Databricks Integration

For Data Engineering, Analytics, ML & IT teams that need CRM, ERP, marketing & operational data flowing into Databricks Lakehouse from Salesforce, HubSpot, NetSuite, SAP & ServiceNow within 2-5 days to accelerate AI model training & unified analytics.

Eliminate manual Spark pipeline scripting from 60+ engineering hours per connector to under 4 hours (over 93% reduction) within 30 days through no-code Databricks connectors with pre-built Salesforce, HubSpot, NetSuite & ServiceNow Delta Lake models.
Reduce AI model training data latency from 24-48 hour batch delays to under 15 minutes (over 95% improvement) in the first month by streaming CRM, ERP & marketing events into Databricks Delta Lake via real-time CDC pipelines.
Accelerate Unity Catalog data onboarding from 8-week IT projects to 2-day self-service flows (over 90% faster) within 60 days through governed no-code ingestion from Marketo, Oracle, Microsoft Dynamics 365 & Zendesk directly into managed Delta tables.
"2-day implementation" guarantee - Reduce Databricks integration projects from 8-12 week custom Spark builds to 2-5 day go-lives by using certified connector templates instead of hand-coded notebooks & Lakeflow jobs.
SOC 2 + ISO 27001 compliance - Lower audit risk from fragmented ingestion scripts by consolidating Databricks integrations into one governed platform with AES-256 encryption, Unity Catalog alignment & full data lineage tracking.

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Trusted by Fortune 500 leaders in financial services, technology, and global enterprise.

Stop Letting Disconnected Source Systems Trap Your Databricks Investment

Connect Databricks Lakehouse with Salesforce, HubSpot, NetSuite, SAP, ServiceNow, Marketo & Oracle to unify customer, revenue & operational data for AI, ML & BI teams within weeks instead of quarters.

Databricks Financial Services Regulatory Compliance Use Case

Financial Services: Regulatory-Compliant Lakehouse

Reduce regulatory reporting cycles from 10 business days to 3 days (70% faster) for a 120-person financial services organization by automating Salesforce, NetSuite, Workday & Oracle data into Databricks with Unity Catalog governance.

Scenario: Global financial institution managing over 2 million customer accounts across Salesforce for CRM, NetSuite for revenue, Workday for HR & Oracle for risk, with compliance teams spending 15+ hours weekly exporting CSVs into Excel for regulatory filings while auditors demand full lineage.

Solution: Configure Put It Forward to stream Salesforce opportunity, NetSuite invoice, Workday headcount & Oracle risk objects into Databricks Delta Lake on 15-minute schedules; register all tables in Unity Catalog with automated access policies; apply data quality rules & approval workflows for regulatory flags; orchestrate real-time alerts to risk owners when compliance thresholds are breached via Power BI & Tableau dashboards.

Databricks Manufacturing Predictive Maintenance Use Case

Manufacturing: Predictive Maintenance Automation

Reduce equipment downtime from 9 hours per incident to 4 hours (over 55% improvement) by unifying SAP ERP, ServiceNow, Oracle Field Service & IoT sensor data into Databricks for ML-driven predictive maintenance models.

Scenario: Manufacturing organization with 300 production assets, 60 service managers & 5 disconnected systems including SAP ERP for inventory, ServiceNow for IT tickets, Oracle Field Service for dispatch, Salesforce for contracts & IoT platforms for sensor telemetry, causing 48-hour delays in failure pattern detection.

Solution: Use Put It Forward to stream SAP ERP parts availability, ServiceNow incident history, Oracle Field Service dispatch logs & IoT sensor readings into Databricks Delta Lake; train MLflow predictive maintenance models on unified asset histories; trigger automated ServiceNow work orders when failure probability exceeds thresholds; surface real-time asset health dashboards in Power BI for operations leaders.

Healthcare: HIPAA-Compliant Patient Analytics

Improve patient data access for clinical analytics from 10 business days to 2 days (80% faster) for a 500-bed hospital network by automating Epic EHR, Workday, ServiceNow & SAP data into Databricks with PHI masking & HIPAA-compliant governance.

Scenario: Regional healthcare system with Epic for patient records, Workday for staffing, ServiceNow for IT operations & SAP for supply chain, with a 5-person BI team spending 2 weeks per reporting cycle manually joining exports for capacity planning & clinical outcome analysis.

Solution: Configure Put It Forward to extract Epic operational metrics, Workday staffing levels, ServiceNow incident volumes & SAP inventory data into Databricks Delta Lake with automated PHI tokenization; register all datasets in Unity Catalog with HIPAA access policies; orchestrate daily incremental loads with automated retry logic & schema drift detection; surface unified operations dashboards in Databricks SQL & Tableau for administrators & department heads.

Turn Source System Events Into Databricks Lakehouse Intelligence

Databricks no-code data integration and Delta Lake automation

Orchestrate CRM, ERP, marketing & operational data changes into Databricks Delta Lake pipelines in days while data engineering retains full control over Unity Catalog governance, scheduling & lineage.

Automate Salesforce opportunity & account syncs into Databricks Delta Lake from nightly batch notebooks to 15-minute CDC streams (over 95% latency reduction) through event-driven connectors with incremental merge patterns.
Sync HubSpot & Marketo campaign engagement into Databricks from weekly manual exports to hourly automated loads (over 85% faster) through scheduled jobs with AI-powered field mapping, deduplication & Unity Catalog registration.
Stream NetSuite & SAP transactional data into Databricks from month-end reconciliations to daily incremental Delta merges (over 90% improvement) using change data capture connectors with full audit trails & schema enforcement.
Push ServiceNow & Zendesk ticket metrics into Databricks from ad-hoc analyst requests to automated pipelines (over 70% time savings) through pre-built connector templates with configurable schedules & Delta table optimization.
Load Microsoft Dynamics 365 & Oracle data into Databricks from quarterly IT projects to self-service data flows (over 80% faster) by enabling business analysts to configure pipelines without writing Spark notebooks or Lakeflow jobs.

Databricks Integration ROI

Quantify the impact of connecting Databricks to your CRM, ERP, marketing & operational systems without multi-month data engineering backlogs or custom Spark development.

Increase AI model training data freshness from 24-48 hour delays to under 1 hour across 15+ source systems (over 95% improvement) within one quarter through unified Databricks pipelines replacing fragmented notebooks & cron jobs.
Reduce data engineering maintenance from 3 full-time Spark developers to 1 part-time admin (over 70% cost reduction) in six months by replacing custom PySpark ETL scripts with governed no-code Databricks orchestrations.
Improve analyst productivity from 15 hours per week on data prep to under 3 hours (over 80% time savings) within two months by delivering clean, joined datasets in Databricks SQL instead of raw exports requiring manual notebook transformation.
Cut pipeline failure resolution time from 8 hours average to under 30 minutes (over 90% faster) by centralizing Databricks data flows into a single platform with automated retry logic, schema drift detection & root cause visibility.
Raise data pipeline uptime from 94% with scattered notebooks to 99.8% within the first 60 days through monitored Databricks connectors, Delta table health checks & enterprise support backed by 24/7 observability.

Databricks Integration Leader

David Hrynk

Director of Program Management

“Having our global teams all working from the same page is critical to our success. Put It Forward exceeded way beyond where others died.”

Uma Asthana

Director of Operations and Technology

“What you just did for our teams' productivity and how we work was magic - you guys are rock stars, I’m truly blown away”

Udo Waibel

CTO

“Put It Forward takes us where no others could - we struggled for years with an enterprise data story - this solved it across the board”

Sarika Saoji

Marketing Platform Technologist

“For me when our internal teams tried to replicate the Put It Forward technology that was when the pin dropped … these are really smart people”

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Why Teams Choose Integration Designer Over Code, RPA, and File Drops

The Only Option Built for Governed, Multi‑System Integrations

19 integration features that matter most when choosing between code, RPA, connectors, and file transfers.

Capability	Put It Forward	Code/Middleware	RPA	Vendor Connector	Bulk File Transfer
Architecture & Scale
No Code Solution	Yes, Native	No	Scripts	Limited	No
Bi-Directional Integrations	Yes, Full	Build	NA	Limited	NA
Data Transformations (with validation)	Yes, Native	Build	No	No/Fixed Mapping	Limited
Data Persistence / State Management	Yes, Native	No	No	No	N/A
API Gateway Compatible	Yes	Build/3rd Party	No	No	No
Service Integration	Yes, Native	Yes, Build	No	No	N/A
Secure On-Premise Integration	Yes, Native	Requires Special Config/No	No	No	No
Intelligence & Automation
Custom Business Rules	Yes, Full	Limited	Limited to scripts	No	No
Process Automation & Orchestration	Yes, Full	Limited	Scripts	Not focused	No
Process Mining	Yes, Embedded	No	No	No	No
AI Agents (Integrated)	Yes, Native	Limited, Build	Scripted	No	No
Governance & Operations
Integrated Data Governance	Yes, Native	No, 3rd Party	Not Focused	Not Focused	No
Error Capture and Correction	Yes, Full	Limited, Build	No, Scripted	No	Not Focused
Integration Reporting, Analytics and Alerts	Yes, Native	Limited	N/A	Limited	No
Audit Reporting and Analytics	Yes, Full	No, Limited	No	No	Limited
Full API Access and Support	Yes, Native	Yes, Build	No, Limited	No	N/A
Implementation support	Yes, Full	Self Funded/SoW	Self Funded/SoW	Self Funded/SoW	Self Directed
Partner API Roadmap Alignment	Yes, Supported	No	No	No/Lagging	NA

The intelligent decision automation playbook for revenue, operations and IT

IDC Put It Forward Next Generation Business Requirements

Take A Tour Of How The Integration Designer Works

Put It Forward - Integration Designer Demo Tour

You'll see in this scenario the Put It Forward Integration Designer connecting two best-of-breed systems together.

Work with standalone configuration-based connectors which can be included in the Process Designer
Set the integration interval from real-time to intraday
Create business rules and event triggers for seamless execution

Integration Designer Auto Data Mapper

Put It Forward's Composable Integration Auto Data Mapper is a powerful tool for streamlining and automating the data integration process.

AI algorithms automatically map fields between integrated systems and services
Reduce manual effort and time needed to be productive
Always stay ahead by taking advantage of the latest API changes

Conversational AI Agents

Discover how Put It Forward's AI-powered Integration Designer uses conversation to simplify complex business rule creation.

Convert complex business rules from natural conversation into functions
Go faster without having to learn how Put It Forward works at an expert level
Reduce the costs of IT and increase the quality of your data

2-Day Integration and Automation Enhancement, Not 2-Month Projects

Put It Forward Workday ServiceNow Integration Project Plan

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We all implement new technology; a transformation or automation project can be simple, targeted, or enterprise-wide.

Accelerate time-to-value and reduce risk with a proven integration plan.

Our proven methodology ensures low-risk, high-impact integrations. Most clients see measurable ROI in the first year accelerated by best practices and enterprise-grade support.

Most clients see improved integration automation performance within 48 hours
Zero disruption guarantee - No downtime to existing systems, pipelines or data loads

Implementation timeframes depend on scope and complexity:

Hour 1-2: Configure connection source and destination
Hour 2-36: Business rule configuration and validation
Hour 36-48: Full deployment

Put It Forward Databricks Integration and Automation Resources

Guide to Agentic Workflows

This guidebook gives Integration Designer users a practical roadmap to implement AI agentic workflows, integrating intelligent automation and predictive analytics, to optimize business processes and decision-making.

Guide to Agentic AI Workflows

Process Automation vs. Orchestration

With increasing workloads across the organization, this discussion walks you through the right time to use process automation or an orchestration solution for integration.

Discover Automation vs. Orchestration

How to real time data integration for Databricks users

Real-Time Integration Best Practices

Integration Designer users will learn practical best practices to automate, scale, and secure real-time data integration and automation for instant, unified insights and agile business operations.

How To: Real Time Data Integration

What You Should Do Next

Get My Personalized IT Automation Demo:

Discover how leading IT teams are slashing manual work by 80% and accelerating digital transformation with Put It Forward. See real use cases, ROI, and outcomes tailored to your environment. No sales pitch, just actionable insights.

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Key IT Transformation and Leadership Assets

Revenue Operations IT Intelligent Automation Playbook

Revenue, Operations and IT Playbook

Discover practical strategies and real-world benefits of intelligent automation to streamline IT operations, integrate data, and drive business transformation.

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Buyer Guide For Intelligent Automation

Get expert guidance on evaluating, selecting, and deploying intelligent automation solutions to maximize IT transformation, efficiency, and business impact.

Get My Intelligent Automation Buyer Guide

How PIF's Architecture Works

Step through the architecture of Put It Forward; by the end of this video, you'll understand the platform, its components, and how it makes a difference in the enterprise.

Databricks Integration – Frequently Asked Questions (FAQs)

How fast can we go live with Databricks integration across our CRM, ERP & marketing systems?

Most teams move from manual CSV uploads or custom Spark notebooks to automated bi-directional integrations with systems such as Salesforce, HubSpot, NetSuite & ServiceNow in 2-5 days by using pre-built Databricks connector templates, guided onboarding & schema-safe deployment patterns that do not require changes to your existing Databricks workspace or Unity Catalog configuration.

How does Put It Forward manage security, compliance & downtime risk when integrating Databricks?

Put It Forward operates as a SOC 2 & ISO 27001 certified platform with AES-256 encryption, Unity Catalog alignment, role-based access controls & full job-level audit trails so that Databricks data stays governed while integrations are monitored 24/7, with blue-green style rollout options that prevent unplanned downtime in production Lakehouse environments.

Can the Databricks connector handle our data volumes, complex schemas & multi-source Delta merges?

The connector is designed for enterprise scale, moving billions of rows per day into Databricks Delta Lake across hundreds of tables while supporting incremental merges, schema evolution, CDC patterns & cross-source key matching so data engineering, ML & BI teams can model complex analytics without rewriting custom PySpark notebooks.

What kind of support will we receive during & after a Databricks integration project?

Projects include guided implementation from specialists who understand Databricks Lakehouse architecture, Unity Catalog governance & common source systems like Salesforce & NetSuite, plus ongoing 24/7 support, pipeline reviews & optimization assistance so your data engineering & ML teams can adjust mappings or schedules with confidence instead of opening long engineering backlogs.

When will we see measurable ROI from connecting Databricks with our source systems?

Most organizations report measurable improvements such as faster ML model training cycles, reduced analyst data prep hours & fewer pipeline failures within the first 30 days after go-live, with full payback typically achieved inside the first two quarters through engineering time savings, improved forecast accuracy & lower Databricks compute costs from optimized ingestion patterns.