Data Strategy Briefing

We aim for 60 minutes, which usually breaks down into: introductions (5 mins), context (5 mins), briefing (35 mins) end-to-end demo (15 mins), but we try to allow a buffer so that the session can overrun, as we find that once the conversation starts flowing, it can easily last 90 minutes!

Absolutely! You can either add some context to the booking form, or you can reply to the meeting invite and add some background, attach architecture diagrams. The more information we have in advance, the more we can tailor the briefing to your specific needs.

By default we operate under Chatham House Rule, but if you prefer, we can issue a mutual NDA to sign. If you require your own organisations NDA to be signed, we can do that too, but it may take a little longer as we'll have to review the contract.

Feel free to invite as many people as you feel comfortable with. The majority of people who book want a 1-2-1 briefing as they want a safe space where they can speak about their challenges candidly and without judgement. We have run the session for different groups within a single organisation, so that it could be tailored to the specific needs of each group. We'll also provide you with a recording of the briefing, which you are free to share with your colleages.

Absolutely not! There's no obligation to engage with us in any way, and we're not going to try and sell you anything. We don't even have a sales team! The two quotes on this page are from people who had briefings, but aren't our customers. We love to talk and share knowledge, which you may have noticed if you read our blog, watch any of our talks, consume any of our open source projects, or subscribe to our Azure Weekly or Power BI Weekly newsletters. We find it really useful to talk to external organisations about their data challenges - it helps us better understand the marketplace. That being said, often the participants get a huge amount of value from the session, and the last question we get asked is "how can we work together?"

No. We have experience with Databricks, Snowflake, Azure Synapse Analytics, Power BI, SQL Server, Cosmos DB and many other data platforms and tools. We often work in heterogenous data estates, where teams have selected various "best of breed" solutions to solve specific problems. But our "We help small teams achieve big things" mantra comes into play here, as we find that data teams are often under-resourced for the demands placed upon them, and we advocate for any solution which alleviates low value infrastructure work, and allows the team to focus on delivering high business value activities. This is why we love Wardley Maps, as they help to visualise between "Genesis" or "Custom Built", which tend to require large amount of effort, and "Product" and "Commodity" which tends to require less effort, and deliver more value.