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An Introduction to the 70-762 Exam and SQL Server Database Design

The 70-762 Exam, titled "Developing SQL Databases," was a key component of the Microsoft Certified Solutions Associate (MCSA): SQL 2016 Database Development certification. It is essential to understand from the outset that Microsoft retired this exam and the entire MCSA certification track on January 31, 2021. Therefore, it is no longer possible to take the 70-762 Exam or achieve this specific certification. The current focus in the Microsoft ecosystem has shifted towards role-based certifications related to Azure data services.

Despite its retirement, the skills and knowledge validated by the 70-762 Exam remain highly relevant and foundational for any professional working with Microsoft SQL Server or other relational database systems. The exam's objectives provide an excellent framework for learning the core principles of database development, from initial design and implementation to creating advanced programmability objects and optimizing query performance. This series will use that framework to guide you through these essential skills.

The Enduring Value of SQL Database Development Skills

The retirement of the 70-762 Exam does not diminish the value of the skills it covered. Every data-driven application, whether on-premises or in the cloud, relies on a well-designed and efficient database. A professional who can design normalized tables, write efficient T-SQL queries, develop robust stored procedures, and optimize performance is an invaluable asset to any development team. These are the core competencies that the 70-762 Exam was designed to measure.

The principles of relational database design, data integrity, and query optimization are timeless. The T-SQL language, while evolving with new features, remains fundamentally the same. Therefore, studying the topics of the 70-762 Exam is an excellent way to build a strong foundation in database development that is directly transferable to modern versions of SQL Server, Azure SQL Database, and other database platforms. It is the practical skill, not the certification number, that holds long-term career value.

Designing and Implementing Tables

The most fundamental object in any relational database is the table. A significant portion of the 70-762 Exam focused on the ability to design and implement tables correctly. A table is a structured collection of data organized into rows and columns. When designing a table, you must define each column, specifying its name and, most importantly, its data type. The design process should adhere to the principles of normalization to reduce data redundancy and improve data integrity.

For example, instead of storing a customer's full address in a single text column, you would normalize it by creating separate columns for street, city, state, and postal code. This makes the data more structured and easier to query. Implementing the table involves writing a CREATE TABLE Transact-SQL (T-SQL) statement that defines all the columns, their data types, and any constraints that should be applied to them. This foundational skill is the starting point for building any database application.

Choosing the Right Data Types

Selecting the appropriate data type for each column in a table is a critical design decision and a key topic for the 70-762 Exam. The data type defines what kind of data the column can hold (e.g., numbers, text, dates) and how that data is stored physically. Choosing the right data type has a significant impact on storage efficiency, data integrity, and query performance.

For example, if a column will only ever store whole numbers between 0 and 255, using a TINYINT data type, which uses only one byte of storage, is far more efficient than using an INT (4 bytes) or a BIGINT (8 bytes). Similarly, using a DATE or DATETIME2 data type for storing dates is better than using a string data type, as it enforces data validity and allows for efficient date-based calculations. A developer must be familiar with the wide range of available data types and their specific use cases.

The Role of Schemas and Filegroups

As a database grows in complexity, it becomes important to organize its objects logically and manage its physical storage. This is where schemas and filegroups come into play, and you would need to understand their purpose for the 70-762 Exam. A schema is a logical container for database objects like tables, views, and stored procedures. It acts like a folder, allowing you to group related objects together, which simplifies management and security. For example, you could create a "Sales" schema for all tables related to sales and a "HumanResources" schema for HR-related tables.

Filegroups, on the other hand, are a physical storage concept. A filegroup is a logical collection of one or more physical data files. By creating multiple filegroups and placing specific tables or indexes on them, you can control the physical placement of your data across different disk drives. This can be used to improve performance by reducing disk I/O contention or to simplify backup and restore operations for very large databases.

Creating and Managing Views

A view is a stored SQL query that is presented to the user as a virtual table. Views are a powerful tool for simplifying data access and enhancing security, and their creation and management are an important part of the 70-762 Exam syllabus. A view can be used to join multiple tables, select a subset of columns, and present complex data in a simple, pre-defined format. This allows application developers and report writers to interact with a simple view without needing to understand the complex underlying table structure.

Views are also a critical security mechanism. Instead of granting a user direct access to your base tables, you can grant them access to a view that only exposes the specific columns and rows they are permitted to see. This ensures that users cannot access sensitive data, like salaries or personal information, that might be present in the underlying tables. Views do not store data themselves; they are simply a window into the data stored in the base tables.

Understanding Temporary Objects: Temp Tables and Table Variables

During complex data processing, developers often need a temporary place to store intermediate result sets. SQL Server provides two primary tools for this: temporary tables and table variables. The 70-762 Exam requires you to know the difference between them and when to use each. A temporary table, created with CREATE TABLE #TableName, is a physical table that is created in the tempdb database. It behaves much like a permanent table; you can create indexes and statistics on it, and it is visible to nested stored procedures.

A table variable, declared with DECLARE @TableName TABLE, is a variable that stores a set of rows. It also exists in tempdb but has a more limited scope and functionality. You cannot create non-clustered indexes on a table variable (though you can have a primary key), and it is not visible to nested stored procedures. Generally, for small, simple data sets, table variables are preferred for their lower overhead, while for larger, more complex intermediate sets where indexing is needed, temporary tables are the better choice.

Key Design Principles for a Relational Database

A well-designed relational database is built on a foundation of established principles. The 70-762 Exam would expect a candidate to have a firm grasp of these principles, particularly normalization. Normalization is the process of organizing the columns and tables in a database to minimize data redundancy. The goal is to ensure that each piece of data is stored in only one place. This prevents data anomalies that can occur when you have to update the same piece of information in multiple locations.

The process involves following a series of normal forms, with the most common being the first three (1NF, 2NF, 3NF). Following these forms helps you to create a database with high data integrity. Another key principle is the use of primary keys to uniquely identify each row in a table and foreign keys to create and enforce relationships between tables. A solid understanding of these design principles is what separates a database developer from someone who simply writes queries.

Writing Advanced SELECT Statements

The ability to retrieve data efficiently and accurately is the most fundamental skill for a database developer. The 70-762 Exam goes far beyond basic SELECT statements, requiring a deep understanding of advanced query-writing techniques. This involves mastering all the clauses of a SELECT statement, including complex WHERE conditions to filter data, GROUP BY and HAVING clauses to aggregate and filter grouped data, and ORDER BY to sort the final result set.

A developer must be proficient in using a wide array of built-in functions for manipulating data within a query. This includes string functions (like LEFT, RIGHT, SUBSTRING), date functions (like DATEDIFF, DATEADD), and conversion functions (like CAST, CONVERT). Writing clean, readable, and efficient T-SQL code is a craft that is developed through practice, and it is a core competency that the 70-762 Exam was designed to measure.

Using Joins, Subqueries, and the APPLY Operator

Data in a normalized relational database is spread across multiple tables. To get a complete picture, you must be able to combine this data in your queries. The 70-762 Exam places a heavy emphasis on these skills. The most common way to combine tables is with the JOIN operator. You must be an expert in the different types of joins: INNER JOIN (to get matching rows), LEFT OUTER JOIN (to get all rows from the left table and matching from the right), RIGHT OUTER JOIN, and FULL OUTER JOIN.

Subqueries, which are queries nested inside another query, provide another powerful way to filter or retrieve data based on a result set. A more advanced operator is APPLY, which comes in CROSS APPLY and OUTER APPLY forms. The APPLY operator allows you to invoke a table-valued function for each row of an outer table, which is a powerful technique that is not possible with a standard JOIN.

Working with Common Table Expressions (CTEs)

As queries become more complex, they can become difficult to read and maintain. Common Table Expressions, or CTEs, are a feature designed to address this problem. A deep understanding of CTEs is essential for writing modern, readable T-SQL and was a key topic for the 70-762 Exam. A CTE, defined using a WITH clause, allows you to create a named, temporary result set that you can then reference within the main SELECT, INSERT, UPDATE, or DELETE statement.

CTEs make complex queries much easier to understand by breaking them down into logical, readable steps. Instead of nesting multiple subqueries, you can define a series of CTEs, with each one building upon the previous one, and then join them together in a simple final query. CTEs are also the only way to perform recursive queries in SQL Server, which are necessary for working with hierarchical data like organizational charts or bills of materials.

The Power of Windowing Functions

Windowing functions are one of the most powerful features in modern T-SQL, and they are a major topic for the 70-762 Exam. These functions allow you to perform calculations across a set of rows that are related to the current row. Unlike aggregate functions, which collapse the rows into a single result, windowing functions return a value for every single row. They operate on a "window" of data defined by an OVER() clause.

This clause allows you to partition the data into groups and order the data within those groups. There are several types of windowing functions. Ranking functions like ROW_NUMBER(), RANK(), and DENSE_RANK() are used to assign a rank to each row. Aggregate window functions like SUM() OVER() or AVG() OVER() can be used to calculate running totals or moving averages. Analytic functions like LAG() and LEAD() allow you to access data from previous or subsequent rows, which is incredibly useful for trend analysis.

Implementing Error Handling with TRY…CATCH

In any robust application, it is not enough to write code that works when everything goes right; you must also handle situations where things go wrong. For database development, this means implementing solid error handling. The 70-762 Exam requires proficiency in using the TRY...CATCH construct in T-SQL. This is the standard structured exception handling mechanism in SQL Server.

You place the T-SQL code that you want to execute inside a BEGIN TRY...END TRY block. If an error occurs during the execution of that code, control is immediately passed to a BEGIN CATCH...END CATCH block. Inside the CATCH block, you can write code to handle the error. This could involve logging the error details to a table, sending an alert, or attempting to clean up the failed operation. Using TRY...CATCH is essential for writing reliable and resilient stored procedures and other T-SQL batches.

Managing Transactions and Concurrency

A database must be able to handle multiple users accessing and modifying data at the same time. This is known as concurrency. Managing this concurrency to ensure data consistency is the job of transactions. The 70-762 Exam tests your understanding of how to use transactions in your T-SQL code. A transaction is a single, logical unit of work that may consist of one or more statements. A transaction must be atomic, meaning either all of its statements succeed, or none of them do.

You control transactions using the BEGIN TRANSACTION, COMMIT TRANSACTION, and ROLLBACK TRANSACTION statements. You start a unit of work with BEGIN TRANSACTION. If all the statements within it complete successfully, you make the changes permanent with COMMIT TRANSACTION. If an error occurs, you use ROLLBACK TRANSACTION to undo all the changes made since the transaction began. Proper use of transactions is fundamental to maintaining data integrity in a multi-user environment.

Modifying Data with INSERT, UPDATE, DELETE, and MERGE

Besides retrieving data, a database developer must be an expert in modifying it. The 70-762 Exam covers the full range of data manipulation language (DML) statements. The INSERT statement is used to add new rows to a table. The UPDATE statement is used to modify existing rows. The DELETE statement is used to remove rows. It is critically important to always use a WHERE clause with your UPDATE and DELETE statements to avoid accidentally modifying every row in the table.

A more advanced DML statement is MERGE. The MERGE statement allows you to perform INSERT, UPDATE, and DELETE operations on a target table from a source table in a single, atomic statement. It is extremely useful for synchronizing two tables, a common task in data warehousing and data integration scenarios. The MERGE statement is more efficient and easier to write than implementing the same logic with separate INSERT, UPDATE, and DELETE statements.

Combining Datasets with UNION and INTERSECT

There are often situations where you need to combine the result sets of two or more separate queries. T-SQL provides set operators for this purpose, and you would need to know them for the 70-762 Exam. The most common set operator is UNION (or UNION ALL). The UNION operator combines the rows from multiple SELECT statements into a single result set. The queries being combined must have the same number of columns with compatible data types. UNION automatically removes duplicate rows, while UNION ALL includes all rows and is therefore more performant.

Two other useful set operators are INTERSECT and EXCEPT. INTERSECT returns only the rows that appear in both of the result sets. EXCEPT returns the rows from the first result set that do not appear in the second result set. These operators are powerful tools for comparing datasets and finding commonalities or differences between them.

Introduction to Stored Procedures

A stored procedure is a pre-compiled collection of one or more Transact-SQL statements that is stored in the database. Stored procedures are a fundamental building block of any database application, and they are a major topic in the 70-762 Exam. Instead of having applications send raw SQL queries to the database, you encapsulate the logic into a stored procedure. The application then simply executes the procedure.

This approach has numerous benefits. It improves performance, as the execution plan for the procedure can be cached and reused. It enhances security, as you can grant a user permission to execute the procedure without granting them direct access to the underlying tables. It also promotes code reuse and modularity, as a single stored procedure can be called by multiple applications, ensuring consistent business logic. A well-written stored procedure is the cornerstone of a robust and secure database back-end.

Designing Parameterized and Modular Stored Procedures

To be truly useful, stored procedures must be flexible. This is achieved through the use of parameters. The 70-762 Exam requires you to be proficient in creating and using parameterized stored procedures. Parameters allow you to pass values into a stored procedure when it is called. For example, instead of writing a procedure that always retrieves the same customer, you would create a parameter for the customer ID. The calling application can then pass in any customer ID to retrieve the details for that specific customer.

Good design also means creating modular procedures. Instead of writing one giant, monolithic procedure that does everything, it is better to break down the logic into smaller, single-purpose procedures. For example, one procedure might handle creating a new customer, while another handles updating an existing customer's address. This makes the code easier to read, test, and maintain.

The Role of User-Defined Functions (UDFs)

A User-Defined Function (UDF) is another type of programmability object that allows you to encapsulate reusable logic. An understanding of UDFs, and particularly their differences from stored procedures, is a key part of the 70-762 Exam. A UDF is a routine that accepts input parameters and returns a value. This returned value can be either a single scalar value (like a number or a string) or a table.

The key feature of UDFs is that they can be used directly within a SQL query. For example, you could create a scalar UDF that calculates a customer's age based on their birthdate. You could then use this function directly in the SELECT list or WHERE clause of a query, just like a built-in function. This can simplify complex queries and promote code reuse for common calculations.

Understanding the Performance Impact of UDFs

While UDFs are very convenient, they can also be a significant source of performance problems if not used carefully. The 70-762 Exam would expect a developer to be aware of these performance implications. Scalar UDFs, in particular, can be very detrimental to query performance. When a scalar UDF is used in a query, it is often executed once for every single row in the result set. This row-by-row execution prevents the query optimizer from creating an efficient, parallel execution plan.

This is often referred to as "row-by-agonizing-row" processing. A query that runs in seconds without a UDF can take minutes or even hours with one. A better alternative in many cases is an inline table-valued function (iTVF). An iTVF is essentially a parameterized view, and the query optimizer is able to expand its logic into the main query and create a much more efficient execution plan. A skilled developer knows when to use a UDF and when to seek a more performant alternative.

Implementing DML Triggers for Auditing and Business Rules

A trigger is a special type of stored procedure that automatically executes in response to a specific event in the database. The 70-762 Exam covers the two main types of triggers, starting with DML triggers. A DML (Data Manipulation Language) trigger fires in response to an INSERT, UPDATE, or DELETE statement on a specific table. Triggers are powerful tools for enforcing complex business rules and for auditing data changes.

For example, you could create an AFTER UPDATE trigger on a product price table. Whenever a price is updated, the trigger could automatically insert a record into an audit table, logging the old price, the new price, the user who made the change, and the date and time. This creates an unchangeable audit trail. Triggers should be used with caution, as they can add overhead to your data modification statements and can be difficult to debug if they become too complex.

Understanding DDL Triggers for Schema Change Control

The second type of trigger, which you would need to be familiar with for the 70-762 Exam, is the DDL (Data Definition Language) trigger. Unlike DML triggers, which respond to data changes, DDL triggers fire in response to schema changes. They execute when statements like CREATE TABLE, ALTER TABLE, DROP INDEX, or CREATE PROCEDURE are run.

DDL triggers are typically used by database administrators to enforce development standards or to audit changes to the database structure. For example, you could create a DDL trigger that prevents anyone from dropping a table from the database. Or, you could create a trigger that logs every ALTER TABLE or CREATE PROCEDURE event to a special audit table. This provides a way to track and control all structural changes made to the database, which is particularly important in a regulated or tightly controlled environment.

Comparing Triggers to Constraints

Both triggers and constraints can be used to enforce data integrity and business rules. A key part of the 70-762 Exam is knowing which tool to use for a given situation. Constraints (like PRIMARY KEY, FOREIGN KEY, CHECK, UNIQUE) are the preferred method for enforcing declarative data integrity. They are generally simpler to implement and are highly optimized by the SQL Server engine, making them much more performant than triggers.

You should always use a constraint if it can meet your requirement. For example, to ensure that a Quantity column is always greater than zero, a CHECK constraint is the best choice. You would only use a DML trigger when the business rule is too complex to be implemented with a constraint. For example, if a rule requires you to query another table to validate an entry, you would have to use a trigger, as a constraint cannot do this.

Ensuring Data Integrity with Constraints

Data integrity refers to the accuracy, consistency, and reliability of the data stored in a database. Ensuring data integrity is a primary responsibility of a database developer, and it is a fundamental topic for the 70-762 Exam. The primary mechanism for enforcing data integrity in SQL Server is through the use of constraints. A constraint is a rule that is applied to a column or a table to restrict the type of data that can be entered.

When you define a constraint, you are telling the database engine to automatically enforce a business rule. If a user or an application tries to insert or update data in a way that violates the constraint, the database will reject the operation and return an error. This is a much more reliable way to enforce rules than trying to code them into every application that accesses the database. Constraints ensure that the data remains valid, regardless of how it is entered.

Implementing Primary Key and Foreign Key Constraints

The two most important types of constraints for defining the structure and relationships in a relational database are the primary key and foreign key constraints. Mastery of these is non-negotiable for the 70-762 Exam. A PRIMARY KEY constraint is used to uniquely identify each row in a table. The column(s) defined as the primary key must contain unique values and cannot contain any null values. Every well-designed table should have a primary key.

A FOREIGN KEY constraint is used to create and enforce a link between the data in two tables. It is a key that points to the primary key in another table. This constraint ensures referential integrity. For example, you could place a foreign key on the CustomerID column in your SalesOrders table that points to the CustomerID primary key in your Customers table. This would make it impossible to create a sales order for a customer who does not exist in the Customers table.

Using UNIQUE, CHECK, and DEFAULT Constraints

Beyond primary and foreign keys, there are several other types of constraints that are important tools for a developer and are covered in the 70-762 Exam. A UNIQUE constraint ensures that all values in a column or a set of columns are unique. It is similar to a primary key, but it allows for one null value. You might use a UNIQUE constraint on an email address column to ensure that no two users have the same email.

A CHECK constraint is used to enforce a specific condition on the data in a column. For example, you could add a CHECK constraint to a salary column to ensure that the value is always greater than zero. A DEFAULT constraint is used to provide a default value for a column when no value is specified during an INSERT operation. For instance, you could set the DEFAULT for an OrderDate column to be the current date and time.

Introduction to XML Data in SQL Server

Modern applications often need to work with semi-structured data, and XML (eXtensible Markup Language) has been a popular format for this for many years. SQL Server has robust, built-in support for storing and querying XML data, and this functionality is a specific objective of the 70-762 Exam. You can store XML data natively using the XML data type. This is not just a simple text field; SQL Server stores the XML in an optimized, parsed format.

Storing XML data natively in the database allows you to keep it with the related relational data and to query it using the database engine. This can be more efficient than parsing large XML files in your application code. You can also create special XML indexes on columns of the XML data type to significantly speed up queries against the XML content.

Querying and Shaping XML with XQuery

To work with data stored in an XML data type column, you cannot use standard T-SQL directly on the XML content. Instead, you use a language called XQuery. Proficiency in the basics of XQuery is a requirement for the 70-762 Exam. XQuery is a standardized language for querying and manipulating XML data. SQL Server integrates XQuery through a set of special methods that can be used on the XML data type.

The .query() method is used to extract fragments of XML from a larger document. The .value() method is used to extract a single scalar value, like a number or a string, from the XML. The .exist() method is used to check for the existence of a particular node or value within the XML, which is useful in WHERE clauses. You can also use the .nodes() method to shred an XML document into a relational rowset, which you can then query with standard T-SQL.

Working with JSON Data in SQL Server 2016

While XML has been around for a while, JSON (JavaScript Object Notation) has become the de facto standard for data interchange in modern web and mobile applications. Recognizing this trend, Microsoft introduced native JSON support starting in SQL Server 2016. A key part of the 70-762 Exam is demonstrating your ability to work with this new data format. Unlike XML, there is no native JSON data type. Instead, you store JSON data in a standard NVARCHAR(MAX) column.

Even though it is stored as text, SQL Server provides a set of built-in functions that understand the JSON structure and allow you to parse and query it efficiently. This support allows you to easily store and manage data from modern applications without having to create a rigid, predefined schema for it. It provides a powerful bridge between the relational world and the more flexible, schema-on-read world of NoSQL and modern application development.

Using FOR JSON and OPENJSON for Data Interchange

The two most important built-in functions for working with JSON data, and key topics for the 70-762 Exam, are FOR JSON and OPENJSON. The FOR JSON clause is used to format the results of a standard T-SQL query as JSON text. You can add this clause to the end of any SELECT statement, and SQL Server will return the result set as a properly structured JSON string. This is extremely useful for creating APIs that need to serve data to web or mobile applications.

The OPENJSON function does the reverse. It is a table-valued function that takes a JSON string as input and shreds it into a relational rowset with rows and columns. This allows you to easily import JSON data sent from an application and insert it into your relational tables. Together, these two functions provide a complete and powerful mechanism for bi-directional data exchange between your SQL Server database and any application that uses the JSON format.

Understanding Query Execution Plans

When you submit a query to SQL Server, the first thing the database does is create an execution plan. This plan is the step-by-step roadmap that the query engine will follow to retrieve the requested data. For a database developer, the ability to read and understand execution plans is the most important skill for diagnosing and fixing performance problems. This skill is a core component of the knowledge required for the 70-762 Exam.

An execution plan shows which tables were accessed, how they were accessed (e.g., a table scan or an index seek), and how the data from different tables was joined together. You can view execution plans graphically in SQL Server Management Studio. By analyzing the plan, you can identify inefficient operations, such as a costly table scan on a large table, which might indicate the need for a new index.

Designing Effective Clustered and Nonclustered Indexes

Indexes are the single most important tool for improving query performance, and a deep understanding of them is essential for the 70-762 Exam. An index is a special data structure that allows the database to find rows in a table much more quickly than scanning the entire table. There are two main types of indexes. A clustered index determines the physical order of the data in a table. Because of this, a table can only have one clustered index.

A nonclustered index is a separate structure that contains a sorted list of key values and a pointer back to the corresponding data row in the main table. A table can have many nonclustered indexes. The art of indexing is to create the right indexes to support your most common and important queries. A good nonclustered index on the columns used in your WHERE clauses and JOIN conditions can change a query's performance from minutes to milliseconds.

Using Advanced Indexing Features

Beyond the basic clustered and nonclustered indexes, SQL Server offers several advanced indexing features that a developer should know for the 70-762 Exam. A covering index is a nonclustered index that includes all the columns needed to satisfy a specific query directly within its leaf level. This allows the query engine to get all the data it needs from the index itself, without ever having to look up the data in the main table, which is extremely efficient.

A filtered index is a nonclustered index that is created on a subset of the rows in a table. For example, you could create an index only on the "open" orders in a large sales order table. This makes the index smaller and more efficient to maintain. Another feature is the ability to include non-key columns in an index, which is another way to create a covering index without making the index key itself too large.

The Role of Statistics in Query Optimization

When the SQL Server query optimizer is deciding which execution plan to use for a query, it needs to be able to estimate how many rows will be returned by each step of the plan. It makes these estimations using a set of statistical information that it maintains about the distribution of data in your columns and indexes. These statistics are a critical, though often overlooked, aspect of query performance, and you should understand their role for the 70-762 Exam.

SQL Server automatically creates and updates these statistics. However, in some cases, the statistics can become out of date, especially after large data modifications. Out-of-date statistics can lead the optimizer to make poor choices and generate an inefficient execution plan. As a developer, you should know how to view the statistics and, in rare cases, manually update them to help the optimizer make the best possible decisions.

Introduction to In-Memory OLTP

Starting with SQL Server 2014 and enhanced in 2016, Microsoft introduced a powerful set of in-memory technologies designed for high-performance online transaction processing (OLTP). A conceptual understanding of these features is a topic on the 70-762 Exam. In-Memory OLTP, also known as Hekaton, allows you to create memory-optimized tables. These tables reside entirely in memory and have a lock-free and latch-free design, which eliminates many of the traditional bottlenecks associated with high-concurrency workloads.

To interact with these tables with the highest possible performance, you can create natively compiled stored procedures. These are special T-SQL stored procedures that are compiled down to native machine code, rather than being interpreted. The combination of memory-optimized tables and natively compiled procedures can provide dramatic performance improvements for specific, high-throughput transactional workloads, such as an e-commerce order ingestion system.

Leveraging Columnstore Indexes for Analytics

While In-Memory OLTP is designed for transactional performance, Columnstore indexes are designed for analytical query performance. This technology is another key innovation covered in the 70-762 Exam. A columnstore index stores data in a columnar format, rather than the traditional row-based format. As we've discussed with other columnar technologies, this is extremely efficient for analytical queries that aggregate data from a few columns in a very large table.

Columnstore indexes also use very high levels of compression, which reduces the memory and I/O footprint of your data. In SQL Server 2016, you can create a clustered columnstore index on a table, making the entire table columnar, which is ideal for data warehouses. You can also create a nonclustered columnstore index on a traditional rowstore table, which allows you to have a single table that can perform well for both transactional and analytical queries, a concept known as real-time operational analytics.

Monitoring and Troubleshooting Performance

A developer's job is not done once the code is written. They must also be able to monitor the performance of their queries and troubleshoot issues when they arise. The 70-762 Exam would expect you to be familiar with the basic tools for this. SQL Server provides a rich set of Dynamic Management Views (DMVs) that give you real-time insight into the health and performance of the server. You can query DMVs to find the most expensive queries currently running or to identify missing indexes.

SQL Server 2016 also introduced the Query Store. This feature acts like a flight data recorder for your database. It automatically captures a history of all the queries that have been run, their execution plans, and their performance statistics. This is an incredibly powerful tool for identifying queries that have regressed in performance over time and for forcing the use of a known good execution plan.

A Comprehensive Review of 70-762 Exam Topics

As you prepare to apply the skills covered by the 70-762 Exam, it is helpful to perform a final review. Start with the foundations of database design: tables, data types, views, and normalization. Ensure you have a mastery of T-SQL, from complex joins and CTEs to windowing functions and error handling. Revisit the programmability objects, understanding the use cases and performance characteristics of stored procedures, UDFs, and triggers.

Solidify your knowledge of data integrity through constraints and your ability to work with both XML and JSON data. Finally, focus on performance. Make sure you can read an execution plan, understand the role of indexes and statistics, and can explain the benefits of the modern in-memory technologies like In-Memory OLTP and Columnstore indexes. A comprehensive grasp of these topics is what defines a skilled and effective SQL Server database developer.

Final Tips

While you can no longer take the 70-762 Exam, the skills it represents are more in demand than ever. The best way to master these skills is through continuous practice and learning. Set up a developer edition of SQL Server on your own machine and work through real-world problems. Build your own database projects. Practice writing complex queries and optimizing them by analyzing their execution plans.

Contribute to open-source projects or answer questions on community forums. This will expose you to a wide variety of different problems and solutions. Stay current with the latest features being introduced in new versions of SQL Server and Azure SQL Database. The world of data is constantly evolving, and a commitment to lifelong learning is the key to a long and successful career as a database professional.

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