Course Description
We
partnered with industry insiders to help you learn the data analysis skills
that employers look for. This 320-hour curriculum features a combination of hands-on
projects, case studies, and career-related coursework.
Module 1: Data
Modeling
This module focuses on various aspects of database designing
concepts right from entities, keys, constraints, etc. 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.
Module 2: T-SQL
This module exposes the candidates to the very details of TSQL
programming along with working on database objects such as tables, views,
stored procedures, user defined functions, triggers, and 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
Module 3: Data Warehousing
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.
Module 4: SSAS
In this module candidates will learn purpose and application of
creating multi-dimensional cube and tabular models for further data analysis.
Furthermore, this module also focuses on writing MDX and DAX queries for
analytical purposes.
Module 5: 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.
Module 6: Power BI
This module is primarily focused on creating data visualizations,
data cleansing, DAX for calculations etc. In this module candidates will also
learn different ways of publishing, embedding, maintaining reports &
dashboards within Power BI services and Power BI report server.
Module 7: Microsoft Azure
This module focuses on basics of cloud services. This module
focuses on connecting and consuming data stored within Azure Storages, Azure
SQL database, Azure Analysis Services, and Data pools for reporting purposes.
Module 8: Tableau
This module offers different ways of developing business
interactive dashboards utilizing Tableau Desktop. Candidates will be exposed to
various features of Tableau related to data preparation, data blending,
calculations utilizing LOD expressions, and publishing to enterprise portal.
Module 9: Python
This module offers overview of Python basics, data structures in
Python, various programming constructs and commonly used libraries. This will
also include various methods of extracting data, cleansing, and basic data
visualizations per business requirements.
Module 10: Snowflake
This module focuses on the key concepts and architecture of
Snowflake. Candidates will learn how to provision a Virtual Data warehouse,
migrating data to Snowflake warehouse using SnowSQL & Snowpipe, querying
Snowflake warehouses, time-travel, Zero-copy cloning, etc
Module 11: TFS and Azure DevOps
Introduction to TFS and Azure DevOps for project coordination,
management, and version control.
Agenda
- 320 hours of training
- Included courses: T-SQL, SSAS, SSRS, Power BI, Microsoft Azure, Tableau, Python, Snowflake, and more
- To be eligible for participation in this bootcamp, you need to have the following:
- Basic understanding of database objects
- Good logic-building and analytical skills
- Ability to write logic for queries
- Good presentation and delivery skills
- This program is available at any learning center or online
- This program is eligible for VA tuition benefits
- Take advantage of job placement assistance for the first 12 months following bootcamp completion
Audience
Graduates of the Data Analytics & Business Intelligence Bootcamp get hired into the following types of job titles:
- Business Analyst
- Business Intelligence Analyst
- Business Intelligence Manager
- Data Analyst
- Data Analytics Consultant
- Data Engineer
- Data Scientist
- Marketing Analyst
- Operations Analyst
- Quantitative Analyst