Why is Data Analytics on the cloud so hard?
TLDR: Because the Cloud is still poorly understood or managed well
Lift and Shift adds complexity and costs
Contrary to 'conventional' thinking, just moving on-prem to the cloud is rarely worth the time and expense. Operating costs can actually go up significantly.
Extracting real value from the cloud is difficult
Even with a specific cloud in mind, designing a framework and the supporting DevOps, is hard because of hands-on expertise gaps.
The jargon and cutting-edge geek-speak is a minefield
The cloud landscape is unfortunately littered with an alphabet soup of unproven technologies, and even outright false claims. Sifting the wheat from the chaff boils down to experience - that someone making the move to the Cloud is unlikely to have.
The skill shortage at the top is far more acute than it appears
Getting hold of Cloud Architects with hands-on expertise in designing efficient and effective frameworks is a tough call. Working with large consulting firms who have these skills will mean months of billable time.
Engagement Road Map
Three steps to a great cloud framework for data analytics!
A no-cost engagement to understand your current tool set, preferred cloud providers, identify challenges and business objective to be met. We also agree on the scope and deliverables. Typically takes one week.
Here we deliver a fully functional framework (data lake + ELT + data warehouse) installed on your cloud account. You are ready for reporting using an SQL based reporting tool on sample data. Typically takes six weeks.
We train you on the fully functional cloud data platform, including data pipelines, orchestration, transformations - with the required metadata and devops management layer. Typically takes two weeks.
Transition to data analytics on cloud simpler!