Data Analytics and Engineering Bootcamp

Database Design and Modeling

This module focuses on various aspects of database designing concepts right from entities, keys, constraints, and normalization to creating physical instance of databases. The focus of Data Modeling is to understand different stages of database designs patterns along with ways to gather business requirements. Topics:

• Software Development Life Cycle (SDLC)

• Requirement Gathering Techniques
• Documentation
• Software Design Methodologies
• ER-Diagrams
• Normalization
• Reverse and Forward Engineering
• Database Integrity

 

Database Programming & Administration

This module exposes the candidates to the very details of T-SQL programming along with working on database objects such as tables, views, stored procedures, user defined functions, triggers, & indexes. Module also covers performance implications of multitude of SQL structures such as joins, sub-queries, set operators, CTEs to be incorporated for implementing business requirements. Topics:

• Introduction to SQL Server
• Data Definition Language (DDL)
• Data Manipulation Language (DML)
• Data Query Language (DQL)
• Constraints & Wild Cards
• Joins & Sub Queries
• Set Operators & Views
• Dynamic SQL & Control Flow Statements
• Stored Procedures, Functions & Triggers
• Indexes
• Error Handling
• Transaction Control Language (TCL)
• Partitions

Data Warehouse (OLAP) Design Techniques

Data Warehousing module provides detailed insight on the designing and developing data structures to store historical data for analytical purposes. This module further explains more about the internals and architecture of Data Warehouses and Data Marts following Kimball or Inmon Methodologies. Topics:

• Online Transaction Processing (OLTP) and Online Analytical Processing (OLAP)
• Dimension Tables
• Fact Tables
• Data Warehouse Architecture
• INMON and KIMBALL approach

 

Data Integration – ETL and ELT

This module talks about SSIS as an ETL tool to practically connect to different data sources, perform various data operations and load data into dimensional structure. Candidates will also be exposed to various concepts of ETL which includes Data Profiling, Data Cleansing, Data Validations, Error Handing and Deployment. Topics:

• Introduction to SSIS
• Data Sources and Connectivity methods
• Data Flow and Control Flow
• Transformations
• Tasks
• Containers
• Error Handling
• Logging
• Checkpoints
• Transactions
• Package and Project Deployment
• Incremental Load

SQL Server Analysis Services (SSAS)

Microsoft SQL Server Analysis Services is an online analytical processing and data mining tool in Microsoft SQL Server. SSAS is used as a tool by organizations to analyze and make sense of information possibly spread out across multiple databases, or in disparate tables or files Topics:

• Introduction to SSAS
• Tabular Model
• DAX
• Perspectives
• Key Performance Indicators
• Row Level Security
• Partitions
• Deployment
• Processing

 

SQL Server Reporting Services (SSRS)

This module is mainly used as presentation layer for creating different types of visual reports for making business decisions. Candidates will be learning different types of reporting constructs, publishing, maintaining reports on Report Server. Topics:

• Introduction to SSRS
• Configuration Manager
• Report Server and Report Manager
• Rendering Reports
• Designing Reports
• Deploy Reports
• Caching
• Snapshot
• Subscriptions

 

Reports & Dashboard Design with Power BI

This module is primarily focused on creating data visualizations, data cleansing, DAX for calculations. In this module candidates will also learn different ways of publishing, embedding, maintaining reports & dashboards within Power BI Desktop and Power BI Service Topics:

• Introduction to Power BI
• Power BI Desktop
• Connectivity Methods
• Visualizations
• Power Query
• DAX
• Row Level Security
• Power BI Service
• Gateways
• Power BI Licenses

 

Cloud Computing with MS-Azure

This module focuses on Infrastructure & Platform services which includes compute, storage, Azure data services (Azure SQL, Data Pools, Synapse Analytics and Data Factory). Candidates will learn provisioning and maintaining above mentioned services and understanding the benefits of cloud computing on MS-Azure platform Topics:

• Introduction to Cloud Computing
• Introduction to Azure
• Azure Storage
• Azure SQL
• PowerShell
• Data Migration
• Azure Data Factory
• Azure BI Services

Snowflake

Snowflake is a cloud data warehouse that can store and analyze all your data records in one place. It can automatically scale up/down its compute resources to load, integrate, and analyze data. Snowflake enables data storage, processing, and analytic solutions that are faster, easier to use, and far more flexible than traditional offerings. Topics:

• Introduction to Snowflake Architecture
• Snowflake Editions and Pricing Model
• Resource Monitor and Data Storage (Micro-partitions)
• Clustering in Snowflake
• Query History, Caching, Time travel, Fail Safe, Zero Copy Cloning
• Objects in Snowflake
• Data Ingestion to Snowflake using SnowSQL, Snowpipe

Python

Python is a computer programming language used to build websites and software, automate tasks, and conduct data analysis. Python has become a staple in data science, allowing data analysts and other professionals to use the language to conduct complex statistical calculations, create data visualizations, build machine learning algorithms, manipulate and analyze data, and complete other data-related tasks. Topics:

• Introduction of Python
• Data Types and Variables
• List, Dictionary, Sets and Tuples
• Control Flow Statements
• Functions in Python
• File Handling
• Object Oriented Concepts
• Error Handling
• Web Scrapping Principles
• Graphical User Interface in Python
• Numpy, Panda and Matplotlib Library

Power Automate Topics

1. Need for Power Automate
   • How Power Automate reduces human intervention in repetitive tasks.
2. Basics of Power Automate
   • Creating Flows and Connectors
   • Working with Variables, Compose, Filter, and Select
   • Integrating with REST APIs
   • Using Loops, Try and Catch, and Logging
   • Triggers and Conditions
3. Power Fx
   • The language of Power Platform
4. Creating and Implementing Real Use Cases
   • Integrating Power Automate with Power BI

Scenarios:

1. Scenario 1: Power Automate for Desktop Flows
   • Explore how to automate desktop applications using Power Automate.
2. Scenario 2: Implementing Real Scenarios for Cloud Flows
   • Practical examples of using Power Automate in cloud environments.
3. Scenario 3: Integrating Power Automate with Power BI
   • How to enhance reporting capabilities by connecting Power Automate and Power BI.
4. Scenario 4: SSIS Pipelines to Power Automate Flow
   • Automating data integration and movement tasks using Power Automate and migrating from SSIS pipelines.

Power Apps Topics

1. Fundamentals of Power Apps
   • Understanding the basic concepts and architecture of Power Apps.
2. Creating Real-Time Domain-Specific Apps
   • Developing applications tailored to specific industry needs.
3. Writeback Using Power Apps in Power BI
   • Enabling data modification directly within Power BI using Power Apps.

Career Success

Sharpen your career skills with our “Career Success” module in the bootcamp. Master job search prep, networking for interviews, and refine application materials. Enhance your interview game with technical and non-technical prep and practical mock interviews. Cap it off with a graduation milestone, marking your readiness for a successful career journey. Gain the edge for lasting professional success with Career Success. Topics:

• Career Success: Preparing for the Job Search
• Building a network and using it to Land Interviews
• Career Success: Resume, Cover Letter, LinkedIn Review
• Career Success: Interview Prep (Technical and Non-Technical)
• Mock Interviews
• Graduation