Connected sources
Bring databases, cloud warehouses, files, web APIs and internal records into a governed source catalogue.
Applications / Data and reporting
Data Hub
Data Hub brings databases, cloud warehouses, files, web APIs and internal records into one governed layer, where teams can preview sources, define relationships, build reusable views and control freshness so every application works from consistent, trusted data.
Highlights
01 — 05
01Visual saved-view builder02Relationships and joins03Calculated fields04Reuse across applications05Connection catalogue
Highlights · 01
Build a client pipeline with meaningful column names and a live preview of the records that will feed studio reports.Visual saved-view builder
Select data, choose fields, add filters and save a reusable business view.
Highlights · 02
Model five connected delivery tables and their field-level relationships on the ERD canvas.Relationships and joins
Connect related records and show the useful combined result.
Highlights · 03
Calculate the planning window between brief receipt and launch, and present the result as whole days.Calculated fields
Build a new business measure from source values with a formula and preview.
Highlights · 04
Reuse the same Client Pipeline view in the weekly document, client-intelligence dashboard and studio workflow.Reuse across applications
Use one saved view in a dashboard, document and workflow.
Highlights · 05
Choose a cloud database or API-backed source while retaining the studio’s uploaded delivery data in the same Data Hub.Connection catalogue
Show the supported database, file and API connection choices with an actual configured source.
A closer look
06 — 20
06Uploaded file data07Form response data08Table and schema browsing09Live data preview10Field selection and naming11Filter groups12Sorting and aggregation13Date calculations14Text and category formulas15SQL inspection and authoring16Cache policy17Runtime filters and selections18View versions19Dependency and consumer information20Data export
A closer look · 06
The uploaded studio delivery file becomes a browsable dataset with six engagements, named leads, budgets and delivery progress.Uploaded file data
Bring supported tabular files into the same browsing and query experience.
A closer look · 07
Browse the submitted client briefs as reporting data, including the business challenge and intended audience.Form response data
Use submitted form records as a source for reporting and automation.
A closer look · 08
Inspect the delivery dataset’s columns and sample records before choosing the fields for a reusable view.Table and schema browsing
Inspect available tables, columns and their types before building a view.
A closer look · 09
Inspect the seven submitted briefs with client contacts, sector, launch dates and investment ranges.Live data preview
Inspect real rows and confirm the chosen source contains the required information.
A closer look · 10
Keep source fields intact while assigning clear output names and display labels for report readers.Field selection and naming
Present meaningful business columns instead of exposing every raw field.
A closer look · 11
Combine a future launch date with a hospitality-sector filter, leaving four relevant briefs in chronological order.Filter groups
Define the criteria that make a saved view useful to a particular business question.
A closer look · 12
Summarise four upcoming hospitality briefs into three distinct client projects, with the calculated result visible in the preview.Sorting and aggregation
Order results and summarise records for downstream consumers.
A closer look · 13
Derive a launch-month reporting bucket directly from each brief’s launch date.Date calculations
Work with dates through the formula tools rather than manually maintaining derived columns.
A closer look · 14
Combine the client and primary contact into a consistent label for review lists and handover reports.Text and category formulas
Combine labels or classify records into useful reporting groups.
A closer look · 15
Inspect the generated SQL for selected columns, calculated fields, filters and launch-date ordering.SQL inspection and authoring
Inspect or edit the supported SQL representation in the saved-view workflow.
A closer look · 16
Reuse the launch-planning results for fifteen minutes while allowing an explicit refresh when the team needs current data.Cache policy
Choose how freshness and cached results should be handled for a dataset or view.
A closer look · 17
Select Cedar House in the consuming dashboard to focus the shared view on its two stakeholder briefs.Runtime filters and selections
Let consuming applications ask for a relevant subset of the same underlying data.
A closer look · 18
Retain the original planning definition alongside a refined version, with an option to restore an earlier version as a new change.View versions
Inspect earlier definitions and maintain a history of changes to a shared view.
A closer look · 19
Inspect the forms, workflows and reporting consumers of the shared client pipeline before changing its definition.Dependency and consumer information
See where a view is used before changing a shared data definition.
A closer look · 20
Export the planning result as CSV, JSON or line-delimited JSON, with clear options for the full result or visible rows.Data export
Export the displayed/query result using the supported formats and options.
Additional Details
The main areas Data Hub brings together.
Dataset exploration
Browse schemas, preview records and understand fields before a source is reused elsewhere.
Relationships and semantics
Define how data connects and add the meaning teams need to use it consistently.
Reusable views
Build filtered, sorted and calculated views that applications can reuse without rebuilding the same logic.
Freshness and lineage
Control caching and availability while retaining context about where a view came from and where it is used.
Governed exchange
Support controlled export, writeback and automation where operational processes need data to move.