Databricks Delta Lake Fundamentals Accreditation

The Databricks Delta Lake Fundamentals Accreditation validates foundational knowledge of Delta Lake — the open-source storage layer that brings ACID transactions, scalable metadata handling, and time travel capabilities to data lakes. It covers Delta Lake's role within the Databricks Lakehouse Platform, core features like schema enforcement, streaming support, and Delta Sharing, as well as how Delta Lake solves common data reliability challenges in cloud storage environments.

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What is the Databricks Delta Lake Fundamentals Accreditation?

Who Should Take This Course?

Data Engineers new to Delta Lake and the Lakehouse architecture
Data Analysts wanting to understand the reliability layer behind Databricks SQL
IT professionals evaluating or adopting the Databricks platform
Software Engineers integrating applications with Delta Lake storage
Anyone pursuing Databricks Associate-level certifications as a foundation
Business stakeholders wanting to understand the technical basis of the Lakehouse

What You Will Learn in the DLF Course

A comprehensive curriculum covering all exam objectives with hands-on labs and real-world practice.

Delta Lake and Lakehouse Architecture

Understand how Delta Lake underpins the Databricks Lakehouse Platform.

Problems with traditional data lakes: reliability, performance, governance
Lakehouse architecture: combining data lake flexibility with data warehouse reliability
Delta Lake's role as the storage foundation of the Lakehouse
Comparing Delta Lake with Parquet, Hive, and traditional data warehouses

ACID Transactions and Data Reliability

Learn how Delta Lake ensures consistent and reliable data operations.

ACID properties: Atomicity, Consistency, Isolation, and Durability
Delta transaction log (_delta_log) and how it tracks changes
Optimistic concurrency control for concurrent writes
Schema enforcement and schema evolution

Time Travel and Data Versioning

Explore Delta Lake's time travel capabilities for auditing and recovery.

Querying historical versions with VERSION AS OF and TIMESTAMP AS OF
Use cases: auditing, debugging, and rolling back bad writes
RESTORE TABLE to revert a Delta table to a prior state
Data retention policies and VACUUM for storage management

Delta Lake Operations and Performance

Optimize Delta tables for query performance and storage efficiency.

OPTIMIZE command and file compaction strategies
Z-Ordering for multi-dimensional data skipping
Auto Optimize: Optimized Writes and Auto Compaction
Data skipping and statistics collection for fast queries

Streaming and Data Sharing

Use Delta Lake for real-time data processing and cross-platform sharing.

Delta Lake as a streaming source and sink
Change Data Feed (CDF) for tracking row-level changes
Delta Sharing: open protocol for sharing data across platforms
Integrating Delta Lake with Databricks Workflows and Auto Loader

Course Prerequisites

Pre-requisites training is free when you purchase the course from ProSupport

Basic understanding of data storage and cloud computing concepts
Familiarity with SQL is helpful but not required
No programming experience required for this accreditation
Completion of free Databricks Fundamentals on-demand training is recommended

Exam Information

Everything you need to know about the DLF certification exam.

Exam Component	Details
Exam Name	Databricks Delta Lake Fundamentals Accreditation
Exam Code	DLF
Exam Type	Multiple Choice (non-proctored)
Total Questions	20
Passing Score	70%
Exam Duration	30 minutes
Language	English
Exam Provider	Databricks Academy (free accreditation, no registration fee)
Exam Focus	Delta Lake architecture, ACID transactions, time travel, schema enforcement, streaming, and Delta Sharing
Exam Registration	Databricks Academy portal (academy.databricks.com) — Free
Retake Policy	No waiting period — retakes available immediately
Certification Validity	Does not expire (accreditation badge)