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ANL-15

Advanced Analytics Implementation

Turn security telemetry, customer data, and operational signals into measurable, governed analytics products.

// Overview

We design and stand up the data plumbing. Warehouses, transformations, dashboards, and model pipelines. With governance and access controls baked in from day one.

Built so your analysts spend time on questions, not on broken pipelines.

Common stacks: Snowflake / BigQuery / Databricks, dbt, Fivetran / Airbyte, Looker / Metabase / Sigma.

// Who it's for

Built for teams that look like this.

  • Companies with data in 5+ SaaS tools and no warehouse
  • Teams running on brittle spreadsheets for KPI reporting
  • Security teams trying to correlate telemetry across vendors

// How we engage

A four-phase engagement.

  1. 01 · Discovery

    Two-week scoping with stakeholders, existing tooling review, and a written engagement plan with milestones, named leads, and success metrics.

  2. 02 · Baseline

    Measure current state against your environment. Not a generic benchmark. And surface the two or three controls that will move the needle first.

  3. 03 · Implement

    Hands-on work alongside your team. We ship in two-week increments with weekly written status and a running risk register.

  4. 04 · Operate

    Move from project to program. Quarterly business reviews, KPI dashboards, and an always-on Slack/Teams channel for your team.

// FAQ

Common questions.

Do you bring engineers or just architecture?

Both. Most engagements include hands-on dbt / pipeline work alongside architecture.

Snowflake or BigQuery?

Either. We pick based on existing cloud commitment, data volumes, and team skills. Not vendor preference.

Where does ML fit?

ML pipelines are scaffolded once the foundation is solid. We don't recommend ML before the underlying data layer is trustworthy.

Ready to scope Advanced Analytics Implementation?

A free 20-minute call gets you a written scoping note, named lead, and rough quote. No procurement loop required.