Data Analytics Process, Cloud Solutions, and Power BI Solutions

• Experience with elementary data analysis (e.g., Excel).
• A general understanding of cloud concepts (e.g., AWS).

Audience

• Database engineers
• Developers

Data analysis refers to the process of obtaining, cleaning, and analyzing data, often times in a visual manner, to derive insights for better decision making. More and more data is being stored in databases in the cloud so it is important to have a strategy for understanding, managing and accessing such data. One popular tool for accessing and visualizing data is Power Bi.

This instructor-led, live training (online or onsite) is aimed at technical persons who wish to gain a practical understanding of available cloud solutions, the data analysis processes needed to work with data in the cloud, and the hands-on practice to apply tools such as Power BI to analyze data.

By the end of this training, participants will be able to:

• Install and configure Power BI.
• Evaluate the various data solutions offered by cloud providers such as Azure.
• Gain an understanding of the different structures, modeling approaches, and data warehouse designs used to store, manage and access Big Data.
• Apply tools and techniques to clean data in preparation for analysis.
• Build reporting and analytics solutions based on on-premise as well as cloud data.
• Integrate data analytics solutions with a data warehouse.
• Mitigate data security risks and ensure data privacy.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

Introduction

Overview of On-Premise and Cloud-Based Data Storage and Analysis Solutions

Understanding Big Data

• Big Data criteria
• Big Data structure
• Working with Big Data

Cloud Solutions

• Azure SQL Database
• Azure Data Warehouse
• Azure Data Factory
• Azure Databricks
• Power BI

Working with Databases

• Data warehouse design
• Dimensional modelling
• Implementation and deployment

Data Models - A Comparison

• SSAS Tabular Data Models
• SSAS Multidimension Models
• Power BI Models

Data Cleansing

• Strategies and tools

Report Models

• Building Power BI tabular models
• Understanding DAX

PowerBI Reports

• Designing Power BI reports

Power BI Architecture

• Workspace generation
• Licensing
• Permissions

Administration

• Administering Azure solutions
• Administering the Power BI Service

Security

• Maintaining a secure Azure architecture
• Azure SQL Database/Data Warehouse, Data Factory and Data Bricks
• Data Masking and Privacy Issues

Summary and Conclusion