SQL for Analytics
By the end of this program, you’ll be proficient in SQL for managing, querying, and analyzing data and confident in ...
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Team SKETO
- Description
- Curriculum
- FAQ
- Announcement
The SQL for Analytics Program is crafted to provide a robust foundation in SQL and data handling, essential for analytical and data-driven roles. In this program, you’ll start by learning the fundamentals of databases, progressing through key SQL commands and concepts, and advancing to Python integration for enhanced data analysis capabilities.
What You’ll Master:
- Introduction to Databases and SQL Fundamentals
Build a strong foundation in SQL with an understanding of database structures, terminology, and practical applications of SQL in data analytics. - Setting Up MySQL
Install and configure MySQL Workbench and MySQL Server, giving you a practical environment to apply SQL queries and manage databases. - Core SQL Commands
Master essential SQL statements for effective data handling:- SELECT: Extract and analyze specific data sets.
- INSERT, UPDATE, DELETE: Modify database records with accuracy and efficiency.
- Data Integrity with SQL Constraints
Ensure the reliability and consistency of data by applying constraints, safeguarding data integrity within your tables. - SQL for Data Analysis
Gain analytical expertise through:- Aggregate Functions: Perform calculations on data sets to derive insights.
- Joins and Subqueries: Combine and filter data from multiple tables to answer complex queries.
- SQL Views and Stored Procedures
Create virtual tables for complex queries using SQL views, and utilize stored procedures to automate repetitive tasks, streamlining your data workflow. - Basics of Python and Data Integration
Learn essential Python programming and libraries for data handling and analysis, preparing you to integrate SQL with Python and unlock advanced analytical capabilities. - SQL and Python Integration
Use Python to access and manipulate SQL data, enabling advanced analysis and data visualization directly from your database. - Capstone Project
Apply your SQL and Python skills in a comprehensive project, demonstrating your ability to handle real-world data analytics tasks and develop insights from structured data.
Who This Program Is For:
Ideal for aspiring data analysts, business intelligence professionals, and anyone looking to build a strong foundation in SQL for analytics. With Python integration, this program is also suitable for those who want to enhance SQL with programming skills for data manipulation and visualization.
Outcome:
By the end of this program, you’ll be proficient in SQL for managing, querying, and analyzing data and confident in integrating Python to automate workflows and conduct in-depth data analysis.
1. Introduction to databases and SQL
2. SQL Theory
3. Basic database terminology
4. Installation of Mysql workbench and MySQLserver
5. Getting started with SQL
6. SQL contraints
7. SQL select statement
8. SQL insert
9. SQL update
10. SQL delete
11. Aggregate function
12. SQL joins
13. SQL sub queries
14. SQL views
15. Stored Procedure
16. Basics of Python Programming
17. Python Libraries
18. Integrating SQL and Python
Project
1. What is SQL, and how is it used in data analytics?
SQL, or Structured Query Language, is a programming language designed for managing and querying relational databases. In data analytics, SQL is used to extract, manipulate, and analyze data stored in databases. Analysts can use SQL to retrieve specific data sets, apply filters, aggregate information, and perform calculations, enabling them to gain valuable insights from the data.
2. How can SQL be used to filter and sort data in data analytics?
SQL provides powerful tools for filtering and sorting data. The “where”clause is used to filter rows based on specified conditions, allowing analysts to extract only the relevant data. Sorting is achieved using the ORDER BY clause, which arranges results based on one or more columns in ascending or descending order. These features help analysts focus on specific subsets of data and present results in a meaningful way.
3. What are SQL aggregate functions, and how do they enhance data analytics?
SQL aggregate functions, such as SUM, AVG, MIN, MAX, and COUNT, enable analysts to perform calculations on groups of data. These functions summarize and provide insights into data patterns, trends, and distributions. For instance, SUM calculates the total of a numeric column, AVG computes the average, MIN and MAX find the minimum and maximum values, and COUNT tallies the number of rows meeting specified conditions. Aggregate functions are essential for summarizing and drawing conclusions from large datasets.
4. Can SQL perform data transformations in data analytics?
Yes, SQL can perform various data transformations. The SELECT statement can be used to create new columns using calculations, combining multiple columns, or applying functions to existing data. Joins allow analysts to combine data from multiple tables, enabling complex analysis by connecting related information. Additionally, CASE statements provide conditional logic for transforming data based on specified criteria. These capabilities allow analysts to shape data to match their analytical needs.
5. How does SQL support data exploration and visualization in data analytics?
SQL supports data exploration and visualization by enabling analysts to retrieve and organize data for further analysis. Analysts can use SQL queries to extract subsets of data, generate summary statistics, and uncover patterns. Once the data is prepared, it can be imported into data visualization tools or libraries to create charts, graphs, and dashboards. By combining SQL's querying capabilities with visualization tools, analysts can communicate insights effectively to stakeholders and make informed decisions based on the data.
Experience SKETO INFOTECH’s Training with Trial Sessions!
Are you ready to explore the world of Data Science, AI, Software Development, or Business Analytics? At SKETO INFOTECH, we’re offering exclusive trial sessions to help you experience our hands-on, industry-focused training before committing to a full program.
Why Choose Our Trial Sessions?
- Get a sneak peek into our expert-led teaching methodologies.
- Explore the latest tools and technologies included in our programs.
- Gain insights into how our project-based learning approach works.
- Interact directly with experienced trainers and mentors.
- Assess how the course aligns with your career aspirations.
Session Options:
- 2-Hour Trial Session: Just Rs. 499/-
- 4-Hour Trial Session: Just Rs. 999/-
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