What will you learn in SQL Essentials Training Course
Write fundamental SQL queries to retrieve, sort, filter, group, aggregate, and calculate data in Microsoft SQL Server Management Studio
Define and manipulate database objects using DDL commands: create/alter/drop tables, constraints, and views
Perform data operations with DML: insert, update, delete, truncate, and upsert via
INSERT…SELECTCombine data from multiple tables using self, inner, left, right, and cross joins
Program Overview
Module 1: DDL Commands
⏳ 1 hour
Topics: RDBMS concepts, normalization,
CREATE/ALTER/DROPtables, data types, and constraintsHands-on: Create and modify tables, add/remove primary & foreign keys, and define views
Module 2: DML Commands
⏳ 1 hour
Topics:
INSERT,UPDATE,DELETE,TRUNCATE, and basicSELECTwithWHERE, sorting, and filteringHands-on: Populate tables, modify existing data, and retrieve filtered datasets
Module 3: Retrieving Data from Multiple Tables
⏳ 45 minutes
Topics: Joins (self, inner, left, right, cross) to combine related table data
Hands-on: Write multi-table queries to produce consolidated result sets
Module 4: Inbuilt Functions & Grouping
⏳ 45 minutes
Topics: Aggregate functions (
SUM,AVG,COUNT),GROUP BY,HAVING, and scalar functions (string, date, conversion)Hands-on: Compute summary metrics and apply conditional filters on grouped data
Module 5: Advanced Database Objects
⏳ 45 minutes
Topics: Stored procedures, user-defined functions, and triggers for automated logic
Hands-on: Create and execute procedures/functions and implement triggers for data integrity
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Job Outlook
SQL Developer: $85,599 average salary — design and optimize database queries for applications
Data Analyst: $70,000–$100,000/year — extract insights and build reports using SQL across various industries
Database Administrator: $75,000–$110,000/year — manage, secure, and tune relational database environments
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Specification: SQL Essentials Training Course
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FAQs
- No prior Big Data experience required.
- Learn Hadoop architecture, HDFS, YARN, and MapReduce.
- Hands-on labs with Hive, Pig, and Spark for real-world analytics.
- Covers cluster navigation, file management, and resource allocation.
- Prepares learners for roles like Big Data Engineer or Hadoop Administrator.
- Implement MapReduce jobs for large-scale batch processing.
- Use Hive and Pig for ETL and analytical queries.
- Build Spark applications using RDDs, DataFrames, and Spark SQL.
- Execute simple structured streaming jobs for real-time data.
- Gain practical experience integrating batch and streaming workflows.
- Configure high availability NameNode setups.
- Implement Kerberos authentication for HDFS security.
- Use Ranger/Knox basics for access control.
- Monitor cluster and job performance using YARN UI and Ambari.
- Tune Spark executors and MapReduce jobs for optimized performance.
- Gain skills to become a Big Data Engineer or Hadoop Administrator.
- Build end-to-end data pipelines with ingestion, processing, and analytics.
- Hands-on experience with Spark, Hive, Pig, and Oozie workflows.
- Learn best practices for cluster management and data security.
- Prepare for high-paying enterprise-level Big Data roles ($100k–$170k/year).
- Automate daily data ingestion using Sqoop and Flume.
- Process datasets with Spark, Hive, and Pig.
- Monitor and tune cluster performance for batch and streaming jobs.
- Build a complete pipeline for clickstream or IoT data analytics.
- Produce a portfolio-ready project showcasing end-to-end Big Data skills.
