☁️ Mastering Azure Data Analytics and Big Data Engineering Certification Course

Module 1: Fundamentals of Cloud Data Architecture and Strategy

ü  The Azure Data Platform Ecosystem Overview

ü  Understanding IaaS, PaaS, and SaaS in Data Services

ü  Data Lakes vs. Data Warehouses in modern architectures

ü  Designing Lambda and Kappa Architectures

ü  Cost Management Strategies for cloud data services

ü  Practical Session: Designing a Conceptual Big Data Azure Training Architecture Diagram

Module 2: Azure Data Lake Storage (ADLS) Gen2 and Security

ü  ADLS Gen2 Structure and Hierarchical Namespace

ü  Data Organization and Zoning (Raw, Curated, Consumption)

ü  Authentication: Shared Key, SAS, Managed Identities

ü  Access Control Lists (ACLs) and Role-Based Access Control (RBAC)

ü  Data Redundancy Options (LRS, GRS, ZRS)

ü  Practical Session: Setting up ADLS Gen2 and Configuring Folder-Level ACLs

Module 3: Data Ingestion and Transfer with Azure Data Factory (ADF)

ü  ADF Components: Pipelines, Activities, Datasets, Linked Services

ü  Connecting to Diverse Data Sources (On-premises, other Clouds)

ü  Copy Activity and Data Movement Optimization

ü  Using Self-Hosted Integration Runtimes (SHIR)

ü  Mapping Data Flows for code-free transformations

ü  Practical Session: Building a Pipeline to Ingest Data from On-premises SQL Server to ADLS Gen2

Module 4: Advanced ADF: Pipeline Orchestration and Monitoring

ü  Implementing Control Flow Activities (If Condition, ForEach, Until)

ü  Triggering Pipelines (Schedule, Tumbling Window, Event Triggers)

ü  Error Handling and Logging Mechanisms

ü  Integration with Azure Key Vault for credentials

ü  Monitoring and Alerting using Azure Monitor

ü  Practical Session: Developing an Incremental Load Pipeline with Error Handling

Module 5: Introduction to Azure Synapse Analytics

ü  Synapse Architecture Overview (Studio, Pools, Security)

ü  The Unified Analytics Experience

ü  Synapse Workspaces Creation and Setup

ü  Integrating Synapse with ADLS Gen2

ü  Security Model within Synapse

ü  Practical Session: Provisioning a Synapse Workspace and Linking Data Lake Storage

Module 6: Data Warehousing with Synapse Dedicated SQL Pools

ü  Dedicated SQL Pool Architecture and MPP (Massively Parallel Processing)

ü  Optimizing Data Distribution and Indexing Strategies

ü  PolyBase and COPY Command for high-volume loading

ü  Scaling and Pausing Compute Resources

ü  Implementing Data Security (Masking, Encryption)

ü  Practical Session: Creating a Dedicated SQL Pool, Loading a Data Warehouse Table, and Querying

Module 7: Serverless Data Processing with Synapse SQL and Spark

ü  Synapse Serverless SQL Pool for Ad-Hoc Queries

ü  Querying Data Lake Files (Parquet, CSV, JSON) using OPENROWSET

ü  Synapse Spark Pool Fundamentals and Notebook Management

ü  Using Spark SQL and DataFrames

ü  Optimizing Spark Performance

ü  Practical Session: Running Serverless SQL Queries on Parquet Data in the Data Lake

Module 8: Azure Databricks for Advanced Data Engineering

ü  Databricks Architecture and Cluster Management

ü  Notebooks, Workspaces, and Collaboration Features

ü  Delta Lake Fundamentals and ACID Transactions

ü  Mounting ADLS Gen2 to Databricks

ü  Working with Delta Tables (Upserts, Time Travel)

ü  Practical Session: Creating a Databricks Cluster and Configuring Delta Lake Storage

Module 9: Big Data Processing with Apache Spark on Databricks

ü  Advanced PySpark Coding for Data Transformation

ü  ETL/ELT Workflow Design on Databricks

ü  Performance Tuning Spark Jobs (Caching, Shuffling)

ü  Implementing Structured Streaming (Batch vs. Stream)

ü  Best Practices for Production Databricks Notebooks

ü  Practical Session: Developing and Optimizing a Complex Data Transformation Pipeline in PySpark

Module 10: Real-Time Data Streaming with Azure Stream Analytics

ü  Stream Analytics Architecture and Components

ü  Data Ingestion from Azure Event Hubs and IoT Hub

ü  Stream Analytics Query Language (SQL-like)

ü  Outputting Data to Synapse, Power BI, or ADLS

ü  Windowing Functions and Time Series Analysis

ü  Practical Session: Setting up a Real-Time Dashboard by Processing Event Hub Data with Stream Analytics

Module 11: Integrating Azure Cognitive Services and AI/ML

ü  Overview of Cognitive Services for data analysis

ü  Integrating ML models (e.g., scoring) into data pipelines

ü  Azure Machine Learning Service for model deployment

ü  Using AutoML for rapid model development

ü  Practical Session: Integrating Text Analytics (Sentiment) into a Databricks Pipeline

Module 12: Data Governance and Cataloging (Azure Purview)

ü  The Importance of Data Governance in Azure big data training

ü  Azure Purview Architecture and Data Mapping

ü  Data Lineage Tracking and Root Cause Analysis

ü  Glossary and Data Classification

ü  Managing Data Quality

ü  Practical Session: Registering Data Sources and Viewing Data Lineage in Purview

Module 13: Security and Compliance in Azure Big Data Solutions

ü  Network Security: VNet Integration and Private Endpoints

ü  Encryption at Rest and In Transit

ü  Managing Secrets with Azure Key Vault

ü  Auditing and Logging for Compliance

ü  Designing for HIPAA, GDPR, and other Regulations

ü  Practical Session: Implementing VNet Integration for Synapse and Data Factory

Module 14: Monitoring, Troubleshooting, and Performance Tuning

ü  Azure Monitor and Log Analytics for Data Services

ü  Troubleshooting Pipeline Failures in ADF

ü  Identifying and Resolving Slow Queries in Synapse SQL

ü  Optimizing Data Partitioning and Skew

ü  Cost Monitoring and Alerting

ü  Practical Session: Analyzing Monitoring Logs to Diagnose a Performance Issue

Module 15: Introduction to Azure Cosmos DB for NoSQL Data

ü  Cosmos DB Data Models (Key-Value, Document, Graph, Column-Family)

ü  Core Concepts: Consistency Levels and Request Units (RUs)

ü  Designing Data Partitioning Strategies

ü  Integrating Cosmos DB with Azure Functions and Data Factory

ü  Use Cases for Azure data analytics training with Cosmos DB

ü  Practical Session: Creating a Cosmos DB Database and Importing Document Data

Module 16: Data Visualization and Reporting with Power BI

ü  Connecting Power BI to Azure Data Sources (Synapse, ADLS)

ü  Developing Effective Dashboards and Reports

ü  Using DAX for Advanced Calculations

ü  Power BI Service Deployment and Sharing

ü  Row-Level Security (RLS) Implementation in Power BI

ü  Practical Session: Building a Power BI Report from Synapse Data

Module 17: Infrastructure as Code (IaC) for Azure Data Resources

ü  Introduction to Azure Resource Manager (ARM) Templates

ü  Deploying Azure Data Services using ARM or Terraform

ü  Managing Configuration and Parameters

ü  CI/CD Pipelines for Data Solutions (Azure DevOps)

ü  Automating Deployment

ü  Practical Session: Writing and Deploying an ARM Template for Synapse Workspace

Module 18: Azure Big Data Certification Exam Preparation and Review

ü  Review of Key Exam Topics and Blueprint

ü  Deep Dive into Challenging Concepts

ü  Time Management Strategies for the Exam

ü  Full-Length Mock Exam Simulation

ü  Q&A and Final Study Plan Development

ü  Practical Session: Timed Mock Azure big data certification Exam and Detailed Review

👩‍🏫 About Our Trainers

Our trainers are Microsoft Certified Azure Data Engineers (Expert level) and seasoned consultants with a minimum of 15 years of industry experience specializing in big data Azure training and cloud architecture. They have led numerous enterprise-scale data migration and analytics projects, providing them with practical, in-depth knowledge of building, optimizing, and securing data solutions. Their expertise is directly aligned with the requirements for the official Azure big data certification, ensuring participants receive relevant and current preparation.

✅ Quality Statement

We are committed to delivering the highest caliber Azure data analytics training. Our curriculum is continuously validated against the latest Azure service updates and the official Azure big data certification exam objectives. We prioritize hands-on labs and real-world scenarios to ensure participants gain not just theoretical knowledge, but the immediate, practical skills required to excel as Azure Data Engineers.

Admission Criteria

ü  Participants should be reasonably proficient in English. 

ü  Applicants must live up to Phoenix Center for Policy, Research and Training admission criteria.

Terms and Conditions

1. Discounts: Organizations sponsoring Four Participants will have the 5th attend Free
2. What is catered for by the Course Fees: Fees cater for all requirements for the training – Learning materials, Lunches, Teas, Snacks and Certification. All participants will additionally cater for their travel and accommodation expenses, visa application, insurance, and other personal expenses.
3. Certificate Awarded: Participants are awarded Certificates of Participation at the end of the training.
4. The program content shown here is for guidance purposes only. Our continuous course improvement process may lead to changes in topics and course structure.
5. Approval of Course: Our Programs are NITA Approved. Participating organizations can therefore claim reimbursement on fees paid in accordance with NITA Rules.

Booking for Training

Simply send an email to the Training Officer on training@phoenixtrainingcenter.com and we will send you a registration form. We advise you to book early to avoid missing a seat to this training.

Or call us on +254720272325 / +254737296202

Payment Options

We provide 3 payment options, choose one for your convenience, and kindly make payments at least 5 days before the Training start date to reserve your seat:

1. Groups of 5 People and Above – Cheque Payments to: Phoenix Center for Policy, Research and Training Limited should be paid in advance, 5 days to the training.
2. Invoice: We can send a bill directly to you or your company.
3. Deposit directly into Bank Account (Account details provided upon request)

Cancellation Policy

1. Payment for all courses includes a registration fee, which is non-refundable, and equals 15% of the total sum of the course fee.
2. Participants may cancel attendance 14 days or more prior to the training commencement date.
3. No refunds will be made 14 days or less before the training commencement date. However, participants who are unable to attend may opt to attend a similar training course at a later date or send a substitute participant provided the participation criteria have been met.

Tailor-Made Courses

We understand that every organization has unique challenges and opportunities as well as unique training needs. Phoenix Training Center offers tailor-made courses designed to address specific requirements and challenges faced by your team or organization. Whether you need a customized curriculum, a specific duration, or on-site delivery, we can adapt our expertise to provide a training solution that perfectly aligns with your objectives.

We can customize this Course to focus on your industry, specific risk profile, or internal stakeholder dynamics. Contact us to discuss how we can create a bespoke training program that maximizes value and impact for your team. For further inquiries, please contact us on Tel: +254720272325 / +254737296202 or Email training@phoenixtrainingcenter.com

Accommodation and Airport Pick-up

For physical training attendees, we can assist with recommendations for accommodation near the training venue. Airport pick-up services can also be arranged upon request to ensure a smooth arrival. Please inform us of your travel details in advance if you require these services. For reservations contact the Training Officer on Email: training@phoenixtrainingcenter.com or on Tel: +254720272325 / +254737296202