Attending the yearly Tableau conference has been something I have done for the past 5 years. I would guesstimate it fuels my data brain for a full 12 months.
No need to convince anyone about the importance of data in the 15,000 person crowd. Not just any data--the right data. I will share insights from large health systems, survey analysts, and granular panel discussions over the next few months or so.
But I thought it would be timely to share a summary of data myths. Full disclosure. This post is late. I started writing a week ago but had to prepare to attend ISPOR/ISPE Summit on Real-World Evidence in Health Care Decision Making in DC. More on that to come as well...
Data myths to cross off your list of excuses...inspired by keynote by Adam Selipsky CEO Tableau
AI will replace the analyst (don't forget algorithms contain biases} AI will assist, not replace. Read the Artificial Intelligence And Life in 2030: One hundred year study on Artificial Intelligence from Stanford.
"Human intelligence has no match in the biological and artificial worlds for sheer versatility, with the abilities “to reason, achieve goals, understand and generate language... create art and music, and even write histories.”
Data is only for analysts—Data is the world's most valuable resource--not oil. Forbes even went a step beyond-- Tableau is listed as the most in demand data skill.
Data governance means “no”—No Data for You! It’s valuable. It’s the new oil. True data governance means secure enablement not restriction or impeded access.
Operate within reasonable parameters. Everything appears to be deserving of a catch phrase. The underground data economy is the latest trend and as far as I can tell it refers to data analysis happening without IT. Excel is already doing this so there is no need to panic!
BI platforms take away power from people.
Using the right tools to answer your data questions can help people see and understand data.
Often when I am asked a data question I think of types of data sources that contain similar information. It would be nice if data existed in a neat little package with a pretty bow but often it looks rough.
We need to abide by good practices for real world data so it will be useful for decision making. There are many out there that consider real world data to be inferior to data captured in randomized controlled trials. Let's face it, to quote Deborah Zarin, MD from the NIH "they are both sausage making"--Its okay to trust but it is more important to verify.
Data has to be curated to access insight.