DatriseAI-first ETL

MyCase to Sisense Integration

AI-first ETL from MyCase into Sisense. Governed entities, incremental sync, typed landing tables.

How Datrise loads MyCase into Sisense

Datrise syncs MyCase's cases, clients, leads, time entries, invoices, and documents into Sisense as modeled tables for a Sisense ElastiCube (or live connection). Flexible or custom fields land in flattened columns for the cube, and timestamps such as created, updated, and status changes are typed as date/time fields.

Sync is incremental: Datrise uses incremental ElastiCube builds on changed rows, so re-runs update only what changed. Date-partitioned facts to speed cube builds. ElastiCube is an in-memory model, so Datrise lands incremental, build-friendly tables rather than forcing full rebuilds.

Ideal for embedded analytics on an in-memory engine.

Endpoints

MyCase: Case management and client intake for law firms.

Sisense: Analytics platform with elastic data models and embedded analytics.

How MyCase entities map to Sisense

MyCase entitySisense objectNotes
casesmycase_casesid PK · custom fields → flattened columns for the cube
clientsmycase_clientsid PK · linked to mycase_cases
leadsmycase_leadsid PK · linked to mycase_cases
time entriesmycase_time_entriesid PK · linked to mycase_cases

FAQ

How does Datrise handle MyCase's custom fields in Sisense?

Flexible values are stored as flattened columns for the cube, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Sisense types.

How does the MyCase to Sisense sync stay up to date?

It runs incrementally — Datrise uses incremental ElastiCube builds on changed rows.

Related pipelines

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