Data Analytics

Our Data Analytics program unlocks mastery of the art of turning data of any size into actionable insights using powerful tools: BI for strategic analysis, SSIS for seamless data movement, Power BI for stunning visualizations, and Snowflake for cloud-powered storage and query. Craft compelling stories from hidden patterns, guide informed decisions, and propel your organization to data-driven success.

Courses required to become a fullfledged Data Analytics professional

Database Design and Development

Database Fundamentals:

Database Concepts: Defining databases, types (relational, hierarchical, network), advantages, and applications
Database Management Systems (DBMS): Roles, types, components, and functions
Data Modeling: Conceptual, logical, and physical model creation using ER diagrams
Entity Relationship Modeling (ERD): Diagramming entities, attributes, relationships, and keys
Normalization: Understanding normal forms (1NF, 2NF, 3NF, BCNF) and their benefits
Table Design: Creating tables, defining data types, constraints, primary keys, foreign keys

SQL Server Basics:

SQL Server Overview: History, features, editions, and architecture
SQL Language: Syntax, data types, operators, and expressions

Database Development:

Creating Databases: Using SQL Server Management Studio (SSMS) or Transact-SQL (T-SQL)
Creating Tables: Defining structures and relationships
Populating Tables: Inserting data, using bulk operations
Writing Queries: Retrieving, filtering, sorting, grouping, and aggregating data
Joining Tables: Inner, outer, self joins, and their applications
Views: Creating, using, and managing views
Stored Procedures: Creating, using, and managing stored procedures for reusable code
Functions: Defining user-defined functions (UDFs) for custom logic
Triggers: Handling events and automating actions

Additional Topics:

Transactions: Handling data integrity and consistency
Security: Implementing user permissions, roles, and access control
Backup and Recovery: Ensuring data availability and disaster recovery
Performance Tuning: Optimizing queries and database performance
Indexing: Understanding types (clustered, non-clustered) and usage strategies

Basics of Azure Cloud and Azure Databases

Azure Fundamentals:

Introduction to Cloud Computing: Concepts, benefits, deployment models (public, private, hybrid)
Overview of Microsoft Azure: Services, features, pricing model, subscription management
Azure Portal: Navigation, resource creation, configuration, monitoring
Azure Resource Manager (ARM): Understanding templates, deployments, resource groups

Azure Database Options:

Relational Databases: Azure SQL Database, Azure SQL Managed Instance, Azure Database for MySQL, Azure Database for PostgreSQL
NoSQL Databases: Azure Cosmos DB, Azure Table Storage, Azure Blob Storage
Choosing the Right Database: Considerations for data model, scalability, performance, cost

Database Deployment in Azure:

Creating Databases: Using the Azure portal, PowerShell, Azure CLI
Connecting to Databases: Using SQL Server Management Studio (SSMS), Azure Data Studio, application connection strings

Data Analytics and Visualizations

Mastering your data with BI, SSIS, and Power BI

This comprehensive course equips you with the skills to extract insights, build stunning visualizations, and drive informed decisions using a powerful combination of tools: Business Intelligence (BI), SQL Server Integration Services (SSIS), and Power BI.

Course Highlights:

Unlock the power of data: Learn how to connect to various data sources, cleanse and transform it using SSIS, and build a robust data warehouse for BI analysis.
Master Power BI: Dive deep into Power BI, a leading self-service BI platform, to create interactive dashboards and reports that bring your data to life.
Visualize your insights: Explore various data visualization techniques and best practices to effectively communicate your findings to stakeholders.
Gain a competitive edge: Enhance your resume and skillset with in-demand BI, SSIS, and Power BI expertise, opening doors to exciting career opportunities.

Module 1: Introduction to Business Intelligence (BI)

What is BI and why is it important?
Different types of BI solutions
The BI lifecycle: data acquisition, transformation, analysis, and presentation
Popular BI tools and platforms

Module 2: Exploring SQL Server Integration Services (SSIS)

Introduction to SSIS: data extraction, transformation, and loading (ETL) processes
Building SSIS packages: data sources, transformations, and destinations
Error handling and debugging in SSIS
Scheduling and automating SSIS packages

Module 3: Mastering Power BI

Introduction to Power BI Desktop and its interface
Connecting to various data sources: Excel, SQL Server, cloud platforms, etc.
Data modeling and creating relationships in Power BI
Building compelling visuals: charts, graphs, maps, and custom visualizations
Creating interactive dashboards and reports
Sharing and collaborating on Power BI reports

Module 4: Data Visualization and Analytics with Power BI

Data visualization best practices: choosing the right chart type, color palettes, and layout
Storytelling with data: using visuals to communicate insights effectively
Advanced Power BI features: DAX calculations, custom visuals, and Q&A
Building interactive reports with filters, slicers, and drill-downs
Integrating Power BI with other Microsoft services like Azure and Excel

Course Benefits:

Gain hands-on experience with BI, SSIS, and Power BI through practical exercises and projects.
Learn from industry experts and experienced instructors.
Enhance your data analysis and visualization skills to make informed decisions.
Prepare for BI and Power BI certifications.
Boost your career prospects in data-driven fields.

Data Warehousing with Snowflake

In this introductory course, you will learn the concept of cloud data warehousing solution – Snowflake.

Module 1: Introduction to Data Warehousing and Snowflake

What is data warehousing and why is it essential?
Traditional data warehousing limitations
The rise of cloud data warehousing and Snowflake’s unique approach

Module 2: Snowflake Architecture and Concepts

Understanding the separation of storage and compute
Exploring cloud resources: virtual warehouses, databases, and schemas

Module 3: Data Ingestion and Management

Loading data from various sources: files and databases
Transforming and shaping data with Snowflake’s powerful tools
Managing data quality and ensuring accuracy

Module 4: Data Querying and Analysis

Leveraging SQL in Snowflake: writing queries, joins, and functions
Building and optimizing complex queries for efficient data retrieval