Short, focused walkthroughs — from cataloging your work to proving its value and scoping an AI agent. Pick a topic and press play.
The idea behind MyDataWork: catalog your analytical work across every tool by metadata alone, organize it into use cases with measurable outcomes, and see the lineage that connects it — structure that supports the freedom in how data workers actually work.
Try now →A workspace that catalogs your data work and tracks the value it delivers — shown across a sample workspace of nineteen assets, seven tools, and six use cases.
Try now →How activating a Solution Pack creates pre-built starter use cases grouped under an Initiative, with editable objectives and Jira integration.
Try now →How scattered analytics tools consolidate into one catalog indexed by metadata — asset records, lineage previews, and indexing via the Windows Connector and cloud connections.
Try now →Inflation, weather, employment, energy prices, demographics — published free, and most teams never get time to look. MyDataWork reads the shape of a use case, never your data, shows you which public sources fit it, and hands you a connection recipe you run in your own environment.
Try now →The anatomy of a use case: Overview, Objectives & Progress with automatic calculation, Assets & People linking, and an Action Plan with AI recommendations.
Try now →Statistical safeguards — median-based analysis and outlier detection — that let you defend aggregated portfolio value.
Try now →A leadership view that rolls your team's tools, use cases, and delivered value into one picture of your estate — a tool portfolio, capability map, dependencies, and change-impact by tool. Deterministic, aggregate, and admin-only.
Try now →Ask an agent what drove revenue growth last quarter and it will answer — but seven catalogued assets carry the name, four of them across four different tools, and the “semantic layer” turns out to be a spreadsheet last touched by someone who has left. Data context tells an agent what the numbers mean; work context tells it which work matters, who owns it, and what breaks when it changes. Ends on a scoped, revocable, metadata-only grant to an agent, with a preview of exactly what it receives. Representative sample data; metadata only.
Try now →Opt-in, admin-controlled AI that works from metadata and context alone — use-case descriptions, asset names, progress notes, lineage, value figures, and stakeholder roles.
Try now →Automated, rule-based monitoring that builds a proactive worklist organized into Insight, Activity, and Cleanup.
Try now →Scoping agentic use cases across your systems using tool metadata — never your data — and exporting a governance brief.
Try now →A supplier and a manufacturer weigh a joint demand forecast — the collaboration that usually dies before it starts. Two companies work in one Team workspace on different email domains, each publishing only the assets it chooses, with lineage running from the supplier’s forecast into the manufacturer’s inventory model. Private by default, revocable, logged. Representative sample data; metadata only.
Try now →Team workspaces where analysts share datasets without duplication while keeping independent use-case ownership.
Try now →A leadership view that rolls your team's tools, use cases, and delivered value into one picture of your estate — a tool portfolio, capability map, dependencies, and change-impact by tool. Deterministic, aggregate, and admin-only.
Try now →A headcount and OPEX planning use case across Excel, CSV, SQL, and Power BI — turning scattered assets into a defensible portfolio piece.
Try now →Scattered forecasting across spreadsheets becomes a living system that stays with the work and keeps surfacing what's next.
Try now →Capturing an analytical study as a reusable record — linking models, data, assumptions, and stakeholders, with external dataset discovery.
Try now →A commercial team at a fictional consumer-products company turns scattered onboarding, order-entry, and forecasting work into one connected estate — lineage that traces a forecast problem upstream, team sharing, live AI recommendations, and a leadership roll-up in Architecture & Value. Representative sample data; metadata only.
Try now →