Every organization is being asked to “do something with AI.” The vendors selling AI agents assume your analytical work context exists in a form they can use. In most organizations, it doesn’t — not yet. Your analyses live in folders, dashboards, scripts, and individual memory. The agents your leadership is about to deploy need that work to be visible, structured, and connected before they can do anything useful with it.
MyDataWork’s Explorer plan is 90 days, free, no credit card. One user, your own workspace, no team complexity to navigate. We made it 90 days because the work that matters here compounds — the more you catalog, link, and document, the more value the workspace produces, and the more prepared you are for what’s coming next.
Here’s how to use that time.
Your 30-60-90 Plan
Days 1-30 — Get organized
Connect your local folders and any cloud sources (GitHub, dbt, Databricks, Snowflake). Let MyDataWork catalog the work you already have — your Excel models, SQL queries, Power BI files, Python notebooks, Alteryx workflows. Run the Workspace Agent once a week and address what it surfaces.
By day 30, you have a complete picture of your analytical surface area. You’ll likely discover assets you forgot you owned, dependencies you hadn’t named, and gaps in documentation you’d been carrying in your head.
Days 31-60 — Find leverage
Document the use cases your work supports. Set measurable objectives — baseline, current, target — on the analyses that matter most. Link the stakeholders who depend on each one. Use the leverage analysis to find work you can reuse, automate, or retire.
By day 60, your assets connect to the business outcomes they serve. The conversation about why your work matters becomes a conversation grounded in evidence, not memory.
Days 61-90 — Operate strategically
Generate portfolio summaries for your manager and stakeholders. Use the Workspace Agent strategically — let it surface cleanup opportunities, activity gaps, and analytical insights you’d miss on your own. Export your portfolio for the conversations that matter: performance reviews, planning meetings, stakeholder reports.
By day 90, you’re operating with a documented record of what you do, why it matters, and what it’s worth. The conversation about your impact gets easier.
When You’re Ready to Bring Your Team In
Somewhere in those 90 days, you’ll hit a moment. Maybe it’s day 12 when you realize your teammate has rebuilt the same query you already have. Maybe it’s day 47 when your manager asks about team coverage and you can only answer for yourself. Maybe it’s day 73 when your stakeholder asks why three people on your team are working on overlapping analyses without knowing it.
That’s the moment Explorer’s value hits its ceiling. The next step — making your team’s collective work context visible the way you’ve made yours visible — needs the Team plan.
On Team, the same patterns work at scale. The team’s portfolio surfaces duplicate work and shared infrastructure (the dashboard three people depend on, the SQL query everyone references). Aggregate metrics let team leads demonstrate analytical output to leadership. The same private-by-default model lets people catalog comprehensively without exposure anxiety — you choose what to share, and with whom.
You can upgrade to Team at any point during your Explorer trial. Your work transfers; your data carries forward; the workspace you built becomes the foundation the team builds on top of.
Why 90 Days?
We made the trial 90 days because the work this enables compounds. The first 30 days are about getting the picture. The next 30 are about finding the leverage in that picture. The final 30 are about operating from it.
Most catalog tools — and most analytics SaaS — give you 14 days. That’s enough time to evaluate a feature, not enough to build a working practice. The work context layer isn’t a feature to evaluate. It’s a working practice to build. Ninety days is what that takes.
Spend it. Or watch your organization’s AI strategy land somewhere else, without you.
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