98-364: Database Fundamentals certification video training course by prepaway along with practice test questions and answers, study guide and exam dumps provides the ultimate training package to help you pass.

MTA 98-364 Exam Prep: Database Fundamentals Training

Introduction to the Course

The MTA 98-364 Database Fundamentals exam is designed to introduce candidates to the foundational concepts of databases. This preparation course will guide learners through the essential topics required for success in the certification exam and practical use in real-world database environments. The structure of the course is divided into multiple parts to make learning easier and progressive.

Course Overview

This course offers a structured pathway to understanding database fundamentals. It explains how databases function, how data is stored, and how data can be queried, manipulated, and maintained. By working through each section, students will gain the knowledge needed not only to pass the certification but also to apply database concepts in academic or professional projects.

Why This Course Matters

Databases are at the center of most modern applications, businesses, and technologies. From banking systems to online shopping platforms, every digital service depends on reliable data storage and retrieval. By completing this course, learners gain both the technical foundation and practical skills that are crucial in the field of information technology.

Structure of the Course

The course is divided into five major parts. Each part focuses on specific areas of database fundamentals, gradually building knowledge and skills. Students will begin with basic concepts and progress toward more advanced applications. The modular structure ensures that each section contributes to exam readiness while also making the learner confident in practical scenarios.

What You Will Learn

Learners will gain the ability to define database structures, understand core relational concepts, write basic queries, and manage database objects. By the end of the course, they will be familiar with concepts such as normalization, security principles, and working with Transact-SQL.

Who This Course Is For

This course is for anyone who wants to begin their journey into databases. It is especially suited for individuals who are preparing for the MTA 98-364 certification. Students, entry-level IT professionals, and career changers who wish to enter the data field will benefit most from this training. It is also a valuable resource for anyone who wants to understand how databases work and why they are essential in modern computing.

Requirements of the Course

There are no strict prerequisites for taking this course. A basic understanding of computers and an interest in technology will be enough. However, familiarity with simple data concepts, spreadsheets, or basic programming will help learners grasp the topics more quickly. Access to a Windows environment and Microsoft SQL Server will enhance practice opportunities.

Course Modules Overview

The training program is built around the core objectives of the exam. Each module develops key knowledge areas step by step. The modules are designed to encourage comprehension, application, and preparation for real-world use as well as the exam itself.

Module One: Understanding Core Database Concepts

This module explains the meaning of a database and the role it plays in computing. Students will learn about different types of databases and why relational databases are the most commonly used. Concepts like tables, rows, and columns will be introduced with practical explanations.

Module Two: Creating Database Objects

This module teaches how to create tables, define columns, and assign data types. It also covers primary keys, foreign keys, and indexes. Learners will explore how objects like views and stored procedures contribute to efficient database operations.

Module Three: Manipulating Data

Here, students will learn how to insert, update, and delete data. Query writing will be introduced through SQL commands. The focus will be on practical examples that help learners understand how to interact with data efficiently.

Module Four: Understanding Data Storage

This part covers how data is stored inside a database system. Students will study files, pages, and indexes. Concepts like normalization and data integrity will be explained with real-world relevance.

Module Five: Administering a Database

This module explains how to secure databases, back up data, and manage user access. Learners will be introduced to the principles of database administration, including performance monitoring and security practices.

Course Descriptions in Detail

This course is not limited to theoretical learning. It combines explanations, examples, and exercises to make the learning experience practical. The goal is not only to prepare students for the MTA exam but also to equip them with skills they can apply in real work environments. By following the structure and practicing regularly, learners will be confident in handling databases independently.

Importance of Relational Databases

Relational databases are the industry standard. They allow data to be stored in organized structures, making it easier to maintain relationships and retrieve meaningful information. This course ensures that learners develop a strong grasp of how relational databases function and why they remain relevant.

Building Practical Skills

The course is structured to help learners practice hands-on activities. Writing SQL statements, creating tables, and managing users are all included in the practical tasks. Each concept is connected with examples that reflect workplace scenarios.

Exam Preparation Strategy

The exam tests understanding rather than rote memorization. This course prepares learners by building confidence in practical problem-solving. Each topic is taught in a way that directly links to the objectives of the certification. Regular practice questions and mock tests are recommended to strengthen exam readiness.

Who Should Avoid This Course

This course is not aimed at advanced professionals who already work with complex databases daily. While it offers value for review, it is primarily designed for beginners and those with limited exposure to database fundamentals.

Why Choose This Preparation Path

This preparation path ensures clarity, simplicity, and thoroughness. Many learners find database concepts confusing at first, but this course presents them in a way that is accessible and easy to digest. The use of short paragraphs and step-by-step teaching allows even complete beginners to keep pace.

Career Benefits After Completion

Earning the MTA 98-364 certification signals to employers that a learner has a solid understanding of database concepts. It opens doors to entry-level positions in database administration, data analysis, and software development. The skills also act as a foundation for higher certifications and advanced studies.

Long-Term Learning Path

This course also serves as a stepping stone for further certifications. After mastering the fundamentals, learners can progress toward Microsoft certifications such as Azure Data Fundamentals or Database Administrator Associate. The knowledge gained here remains valuable across multiple paths.

Introduction to Database Objects

Databases rely on structured objects to manage data efficiently. Objects define the way information is stored, retrieved, and manipulated. Understanding objects is essential for creating solid database structures and passing the MTA 98-364 exam. This section introduces tables, keys, views, stored procedures, and other objects that form the building blocks of relational databases.

Tables as the Foundation of Databases

Tables are the core storage mechanism in a relational database. A table consists of rows and columns where each row represents a record and each column represents a data field. Without tables, relational databases would not exist because data must be structured to be useful.
Tables are designed with clear rules to ensure consistency. Each column is given a name and a data type that restricts what kind of values it can accept. Rows store the actual values that users input. This combination allows databases to store large volumes of information while keeping it organized.

Understanding Data Types

Data types define the kind of information a column can hold. Choosing the right data type is crucial because it affects storage efficiency and data integrity. Common data types include integers, decimals, dates, and strings. If a column must store numbers only, assigning it as a string would lead to problems.
Proper data typing also prevents errors in calculations and comparisons. For example, comparing dates stored as text can lead to wrong results, while storing them as date types ensures accuracy. Learners must practice identifying the most suitable data type for each column.

Primary Keys and Uniqueness

A primary key is a unique identifier for each row in a table. It ensures that no two rows can have the same key value. Primary keys are critical for maintaining data integrity and making sure records are not duplicated.
When creating a table, one or more columns may be designated as the primary key. In most cases, a single column such as an ID number is enough. Sometimes, multiple columns are combined to create a composite primary key. This enforces uniqueness across a combination of values.

Foreign Keys and Relationships

Foreign keys establish relationships between tables. A foreign key in one table refers to the primary key of another table. This creates a link that allows databases to maintain structured and meaningful connections.
For example, a table of orders may contain a foreign key that refers to the primary key in a customer table. This ensures every order is associated with a valid customer. Without foreign keys, relational databases would lose the ability to connect different sets of information logically.

Indexes for Faster Access

Indexes are special objects that improve the speed of data retrieval. When a table grows large, searching through rows becomes slower. An index works like a book’s index, allowing the system to find data quickly without scanning every row.
While indexes are useful, they must be used carefully. Too many indexes can slow down insert or update operations because the system must maintain each index whenever data changes. Learners must balance performance by creating indexes only where necessary.

Views for Simplified Access

Views are virtual tables that show data from one or more tables in a simplified form. They do not store data themselves but act as a saved query that can be reused. Views make it easier to present complex information in a user-friendly format.
For example, a view may combine customer and order data into a single display. Instead of writing a complicated query each time, users can select from the view directly. This saves time and reduces errors while maintaining security by exposing only necessary columns.

Stored Procedures and Automation

Stored procedures are sets of SQL statements that are saved and reused. They are useful for automating common tasks such as inserting records or generating reports. By creating stored procedures, developers ensure consistency in operations while reducing the need to rewrite SQL code repeatedly.
They also improve security by limiting direct access to underlying tables. Users can execute a stored procedure without having permission to manipulate tables directly. This makes databases more controlled and less prone to mistakes or unauthorized changes.

Functions and Reusability

Functions are similar to stored procedures but are designed to return a single value. They allow developers to create reusable logic such as calculating totals or formatting dates. Functions are often used within queries to simplify code.
For example, a function may calculate sales tax for a given amount. Instead of rewriting the formula every time, the function can be called whenever needed. This makes SQL more efficient and easier to maintain.

Triggers and Automatic Actions

Triggers are special objects that execute automatically when a specific event occurs in a table. They can respond to actions such as insert, update, or delete. Triggers are often used to enforce business rules or maintain audit trails.
For example, if a record is deleted from an orders table, a trigger may log the action into an audit table. This ensures accountability and prevents unauthorized changes from going unnoticed. Triggers must be designed carefully to avoid unintended consequences like infinite loops.

Introduction to SQL

Structured Query Language, or SQL, is the standard language used to interact with relational databases. It allows users to define structures, insert data, retrieve information, and manage permissions. SQL is divided into several categories including Data Definition Language, Data Manipulation Language, and Data Control Language.
Understanding SQL is vital for passing the exam and applying knowledge in real projects. It is not only a technical skill but also a universal language of data that professionals across industries rely on daily.

Writing Basic SQL Queries

Queries are commands that retrieve specific data from tables. A query begins with the SELECT statement, followed by the columns to display and the table to search. Conditions can be added with the WHERE clause to filter results.
For example, retrieving the names of customers from a table involves writing SELECT Name FROM Customers. Adding a condition such as WHERE City = 'New York' narrows results to customers in that city. Practicing simple queries helps learners develop confidence in navigating data.

Using Joins to Combine Tables

Joins allow data from multiple tables to be retrieved in a single query. Since relational databases are designed with separate but related tables, joins are necessary to bring information together.
An INNER JOIN retrieves rows that have matching values in both tables. A LEFT JOIN retrieves all rows from one table and matching rows from another. These variations give flexibility depending on the data needed. Mastering joins is essential for real-world work and exam readiness.

Aggregating Data with SQL

Aggregation functions summarize data by calculating totals, averages, counts, and more. Functions like SUM, AVG, COUNT, MIN, and MAX allow meaningful insights from large datasets. They are often combined with the GROUP BY clause to organize results.
For example, finding the total sales per customer involves grouping rows by customer and applying the SUM function to sales amounts. This transforms raw data into useful information for analysis and decision-making.

Modifying Data with SQL

SQL also allows changes to existing data. The INSERT statement adds new rows, UPDATE modifies existing rows, and DELETE removes rows. These commands form the basis of Data Manipulation Language.
Practicing modifications is important because small mistakes can lead to large consequences. For instance, forgetting a WHERE clause in an update may change every row in a table instead of just the intended ones. Understanding how to use these commands safely is critical.

Enforcing Data Integrity

Data integrity ensures that information in a database remains accurate and consistent. Keys, constraints, and relationships are mechanisms that enforce integrity. Primary keys prevent duplicate records, foreign keys ensure valid relationships, and constraints restrict values to acceptable ranges.
For example, a constraint may prevent negative values in a quantity column. This protects the database from invalid data and supports reliable analysis. Integrity mechanisms form the backbone of professional databases.

Introduction to Normalization

Normalization is the process of organizing data to eliminate redundancy and improve efficiency. It involves dividing data into related tables and defining relationships between them. The goal is to avoid storing the same information multiple times.
For example, storing customer addresses in both the customer and order tables leads to duplication. Normalization ensures addresses are stored once in the customer table and referenced through relationships. This reduces errors and makes updates easier.

Practical Applications of Objects and SQL

The concepts of objects and SQL commands are not limited to exams. They apply directly to workplace tasks such as managing employee records, processing sales transactions, and maintaining customer data. By practicing with real-world examples, learners can see how databases solve common business problems.
Employers value professionals who not only understand theory but also apply it effectively. Demonstrating SQL proficiency and knowledge of objects adds credibility in job interviews and daily responsibilities.

Introduction to Data Storage Concepts

Understanding how data is physically and logically stored is an important aspect of database fundamentals. Storage structures determine how efficiently data can be retrieved, how much space is used, and how quickly queries execute. Without a clear understanding of storage, database performance and reliability cannot be guaranteed. For exam preparation and real-world use, candidates must grasp both the logical representation of storage in tables and the underlying physical organization inside the database engine.

Logical Storage of Data

From a user perspective, data is stored in tables consisting of rows and columns. However, internally, the database engine manages storage in smaller units such as pages and extents. Each page usually contains a fixed size of data, and multiple pages are grouped into extents. This structure allows the system to organize and retrieve information efficiently. Learners preparing for the exam should understand that while they interact with tables and records, the database engine continuously manages the lower-level details.

Physical Storage of Data

Physically, data is stored on disk drives. The database engine translates logical operations such as inserting a record into actual disk operations. Modern systems also use memory caching to reduce disk operations and improve performance. The exam does not expect deep knowledge of hardware mechanics, but understanding that disk operations are slower than memory operations helps learners see why optimization and indexing matter.

Role of Indexes in Storage Efficiency

Indexes are essential in optimizing how data is accessed. An index acts like a roadmap that allows the system to jump directly to the relevant location rather than scanning an entire table. Without indexes, queries on large datasets would take much longer. However, indexes also consume storage space and slow down updates because they must be maintained alongside the data. For effective exam preparation, learners must recognize the trade-off between fast retrieval and the overhead of maintaining indexes.

Clustered and Nonclustered Indexes

Clustered indexes define the physical order of data in a table. A table can only have one clustered index because the data itself is stored in that order. Nonclustered indexes, on the other hand, are separate structures that point back to the table’s data. Understanding the difference between these two types is critical for both exam questions and practical use. Clustered indexes are ideal for queries that return ranges of data, while nonclustered indexes are useful for quick lookups.

Case Study on Indexing Performance

Imagine a company with a database storing millions of sales records. A manager often needs to view sales figures by date. If the sales table is indexed on the date column, the query will quickly locate the relevant rows. Without an index, the database would scan every row, wasting time and resources. This example demonstrates why proper indexing strategy is essential in designing efficient databases.

Data Redundancy and Its Problems

Redundancy occurs when the same piece of information is stored in multiple places. For example, storing customer addresses in both the customer and orders table creates unnecessary duplication. Redundancy increases storage usage and makes updates difficult. If a customer changes their address, multiple tables must be updated, which risks inconsistency. Exam questions often test understanding of redundancy and its prevention.

Introduction to Normalization

Normalization is a method used to minimize redundancy and improve efficiency. It organizes data into related tables and enforces relationships through keys. The goal is to ensure that each piece of information is stored once and referenced wherever needed. Normalization is divided into forms, each with specific rules. Students should not memorize every detail but must understand the concept and purpose behind normalization.

First Normal Form

The first normal form requires that each column contain atomic values, meaning no multiple values in a single column. For example, instead of storing multiple phone numbers in one column, each phone number should be placed in a separate row. This rule ensures data is structured clearly and is easier to query. Exam questions often provide examples of tables that violate first normal form and ask learners to identify corrections.

Second Normal Form

The second normal form builds on the first by ensuring that all non-key attributes are fully dependent on the primary key. This prevents partial dependencies. In practice, this means if a table has a composite key, no column should depend on just part of the key. By enforcing this rule, redundancy is reduced and relationships are clarified. Students should be able to identify when a table violates this principle.

Third Normal Form

The third normal form requires that no column depends on another non-key column. In other words, all non-key attributes must depend only on the primary key. This prevents transitive dependencies. For example, if a table contains customer information along with city and postal code, and the postal code determines the city, this violates the third normal form. The solution would be to separate city and postal code into a related table.

Practical Example of Normalization

Consider a university database storing student information, courses, and instructors in a single table. This design results in redundancy because the same instructor details are repeated for each student in their class. By normalizing, the system splits data into separate tables: one for students, one for courses, and one for instructors. Relationships are maintained with keys. This reduces redundancy, ensures data consistency, and makes maintenance easier.

Denormalization in Practice

While normalization improves consistency, sometimes performance requires denormalization. Denormalization intentionally introduces redundancy to speed up queries. For example, a reporting database may store pre-joined data to avoid complex joins in queries. The exam may touch on this concept to test awareness that database design involves balancing performance and normalization principles.

Introduction to Database Security

Security is a vital part of database management. Without security, sensitive data such as customer records or financial transactions can be exposed. Database security involves controlling access, managing permissions, and protecting against threats. For exam preparation, learners must understand basic principles of security including authentication, authorization, and encryption.

Authentication and Authorization

Authentication confirms the identity of a user, while authorization determines what actions that user can perform. For example, an employee may log into the database with a username and password for authentication. Authorization then decides whether they can view, insert, or delete records. Understanding this distinction is important for both exam questions and real-world practices.

Database Roles and Permissions

Permissions in a database can be granted directly to users or assigned through roles. Roles simplify management by grouping permissions and assigning them collectively. For instance, a database administrator may have permissions to create and delete tables, while a data analyst may only have permission to run queries. Roles help ensure that users only access the data necessary for their responsibilities.

Encryption of Data

Encryption protects data by converting it into a format that is unreadable without a key. Databases may use encryption for data at rest, stored on disk, or for data in transit, moving between applications and the database. For example, encrypting customer credit card numbers ensures that even if unauthorized access occurs, the data remains protected. The exam may not require deep technical knowledge but expects awareness of encryption’s role in security.

Backup and Recovery Strategies

Security is not only about preventing unauthorized access but also about protecting against data loss. Backup strategies ensure that data can be restored in case of system failure. Full backups copy the entire database, while differential and transaction log backups capture changes. Recovery strategies define how these backups are used to restore operations. Understanding backup types is crucial for exam preparation and practical database management.

Case Study on Security Practices

A healthcare organization must protect patient data to comply with regulations. This involves assigning strict permissions, encrypting sensitive information, and maintaining regular backups. A real-world scenario like this highlights why database security is not optional but an essential part of operations. Exam candidates should connect theoretical security principles with practical applications.

Monitoring and Performance Tools

Databases provide tools to monitor performance, detect problems, and prevent misuse. Logging and auditing features track user actions, while performance monitors help identify slow queries. Administrators use these tools to maintain database health. The exam may test awareness of these features to ensure learners understand that databases require ongoing management beyond just design.

Introduction to Advanced SQL

By this stage of learning, students already understand the basics of SQL. Now the focus shifts to advanced SQL topics that are tested in the exam and widely used in real-world environments. Advanced SQL involves complex queries, subqueries, transactions, and set operations. It also explores how SQL can manage large volumes of data efficiently. Mastery of these concepts ensures learners are prepared for scenarios that go beyond the fundamentals.

Subqueries in SQL

A subquery is a query within another query. It is used when the result of one query is required to complete another. Subqueries may appear in the WHERE clause, FROM clause, or SELECT clause. For example, to find students who scored above the average, one query calculates the average score and another selects students with scores higher than that value. Subqueries provide flexibility and make SQL powerful for solving complex problems.

Correlated Subqueries

Unlike simple subqueries that run once, correlated subqueries run for each row being evaluated. They reference columns from the outer query, making them dependent on it. For instance, finding employees whose salary is greater than the average salary of their department requires a correlated subquery. This concept is slightly more advanced but very practical for detailed analysis.

Common Table Expressions

A common table expression or CTE is a temporary result set that can be referenced within a query. CTEs make complex queries easier to read and maintain. They are especially useful for recursive queries such as finding hierarchical relationships in organizational charts. For exam preparation, learners should understand the syntax and benefits of using CTEs over deeply nested subqueries.

Set Operations in SQL

Set operations combine results from multiple queries. UNION merges results while removing duplicates, UNION ALL includes all rows, INTERSECT returns only matching rows, and EXCEPT returns rows from one query not found in another. These operations are powerful for data comparison tasks. A practical example would be comparing customers who purchased products in one year versus another. Understanding set operations expands the range of solutions possible with SQL.

Transactions and Their Importance

A transaction is a unit of work that must be completed fully or not at all. Transactions ensure consistency in databases when multiple operations are involved. For example, transferring money between bank accounts requires deducting from one account and adding to another. If one operation fails, both must be rolled back to prevent errors. Transactions are vital in maintaining reliability in business-critical systems.

ACID Properties of Transactions

Transactions follow four key properties known as ACID. Atomicity ensures all operations complete successfully or none at all. Consistency guarantees that the database remains valid after the transaction. Isolation ensures that concurrent transactions do not interfere with each other. Durability makes sure that once a transaction is committed, it remains permanent even if the system fails. These principles form the backbone of transactional integrity.

Implementing Transactions in SQL

Transactions in SQL are managed using commands such as BEGIN TRANSACTION, COMMIT, and ROLLBACK. For example, after starting a transaction, multiple insert or update statements can be executed. If everything works as expected, the COMMIT command saves the changes. If an error occurs, the ROLLBACK command restores the database to its previous state. Practicing transaction commands helps learners understand how to maintain integrity in complex scenarios.

Isolation Levels and Concurrency

When multiple users access a database simultaneously, concurrency issues may arise. Isolation levels define how transactions interact with each other. Common levels include Read Uncommitted, Read Committed, Repeatable Read, and Serializable. Each level balances performance with accuracy. Lower isolation levels allow faster performance but risk issues like dirty reads or phantom reads. Higher levels ensure accuracy but may reduce concurrency. Understanding these trade-offs is important for both the exam and practical use.

Case Study on Transaction Management

Consider an online shopping system where multiple users purchase products simultaneously. Transactions ensure that inventory is updated correctly and payments are processed without errors. Without transactions, it would be possible for two customers to buy the last available item at the same time, leading to data conflicts. This example highlights why transaction management is essential in real systems.

Database Administration Basics

Database administration involves managing and maintaining databases to ensure reliability, security, and performance. Administrators are responsible for creating databases, managing users, monitoring activity, and optimizing queries. While the MTA 98-364 exam does not require expert-level administration skills, learners must understand the basic responsibilities of a database administrator.

Creating and Managing Databases

Administrators begin by creating databases using SQL commands or graphical tools. This involves defining storage paths, assigning file groups, and setting initial sizes. Managing databases includes monitoring file growth, ensuring backups are scheduled, and maintaining availability. Students preparing for the exam should know that database creation is more than just adding tables; it involves configuring the environment for stability and scalability.

User Management and Security

One key responsibility of administration is user management. Administrators create user accounts, assign roles, and set permissions. Security principles dictate that users should only have access necessary for their role. For example, a sales employee may be able to view customer data but not delete it. Understanding how permissions work is essential for protecting data and ensuring compliance with policies.

Backup and Restore Operations

Backups are critical for preventing data loss. Full backups copy the entire database, while differential backups copy only changes since the last full backup. Transaction log backups capture ongoing changes for point-in-time recovery. Restoration involves applying backups to bring a database back online after a failure. Students should be able to explain the purpose of each backup type and when they are used.

Performance Tuning and Optimization

Performance tuning ensures that databases run efficiently even as data grows. Administrators analyze query execution plans to identify bottlenecks. Indexing strategies are adjusted to improve speed, and query rewriting may reduce complexity. Monitoring tools help detect issues such as slow queries or locking conflicts. Performance tuning is a continuous process and a major part of real-world database management.

Query Optimization Techniques

Optimizing queries is one of the most effective ways to improve performance. Techniques include selecting only necessary columns instead of using SELECT *, applying indexes to frequently searched columns, and avoiding unnecessary subqueries. Properly structured queries can make the difference between results in seconds or minutes. The exam may test knowledge of optimization strategies in scenarios involving large datasets.

Storage Management in Administration

As databases grow, managing storage becomes a key responsibility. Administrators monitor disk usage, allocate additional space, and configure automatic growth settings. Proper storage management prevents unexpected outages and ensures that queries can run without interruption. For exam preparation, learners should understand that storage planning is a proactive task rather than a reactive one.

Monitoring Database Health

Monitoring tools allow administrators to track performance, detect security issues, and predict potential failures. Logs provide details of system operations and user activity. Alerts can be configured to notify administrators when problems arise, such as low disk space or failed backups. Monitoring is essential for maintaining uptime and reliability. Learners must recognize that proactive monitoring is part of professional database management.

Case Study on Administration Challenges

A financial institution manages millions of transactions daily. Administrators must ensure backups are frequent, performance is optimized, and security policies are strictly enforced. When performance issues arise, administrators analyze queries and indexes to restore efficiency. This case illustrates the importance of database administration in mission-critical systems where even minor errors can have significant consequences.

Advanced Security Considerations

Beyond basic permissions, advanced security includes encryption, auditing, and compliance management. Encryption protects sensitive data, while auditing tracks user actions for accountability. Compliance management ensures databases meet legal and organizational requirements such as GDPR or HIPAA. While the exam covers security at a basic level, awareness of advanced practices strengthens practical understanding.

High Availability Concepts

High availability ensures that databases remain accessible even during failures. Techniques include database mirroring, replication, and clustering. These solutions reduce downtime and protect against hardware or software failures. While detailed configuration may be beyond exam scope, learners should understand the purpose and benefits of high availability.

Disaster Recovery Planning

Disaster recovery involves preparing for catastrophic failures such as hardware damage, natural disasters, or cyberattacks. Recovery strategies depend on backup frequency, redundancy, and recovery objectives. Organizations must balance costs with acceptable downtime. For the exam, learners should know that disaster recovery is an essential part of responsible database management.

Administration and Advanced SQL Concepts

explored advanced SQL including subqueries, CTEs, and set operations. It emphasized transactions and their role in maintaining integrity, then moved into database administration covering backups, performance, and security. Learners should now understand how advanced SQL features expand the power of queries and how administration ensures database reliability. These skills prepare students not only for the MTA 98-364 exam but also for entry-level roles in database support and management.

Prepaway's 98-364: Database Fundamentals video training course for passing certification exams is the only solution which you need.