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Map what you have. Move what's next. Keep the map.

Symbric Audits and Migration is a managed audit of your data estate, then the migration: what's there, what's actually used, and what's safe to drop, with evidence for each call.

Audit plan ready inside two weeks of access.

Every drop recommendation ships with the evidence behind it.

The map keeps updating after handover.

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audit / estate_mapread window 90d

412

fields scanned

239

read

173

flagged for review

  • opportunity.legacy_score0 readsFLAGGED
  • account.region_coderead by 2 pipelinesKEEP

01

What a mapped audit changes before you migrate.

Without Symbric

  • A hand-written mapping document, already stale by the time it ships.
  • Everything migrates, because nobody is certain what's still read.
  • The definitions leave with the people who held them.
  • Cutover weekend is the first real test.
  • You pay for the map once, then again when it drifts.

With Symbric

  • A map built from the schema and how people actually use it.
  • A drop list. Each candidate names who read the field, how often, and whether that was a person or a pipeline.
  • Definitions get written down as the work happens.
  • A full dry run against a target instance runs first.
  • The map keeps updating after the work ends.

02

What the audit reads before anything moves.

The audit reads the schema and the usage, then reads the gap between them.

schema scan

tables, columns, objects, automations

  • Dead fields and empty objects, named and located
  • Seat and licence usage, one system at a time

the gap

  • Automation nobody currently on the team can explain
  • Data that should exist and does not
  • Gaps between systems a schema scan alone misses

usage signal

app logs, pipeline runs, who opens what

  • How people actually use each system, mapped back to its schema
  • The blast radius of a change, before it happens

03

The kinds of work.

  • CRM to CRM

    The field mapping is the easy part. The hard part is the workflow logic buried in automations, and the process a rep built around a quirk nobody wrote down.

  • Merging two data estates

    Two systems of record rarely agree on what a customer is. The work is reconciling identity across both before either dataset can be trusted.

  • Warehouse and semantic layer replatforms

    Every dashboard built on the old semantic layer has to land on new tables without its answer changing underneath it.

04

How the work runs.

read-only on live systems

  1. access
  2. map
  3. dry run

writes to live systems

  1. sign-off
  2. migrate
  1. Phase 01

    Connect, then map.

    We connect to the sources with read-only access and build the map from the schema and observed usage together.

    Phase 01 outputinside two weeks of access

    1. mapSystems map, every source and destination named
    2. dropDrop list, each candidate with its evidence
    3. docMapping document, field to field
    4. planProposed phases and sequencing
  2. Phase 02

    Dry run, then migrate.

    A full run against a target instance comes before sign-off. Once approved, the migration runs with your team, for your team, or alongside whoever you already have. Priced per project. The software continues on a normal subscription afterward.

    Phase 02 outputpriced per project

    1. dry runFull migration rehearsed against a target instance
    2. sign-offChecked against the mapping document before anything moves
    3. migrateThe migration runs, on the agreed timeline
    4. handoverThe software continues on a normal subscription

05

What ships, and how we keep it safe to run.

Delivered

  • An editable systems map
  • An integration flow graph
  • A downstream impact map for any field or process
  • A ranked drop list with evidence
  • A seat and licence review
  • Source-to-destination coverage views
  • Column-level diffs
  • A semantic layer rebuilt on the destination
  • A dry run report

Guardrails

  • Nothing runs against a live system before sign-off and a dry run
  • A person reviews every mapping before it ships
  • Access starts read-only and least-privilege. Elevated permissions apply only to an approved phase, then get revoked
  • Access follows your own roles, personal data is masked, and writes are logged
  • Plain tables in your own warehouse. No proprietary formats

06

What it connects to.

Systems of record

  • Salesforce
  • HubSpot
  • NetSuite
  • Zendesk

Databases and files

  • Postgres
  • MySQL
  • SQL Server
  • S3

Destination warehouses

  • Snowflake
  • BigQuery
  • Databricks
  • dbt

See your data estate mapped.

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