Dear Analyst #124: Navigating people, politics and analytics solutions at large companies with Alex Kolokolov
Description
We sometimes forget that a large organization is composed of groups and divisions. Within these groups, there are teams and individuals looking to advance their careers. Sometimes at the expense of others. When your advancement depends on the success of your project, the benefits of that project to your company may be suspect and the tools you use to complete that project may not be the best tools for the job. Alex Kolokolov started his journey in data like many of us: in Excel. He moved on to Power BI, PowerPivot, PowerQuery, and building data visualizations for the last 15 years. In this episode, he talks through consulting with a company as the analytics expert only to find out that the the underlying forces at play were company politics. He also discusses strategies to make your line charts tell a better data story.
The state of analytics at companies in traditional industries
Alex consults with large companies in "traditional" industries like oil, gas, and mining companies. The state of analytics and knowledge of analytics is not equal in these companies, according to Alex. You'll come across data science and AI groups at these companies who are, indeed, working on the cutting edge. But then when you approach other departments like HR or operations, they are still quite far from this digital transformation that everyone's talking about.
Alex worked with a mining company where there are cameras that can ID employees using facial recognition when they walk through the door. But when you sit down with the folks who are actually doing the work at the plant, they are still humming along on Excel 2010. Excel 2010! What a time...
Source: dummies.com
In terms of creating dashboards, teams from these companies would consult their IT or tech team to create a report. But then the IT team comes back and says it will take three months to create this report given their current backlog. Hence the reason these companies outsource the analytics training, metrics collection, and dashboarding to people like Alex.
Internal battles for power and platforms
Alex once worked with a government institution and they were building an internal SQL data warehouse before Power BI came on the scene. This specific project was driven by IT as a warehouse solution for the finance department. a few years later, the head of this SQL project became the CIO, but started getting some pushback from the heads of the finance department. It turns out the finance department heads already had their own platform in mind and claimed Microsoft's technology was outdated for their purposes (the finance team wanted to go with Tableau to build out pretty dashboards).
Source: reddit.com
The finance department proceeded to roll out their solution in Tableau and the CFO eventually became the Chief Digital Office and pushed the CIO who was spearheading the SQL project out. The project wasn't about Microsoft vs. Tableau at all. It was all about who was better at playing the game of internal politics and fighting for the resources to get your project across the line.
When digital transformation is 10 years too late
Large companies Alex has worked claimed they went through "digital transformation" but this was back in 2012. When Alex started working with these companies over the last few years, he found that individuals were still using SAP and Excel 2010. It's as if the digital transformation didn't go past 2012,
When you think of your data warehouse, the "semantic layer" may not be the first thing that pops in your mind. Prior to reading Frances O'Rafferty's blog post on this topic, I didn't even know this was a concept that mattered in the data stack. To be honest, the concept is still a bit confusing...
Published 09/10/24
If you could only learn one programming language for the rest of your career, what would be it be? You could Google the most popular programming languages and just pick the one of the top 3 and off you go (FYI they are Python, C++, and C). Or, you could pick measly #10 and build a thriving career...
Published 08/05/24