Hi Tristan and Drew. It is fascinating how the problems remain the same, but the tools are much nicer and the costs are down 100x over the past two decades! Connecting people, gaining trust and building a culture is critical to achieving ROI! A culture I learned the most from was Netflix, "it isn't wrong to be wrong, it is ONLY wrong to NOT learn and take action!"
I worked at Brio Technology in the 1990s (the easiest BI tool of its day), Loudcloud, SAS, and Netflix in the 2000s, and Tableau in the 2010s. The core problems remain unchanged. Connecting data scientists, analysts, and data engineers to the critical issues that possess the potential to produce high ROI. Even more important, connecting them and building trust in the teams of the business that WILL actually act upon insights and iteratively build upon successes and failures.
So, quality data must be collected, socialized, enhanced, analyzed, and optimized. This is the process that is needed. But at those "99% companies," it is often the need to build a culture that can admit/accept being "wrong" and will actively implement changes using the data insights gathered.
Ironically, vendor sales efforts are often key to helping achieve liftoff in these cultural shifts. Why? When executives hear the sales pitch and invest the dollars, it can signal to the line of business managers to use the new systems to drive change. By forcing the new approach, it enables team members to become part of the process as tools designed to be accessible by line-of-business analysts along with advanced data scientists and engineers can help build trust and collaboration.
I appreciate the openness and sharing some of the Data Council highlights!
> Today though, that same group is now composed of people building or investing in data tools.
As you say, this benefits the broader community, but at the expense of the core community[1], which will have to be considered effectively disbanded due to new allegiances which are probably on average less encouraging of vulnerability.
I guess this is what maturity looks like for the scene, and thus the "scenius"[2] is finished - does this mean the tech and process in this space is reaching its approximate final form?
1- dare I say OG? I only recognise some of those names lol
Hi Tristan and Drew. It is fascinating how the problems remain the same, but the tools are much nicer and the costs are down 100x over the past two decades! Connecting people, gaining trust and building a culture is critical to achieving ROI! A culture I learned the most from was Netflix, "it isn't wrong to be wrong, it is ONLY wrong to NOT learn and take action!"
I worked at Brio Technology in the 1990s (the easiest BI tool of its day), Loudcloud, SAS, and Netflix in the 2000s, and Tableau in the 2010s. The core problems remain unchanged. Connecting data scientists, analysts, and data engineers to the critical issues that possess the potential to produce high ROI. Even more important, connecting them and building trust in the teams of the business that WILL actually act upon insights and iteratively build upon successes and failures.
So, quality data must be collected, socialized, enhanced, analyzed, and optimized. This is the process that is needed. But at those "99% companies," it is often the need to build a culture that can admit/accept being "wrong" and will actively implement changes using the data insights gathered.
Ironically, vendor sales efforts are often key to helping achieve liftoff in these cultural shifts. Why? When executives hear the sales pitch and invest the dollars, it can signal to the line of business managers to use the new systems to drive change. By forcing the new approach, it enables team members to become part of the process as tools designed to be accessible by line-of-business analysts along with advanced data scientists and engineers can help build trust and collaboration.
I appreciate the openness and sharing some of the Data Council highlights!
Great snippet on what went down, thanks Drew
> Today though, that same group is now composed of people building or investing in data tools.
As you say, this benefits the broader community, but at the expense of the core community[1], which will have to be considered effectively disbanded due to new allegiances which are probably on average less encouraging of vulnerability.
I guess this is what maturity looks like for the scene, and thus the "scenius"[2] is finished - does this mean the tech and process in this space is reaching its approximate final form?
1- dare I say OG? I only recognise some of those names lol
2- https://perell.com/fellowship/conjuring-scenius/