6 - EVALUATE with Data (Taylor's Version)

Data Rants with Scott Taylor -The Data Whisperer

Validate, integrate, aggregate, interoperate
and then on top of that then you can evaluate
Once you've built this foundation,
then you can start to evaluate
that's where analytics comes in
so that classic phrase “garbage in garbage out”
If you don't have that Foundation of Truth
on the bottom, you're not going
to get adequate meaning
when you roll it up and start to evaluate
Util you've done that,
the evaluation process is a waste of time, right?
That's that analytics delivery without the data foundation.
I love that terminology.
I'm taking it on the road with me
then you get into BI,
then you get into AI
then you get into ML,
then you get into business intelligence.
Then you get into all those kinds of analytics.
It's your data scientists are doing more
data science work than data janitor work
cleaning up all that data
Every BI tool I've ever seen demos really well
because the data is perfect
But if the data is not perfect
somehow it doesn't work
don't start pouring stuff in a
beautiful little visualization graphic
and all kinds of crazy reporting
until you've got those foundational things done.
Otherwise, they're not going to trust that dashboard
that you put in front of the business stakeholders.
You've got to have that foundation first
so you want to make sure you've got
standardized, clean, trusted data
into that evaluation process.
So your analytics and your BI tools
can work at their best efficiency
and get the most value
and the best answers out of it.
Good decisions made on bad data
are just bad decisions you don't know about yet.