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SQL Advanced level for Analysts Training
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Drive Team Excellence with SQL Advanced level for Analysts Corporate Training

Empower your teams with expert-led on-site, off-site, and virtual SQL Advanced level for Analysts Training through Edstellar, a premier corporate training provider for organizations globally. Designed to meet your specific training needs, this group training program ensures your team is primed to drive your business goals. Help your employees build lasting capabilities that translate into real performance gains.

Advanced SQL uses complex queries and techniques to manipulate and retrieve data from relational databases. SQL Advanced level for Analysts provides analysts with an in-depth understanding of advanced SQL techniques and practices. It is necessary to equip teams with the skills to handle intricate data analysis tasks, generate sophisticated reports, and enhance database performance to derive valuable insights from large datasets. The SQL Advanced level for Analysts training enables employees to handle complex data structures, utilize advanced functions, and develop stored procedures to extract, manipulate, and analyze data effectively.

The SQL Advanced level for Analysts instructor-led training course provided by Edstellar can be customized to meet team requirements. The virtual/onsite course, led by expert trainers, ensures employees master optimization strategies and explore complex database operations.

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Key Skills Employees Gain from instructor-led SQL Advanced level for Analysts Training

SQL Advanced level for Analysts skills corporate training will enable teams to effectively apply their learnings at work.

  • Query Optimization 
    Query Optimization is the process of enhancing database queries to improve performance and efficiency. This skill is important for data analysts and database administrators to ensure fast data retrieval, reduce resource consumption, and enhance overall system performance.
  • Advanced Joins 
    Advanced Joins refer to complex SQL techniques used to combine data from multiple tables. This skill is important for data analysts and database developers to extract meaningful insights and optimize queries efficiently.
  • Window Functions 
    Window Functions are SQL features that perform calculations across a set of table rows related to the current row. this skill is important for data analysts and engineers to efficiently analyze trends and patterns in large datasets.
  • Subquery Mastery 
    Subquery Mastery involves crafting and optimizing nested queries within SQL to retrieve complex data efficiently. This skill is important for data analysts and database developers, as it enhances data retrieval accuracy and performance, enabling informed decision-making.
  • Data Aggregation 
    Data Aggregation is the process of collecting and summarizing data from various sources. This skill is important for data analysts and business intelligence roles to derive insights and inform decision-making.
  • Transaction Control
    Transaction Control is the ability to manage and oversee financial transactions effectively, ensuring accuracy and compliance. this skill is important for roles in finance, accounting, and auditing, as it helps maintain integrity and trust in financial reporting.

Key Learning Outcomes of SQL Advanced level for Analysts Training Workshop for Employees

Upon completing Edstellar’s SQL Advanced level for Analysts workshop, employees will gain valuable, job-relevant insights and develop the confidence to apply their learning effectively in the professional environment.

  • Analyze and filter data using WHERE clauses with complex conditions, operators, and functions
  • Sort query results effectively using the ORDER BY clause with proper understanding of precedence and hierarchy
  • Apply various SQL functions (character, numeric, datetime) for data manipulation and conversion
  • Create complex queries with aggregate functions (COUNT, SUM, AVG, MIN, MAX) and GROUP BY clauses for data summarization and grouping
  • Implement different join types (inner, outer, various SQL99 joins) to combine data from multiple tables
  • Utilize subqueries for complex data retrieval tasks, including single-row and multi-row subqueries with appropriate operators
  • Analyze and combine query results using set operations (UNION, UNION ALL, INTERSECT, MINUS/EXCEPT)
  • Manage transactions effectively using COMMIT, ROLLBACK, and SAVEPOINT statements for data consistency

Key Benefits of the SQL Advanced level for Analysts Group Training

Attending our SQL Advanced level for Analysts group training classes provides your team with a powerful opportunity to build skills, boost confidence, and develop a deeper understanding of the concepts that matter most. The collaborative learning environment fosters knowledge sharing and enables employees to translate insights into actionable work outcomes.

  • Empowers employees with the skills to write complex queries using advanced filtering techniques with WHERE clause
  • Develops the required skills in employees to effectively sort and organize query results using the ORDER BY clause
  • Provides insights into various SQL functions (character, numeric, datetime) for data manipulation and conversion tasks
  • Equips the team with the techniques to create insightful data summaries using aggregate functions (COUNT, SUM, AVG, MIN, MAX) and GROUP BY clauses
  • Cultivates ideas in employees for strategically joining tables using different join types (inner, outer, various SQL99 joins) for data analysis
  • Develops the skills to write subqueries to answer complex data retrieval questions, including single-row and multi-row applications
  • Empowers employees with the techniques to combine and manipulate query results using set operations (UNION, UNION ALL, INTERSECT, MINUS/EXCEPT)
  • Provides insights into managing transactions with COMMIT, ROLLBACK, and SAVEPOINT statements to ensure data consistency

Topics and Outline of SQL Advanced level for Analysts Training

Our virtual and on-premise SQL Advanced level for Analysts training curriculum is structured into focused modules developed by industry experts. This training for organizations provides an interactive learning experience that addresses the evolving demands of the workplace, making it both relevant and practical.

  1. Syntax rules
    • Basic SQL syntax
    • Syntax conventions
  2. Selecting all columns
    • Using SELECT *
    • Advantages and drawbacks
  3. Projection
    • Specifying columns
    • Renaming columns
  4. Arithmetical operations
    • Addition, subtraction, multiplication, division
    • Order of operations
  5. Column aliases
    • Assigning aliases
    • Usage in SELECT statements
  6. Literals
    • Numeric literals
    • String literals
  7. Concatenation
    • Using CONCAT function
    • Using '+' operator
  1. WHERE clause
    • Basic WHERE clause
    • Multiple conditions
  2. Comparison operators
    • Equal to (=)
    • Not equal to (<>)
    • Greater than(>)
    • Less than(<)
    • Greater than or equal to(>=)
    • Less than or equal to(<=)
    • Using with NULL values
  3. LIKE condition
    • Pattern matching
    • Using wildcards
  4. BETWEEN AND condition
    • Including endpoints
    • Combining with other conditions
  5. IS NULL condition
    • Checking for NULL values
    • Using IS NOT NULL
  6. IN condition
    • Specifying multiple values
    • Subqueries with IN
  7. Logical operators (AND, OR, NOT)
    • Combining conditions
    • Using NOT operator
  8. Multiple conditions and order
    • Precedence of operators
    • Using parentheses
  9. DISTINCT clause
    • Eliminating duplicates
    • Usage in SELECT queries
  1. ORDER BY clause
    • Sorting in ascending order
    • Sorting in descending order
  2. Sorting by multiple columns
    • Sorting hierarchy
    • Using multiple columns
  1. Single-row vs multi-row functions
    • Difference and usage
    • Examples of each
  2. Character, numeric, DateTime functions
    • Common character functions
    • Numeric and DateTime functions
  3. Explicit and implicit conversion
    • Explicit CAST and CONVERT
    • Implicit conversions
  4. Conversion functions
    • TO_CHAR, TO_NUMBER, TO_DATE
    • Format specifiers
  5. Nested functions
    • Combining functions
    • Order of execution
  6. Dual table
    • Purpose and usage
    • Oracle vs other databases
  7. Current date and time functions
    • SYSDATE, CURRENT_TIMESTAMP
    • Time zone considerations
  1. Aggregate functions
    • COUNT, SUM, AVG, MIN, MAX
    • Using DISTINCT with aggregates
  2. Handling NULL values
    • Ignoring NULLs in aggregate functions
    • COALESCE and NVL functions
  3. GROUP BY clause
    • Grouping data
    • Using with multiple columns
  4. Grouping by multiple columns
    • Hierarchical grouping
    • Rollup and Cube options
  5. Filtering aggregated data with HAVING
    • Using aggregate results
    • Multiple HAVING conditions
  6. Multidimensional grouping (ROLLUP and CUBE)
    • Creating subtotals
    • Generating multiple levels of aggregation
  7. Identifying summaries (GROUPING)
    • GROUPING function usage
    • Identifying groupings
  8. GROUPING SETS operator
    • Combining multiple GROUP BY operations
    • Custom groupings
  1. Types of joins
    • Inner join
    • Outer join
  2. NATURAL JOIN
    • Matching columns automatically
    • Potential pitfalls
  3. Table aliases
    • Assigning aliases
    • Using aliases in queries
  4. Oracle join conditions
    • Using (+) notation
    • Oracle-specific joins
  5. SQL99 joins (INNER, LEFT, RIGHT, FULL)
    • Standard SQL joins
    • Differences and advantages
  6. Cartesian product
    • Definition and examples
    • Avoiding unintended results
  1. Subquery conditions
    • Where to use subqueries
    • Nesting subqueries
  2. Single-row vs multi-row subqueries
    • Difference in result set
    • Use cases
  3. Single-row subquery operators
    • Comparison operators
    • IN, ANY, ALL
  4. Aggregate functions in subqueries
    • Using aggregates in subqueries
    • Grouping and filtering
  5. Multi-row subquery operators (IN, ALL, ANY)
    • Comparing multiple values
    • Using with aggregate functions
  1. UNION
    • Combining result sets
    • Removing duplicates
  2. UNION ALL
    • Combining all rows
    • Including duplicates
  3. INTERSECT
    • Common rows between queries
    • Usage scenarios
  4. MINUS/EXCEPT
    • Rows in the first query but not the second
    • Use cases and examples
  1. COMMIT
    • Saving changes
    • Transaction finalization
  2. ROLLBACK
    • Undoing changes
    • Transaction cancellation
  3. SAVEPOINT statements
    • Creating savepoints
    • Rolling back to savepoints
  1. Sequences
    • Creating sequences
    • Usage in tables
  2. Synonyms
    • Creating and managing synonyms
    • Advantages of using synonyms
  3. Views
    • Creating views
    • Using views in queries
  1. Tree construction (CONNECT BY PRIOR and START WITH)
    • Creating hierarchical data
    • Querying hierarchical data
  2. SYS_CONNECT_BY_PATH function
    • Retrieving path in a hierarchy
    • Usage examples
  1. CASE expression
    • Simple and searched CASE
    • Using in SELECT, WHERE, and ORDER BY
  2. DECODE expression
    • Replacing multiple IF-THEN-ELSE
    • Using in SELECT statements
  1. Time zones
    • Understanding time zones
    • Time zone offsets
  2. TIMESTAMP data types
    • Storing date and time
    • Precision options
  3. DATE vs TIMESTAMP
    • Differences and usage scenarios
    • Conversion between types
  4. Time zone conversions
    • Converting between time zones
    • Handling daylight saving time
  1. Partitioning data
    • Logical and physical partitioning
    • Partitioning strategies
  2. Window functions
    • Understanding window frames
    • ROW_NUMBER, RANK, DENSE_RANK
  3. Rank functions
    • Ranking data
    • Partitioned ranking
  4. Reporting functions
    • Generating reports
    • PIVOT and UNPIVOT
  5. LAG/LEAD functions
    • Accessing previous or next row values
    • Use cases
  6. FIRST/LAST functions
    • Accessing first or last row values
    • Ordering and filtering
  7. Reverse percentile functions
    • Percentile calculations
    • Inverse percentile functions
  8. Hypothetical rank functions
    • HYPOTHETICAL_RANK
    • Simulating ranking functions
  9. WIDTH_BUCKET functions
    • Binning data
    • Grouping into buckets
  10. Statistical functions
    • MEAN, MEDIAN, MODE
    • Variance and standard deviation

Who Can Take the SQL Advanced level for Analysts Training Course

The SQL Advanced level for Analysts training program can also be taken by professionals at various levels in the organization.

  • Data Analysts
  • SQL Developers
  • Business Analysts
  • Database Administrators
  • Data Engineers
  • IT Professionals
  • Systems Analysts
  • Data Scientists
  • BI Analysts
  • Research Analysts
  • ETL Developers
  • Managers

Prerequisites for SQL Advanced level for Analysts Training

There are no specific prerequisites for SQL Advanced level for Analysts training. However, it is beneficial to have a basic understanding of SQL querying and database concepts.

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