Your best customerintelligence sits in Databricks.Our Databricks consultingservices make sure it reaches your campaigns.

For most mid-market brands with a mature Databricks environment, the answer is no. You already have the compute and storage. We configure Hightouch or Census as your activation layer, connecting Databricks directly to your MAPs and ad platforms via Reverse ETL. This composable approach is faster, cheaper, and more flexible than layering a full CDP on top of an existing warehouse. We assess your maturity level and recommend accordingly; we have no vendor bias toward any CDP.

We use Hightouch's native Databricks connector to sync computed audiences, propensity scores, and calculated traits from your Delta tables directly into Braze Custom Attributes, SFMC Data Extensions, Klaviyo properties, or HubSpot contact fields. For real-time use cases, Hightouch Live Events enables sub-60-second delivery from warehouse event to MAP trigger. We handle schema mapping, sync scheduling, and failure alerting as part of the engagement.

Yes. We build data models, dbt transformations, and Hightouch audience configurations so marketing teams can access precomputed, ready-to-use segments and attributes — no SQL required. For self-serve audience building, Hightouch's Audience Hub provides a marketer-friendly UI backed by your Databricks warehouse. We also set up Databricks SQL dashboards for marketing performance tracking, accessible to non-engineers.

We build identity frameworks in Databricks using deterministic matching (email, phone, device ID) and probabilistic stitching for anonymous signals. The resulting identity graph is materialized as a Delta table and refreshed on a schedule appropriate to your event volumes — typically daily for full graph rebuilds with incremental updates every few hours. This powers consistent suppression, frequency capping, and personalization across every MAP we connect.

At three levels.

1. Predictive models: churn prediction, LTV scoring, and propensity-to-purchase built with MLflow and optionally Databricks AutoML — scores sync to MAPs via Hightouch.
2. Agent Bricks (Databricks' 2025/26 AI agent suite): we are tracking early access for agentic next-best-action workflows.
3. Databricks Cortex: LLM-powered SQL generation and natural-language analytics for marketing ops teams. We prioritize use cases by revenue impact and implement in phases.

The Foundation Sprint of our Databricks integration service delivers core pipelines, including Databricks Workflows, Hightouch connection, and the first audience live in your MAP within 6–8 weeks.

ML use cases (churn prediction, LTV scoring via MLflow) add 3–4 weeks.

We run a parallel validation window before full cutover to ensure data parity. Advanced use cases, such as Agent Bricks and real-time DLT pipelines, are scoped separately.

We implement three layers of quality control:

1. Schema validation and anomaly detection on incoming event streams using Databricks Expectations in DLT pipelines
2. Hightouch sync monitoring with failure alerting and automatic retry logic
3. A parallel-run validation period before cutover, comparing warehouse-computed segments against the existing source of truth to confirm <0.5% variance.

Every audience and attribute used in campaigns has a documented freshness SLA.

Yes, we have delivered Databricks activation integrations across all three.

• Braze via Hightouch Custom Attribute sync and Connected Content for real-time personalization.
• Salesforce via both Data Cloud (for SFMC-native stacks) and direct Hightouch-to-Sales-Cloud enrichment.
• HubSpot via Census or Hightouch contact property updates.

None of this requires replacing your existing MAP — Databricks becomes the intelligence layer feeding into whatever channels you already operate.

Three things.

• First, we own the MAP layer — most data shops deliver a pipeline and hand off. Mavlers builds the Databricks architecture, configures Braze, SFMC, or Klaviyo downstream, and builds the lifecycle journeys that use the data.
• Second, we are lifecycle marketers who happen to be strong data engineers, not the other way around. Every data decision we make is driven by a campaign use case.
• Third, we offer a single SLA for data infrastructure and marketing execution; no handoff between a data agency and a marketing agency.