Can the program be customized?

Yes. Build Pipelines with Lakeflow Spark Declarative Pipelines supports customization around lab depth, demo context, certification focus, and team-specific scenarios.

Yes. This program includes instructor-led labs and practical exercises aligned to real implementation patterns.

How does this align with official certification or curriculum?

This program is aligned to the official Databricks curriculum and learning path referenced for this track.

How are prerequisites assessed?

We review prerequisite readiness during scoping and can recommend preparatory modules or a skills checkpoint before cohort start.

What happens after the program?

Private cohorts receive a handover summary, recommended next learning paths, and optional follow-on advisory for rollout or certification readiness.

Enterprise Program Brief

Build Pipelines with Lakeflow Spark Declarative Pipelines

Part of the Databricks Analytics Engineer pathway. Learn how to build governed, end-to-end SQL pipelines using the Spark Declarative Pipelines editor.

Official Source: DatabricksDatabricksIntermediate

Plan Private Delivery Consult a Solutions Architect

Download Program Brief (PDF)

Program Snapshot

Engagement scoped to cohort

DurationSelf-paced or instructor-led

FormatSelf-paced or instructor-led

LevelIntermediate

SubjectAnalytics

MCT-led delivery
Private cohort / virtual ILT
Typical response: 1 business day

Scoping call typically scheduled within one business day

VNode ITeS delivers Build Pipelines with Lakeflow Spark Declarative Pipelines as an MCT-led Databricks program for Analytics Engineer. Typical duration is Self-paced or instructor-led (Self-paced or instructor-led). Labs follow production-shaped scenarios rather than slide-only walkthroughs. Private cohorts can shift emphasis by role mix, workspace or repo constraints, and rollout timing.

Audience Profile

Built for these roles

SQL practitioners building governed pipelines in the Spark Declarative Pipelines editor.

Analytics Engineer
Analytics
Tailored Team Delivery
Implementation-Focused

Overview

Executive overview

Learn how to build governed, end-to-end SQL pipelines using the Spark Declarative Pipelines editor.

Prerequisites

Working SQL and familiarity with Databricks pipelines.

Program Outcomes

Capabilities your teams will gain

Understand streaming tables, materialized views, and temporary views
Enforce data quality with built-in expectations
Handle slowly changing dimensions with AUTO CDC INTO
Analyze pipeline execution through event logs and metrics

Enterprise Delivery

Official learning & delivery options

Review the vendor learning resource, then book a consultation or request a private cohort for your team.

View Official Learning Book a Consultation Request Private Cohort Program brief (PDF)

Curriculum

Curriculum roadmap

Streaming tables, materialized views, and temporary views
Data quality expectations
Slowly changing dimensions with AUTO CDC INTO
Pipeline event logs and metrics

Module 1

Pipeline objects

Understand streaming tables, materialized views, and temporary views.

Understand streaming tables
materialized views
and temporary views

Module 2

Data quality expectations

Enforce data quality with built-in expectations.

Slowly changing dimensions with AUTO CDC INTO
Pipeline event logs and metrics

Module 3

AUTO CDC INTO

Handle slowly changing dimensions with AUTO CDC INTO.

Slowly changing dimensions with AUTO CDC INTO

Module 4

Event logs and metrics

Analyze pipeline execution through event logs and metrics.

Pipeline event logs and metrics

Delivery Models

Delivery models

Virtual ILTOnsiteHybridExecutive WorkshopBootcampWeekend

Engagement Fit

Engagement fit

Implementation-focused labs
Private cohort delivery
Intermediate practitioner depth
Business outcome alignment

Enterprise Customization

Enterprise customization

Tailor this program to your organization's priorities: Helps analytics teams build governed SQL pipelines with quality checks and change handling.

Align the pipeline example to a current ingestion source

Credentials

Certification & official source

Aligned to the official Databricks training catalog and certification guidance for this program.

View Databricks Training Source

Resources

Program resources

Yes. Most enterprise clients prefer private delivery scoped to role mix, timezone, and rollout timeline. We align lab environments and scenarios to your tenant context where applicable.

Program brief (PDF)View Databricks Training Source

Enterprise Proof

Trusted delivery outcomes

“The Microsoft Fabric implementation program gave our data engineering team a structured path from legacy pipelines to a modern lakehouse architecture.”

“We needed a partner who understood both the technical depth of Azure OpenAI and the governance requirements of an enterprise.”

Banking & Finance

Representative Enterprise Banking Team

The focus was not just on tooling knowledge, but on helping teams work from a shared operating model as they adopted a more modern data platform.

Clearer platform operating model across teams
Improved confidence in modern data stack adoption

Read engagement

Retail & E-commerce

Representative Retail Analytics Team

Instead of treating reporting as a tooling issue alone, the work focused on consistency, governance, and shared delivery practices across analysts and engineering teams.

Higher consistency in report design practices
Improved collaboration between analysts and engineering teams

Read engagement

Delivery Capability

Enterprise-grade instruction

View delivery capability profile

MCT-led delivery

Programs led by Microsoft Certified Trainer practitioners

Enterprise program oversight

Founder-led specialist delivery with structured rollout planning

Global delivery

APAC · EMEA · Americas · Virtual & Onsite

Implementation-focused

Hands-on labs aligned to production scenarios

Plan delivery