel!
Kori Grillo
Preferred HCNY
This was a great class. I am new to project management and this gives me a great stepping stone to effective project management.
Janet Hunt
Gave a good base to start learning Java. Now I have a better understanding of how our Java applications work. I feel more confident that I can eventually become a Java pro. I would take more Webucator classes.
Shiju Daniel
City of Philadelphia District Attorney's Office
Andrea Tijerina
Rady Childrens Hospital, San Diego

No cancelation for low enrollment

Certified Microsoft Partner

Registered Education Provider (R.E.P.)

GSA schedule pricing


Students who have taken Instructor-led Training


Organizations who trust Webucator for their Instructor-led training needs


Satisfaction guarantee and retake option


Students rated our trainers 9.29 out of 10 based on 29,006 reviews

Contact Us or call 1-877-932-8228