Introduction to Apache Spark

What is Apache Spark?

Evolution from Hadoop to Spark

Spark vs. Traditional Data Processing

Spark Ecosystem Overview

Cluster Architecture (Driver, Executors, Tasks)

Setting Up Databricks & Spark

Introduction to Databricks Platform

Creating a Databricks Workspace

Databricks Notebooks & Commands

Clusters: Types, Configurations & Autoscaling

Databricks File System (DBFS)

Connecting Databricks with Cloud Storage (Azure)

Spark DataFrames & Transformations

Introduction to Spark DataFrames

Schema Inference & Explicit Schema Definition

Transformations & Actions (map, filter, reduce, groupBy, etc.)

Joins, Aggregations & Window Functions

Handling Missing Data & Data Cleansing

Caching & Performance Optimization

Spark SQL & Delta Lake

Writing SQL Queries in Spark

Spark DataFrames vs. Spark SQL

Hive Metastore Integration

Introduction to Delta Lake

Schema Evolution & Time Travel

ACID Transactions in Delta Lake

Optimizing Delta Tables (Z-Ordering, Auto-Optimize, Vacuum)

Spark Streaming on Databricks

Introduction to Spark Streaming

Structured Streaming Architecture

Streaming Sources (Kafka, Event Hub, Delta Tables)

Stream Processing & Window Operations

Stateful Processing & Checkpointing

Writing Streaming Data to Delta Lake

Advanced Spark Optimization

Lazy Evaluation & Catalyst Optimizer

Tungsten Execution Engine

Broadcast Joins & Skew Handling

Adaptive Query Execution (AQE)

Partitioning & File Format Optimization

Best Practices for Spark Job Performance

Microsoft Fabric and DP-700 Certification Preparation

Microsoft Certified: Fabric Data Engineer Associate

Implement and Manage an Analytics Solution

Configure Microsoft Fabric workspace settings

Configure Spark workspace settings

Configure domain workspace settings

Configure OneLake workspace settings

Configure data workflow workspace settings

Implement lifecycle management in Fabric

Configure version control

Implement database projects

Create and configure deployment pipelines

Configure Security and Governance

Implement workspace-level access controls

Implement item-level access controls

Implement row-level, column-level, object-level, and file-level access controls

Implement dynamic data masking

Apply sensitivity labels to items

Endorse items

Orchestrate Processes

Choose between a pipeline and a notebook

Design and implement schedules and event-based triggers

Implement orchestration patterns with notebooks and pipelines, including parameters and dynamic expressions

Ingest and Transform Data

Design and implement loading patterns

Design and implement full and incremental data loads

Prepare data for loading into a dimensional model

Design and implement a loading pattern for streaming data

Monitor and Optimize an Analytics Solution

Monitor Fabric items

Monitor data ingestion

Monitor data transformation

Monitor semantic model refresh

Configure alerts

Identify and resolve errors

Optimize performance across lakehouses, pipelines, and datawarehouses

DP-700 Exam Preparation

Comprehensive Review of Course Content

Practice Tests & Tips for Exam Success

Q&A Sessions with Instructors

Mock Exams and Real-World Problem Solving

Duration & Timings :

Duration – 75 Hours.

Training Type: Instructor Led Live Interactive Sessions.

Faculty: Experienced.

Weekday Session – Mon – Thu 8:30 PM to 10:30 PM (EST) – 10 Weeks. April 28, 2025.

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