-By Alex Yeung
As a side hobby, I regularly cook. Apparently, it’s quite popular. It’s certainly lighter, less salty, less sugary, and saves a small fortune in eating out.
“You should sell this,” regularly pops up in conversation. This led me to think, “let’s see if I can scale up.”
So, I set up a house party. Shopped around for the best chicken, best coffee beans, and a bottle of Tokaji to go with iles flottantes.
After saying goodbye to well-fed guests and looking over at the pile of cutlery and crockery left behind, I contemplated this experiment and decided that no, I was not going to give up the day job.
It should have been pretty obvious really. As you scale up you have to consider the impact of quantities on pipelines, bottlenecks, and workflow.
Data is pretty similar in that regard. Anyone can set up a spreadsheet, but the demands of users will mean that this spreadsheet set up will soon need to be replaced by a shared database, and perhaps an SQL server. As people want to do more and more things to this database, this will need to be scaled up to handle additional burdens, bring in greater computation power.
Before long, there will be a need to set up a fully-fledged, responsive database with APIs and machine learning that can plug into another database or integrate another dataset is a whole new game altogether.
All the while, more people are needed to create, curate, and manage, raising the need to bring in new skill sets and extra resources.
This can take your teams outside of their core functions, and ultimately slow your product’s route to market.
But what if the data was there, on hand?
What if the infrastructure was already present to set up a database with little work?
This is where we come in.
With our team of seasoned developers and an architecture that can handle millions of rows of data going back years at a time, your teams can have immediate access to a comprehensive, global dataset around a $13 trillion marketplace in weeks.
To find out more about our data and how we can help, get in touch.