On Monday’s episode we were talking about the way to avoid the many pitfalls associated with building an all star in-house analytics and data team.
This shorty episode builds on this by talking about the important skillsets you must look for when hiring your first database administrator!
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Music for the show: Foolish Game / God Don’t Work On Commission by spinmeister (c) copyright 2014 Licensed under a Creative Commons Attribution (3.0) license. http://dig.ccmixter.org/files/spinmeister/46822 Ft: Snowflake
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And on the go. I’m your host Jordan bohall. If you like what you hear, be sure to subscribe lows, get the latest episode. So wherever you get podcast, and if you’d like to stay up to date on everything data couture, be sure to follow us on Twitter at data couture pod. Finally, if you’d like to help support this in future episodes, consider becoming a patron of the podcast through our Patreon email@example.com. forward slash data couture. Now on to the show.
Welcome to the show. I’m your host Jordan and on today’s data bytes, we’re following up on Monday’s episode about how to hire a data analytics team as well as how to avoid some of the common pitfalls with going about getting a data team and the two ways previously mentioned. Today, we’re going to be speaking specifically about how to hire a DB when it comes time to hire a dB. Now if you’re just starting out with your analytics team, you’re not going to want a database administrator and the traditional sense of dB a, you’re going to want someone who has a bit of a more varied skill set. And so when you’re starting to form your data team, you’re going to want somebody who is well versed in the particular technology stack that your company or organization employees. So again, for example, at my company, we employed the.net framework, which is the Microsoft stack of technologies. And so you want to deviate who’s very familiar with stored procedures, sequel, c++, C sharp, those kinds of languages.
Now, when you’re just starting out, you’re going to need to build a number of things. The first is a data warehouse. And there are lots of ways of building a data warehouse. So you can build a very traditional relational data warehouse, you can build relational data warehouse, it’s built on a star schema or a set of star schema, you can build one that involves cubes, you can also go into the Big Data realm and build a data lake, which case you can have all of your structured elements as well as a bunch of you’re unstructured elements like chat and social media feeds and voice data and what have you. Now that decision will be really dependent upon the sort of business you’re in as well as the sort of needs you’re going to have from your analytics team.
When it comes to actually doing the analysis pieces. However, you’re going to need a DB a or a data engineer, if you’re just starting out who can understand the various architecture types, their strengths and weaknesses and why one might be better for your organization than another. And of course, if you’re starting out with relational dB, that doesn’t mean you can’t eventually tack on or include a data lake. So you can build in all those unstructured pieces when your company is ready for them. In any case, this TBA, they’re gonna, they’re gonna hold a role, that’s not a traditional programming role, even though they have to do a lot of the coding and they’re gonna have to be somebody who can really just knock out code at a lightning speed because you’re going to need them to before you hire, or at least before your business intelligence engineer or your visualization engineer can make sense of any of the data, they’re also going to have to deal with requirements that aren’t set in stone.
And so what do I mean by this? I mean, that your typical custom dev shop who’s going to require very rigorous requirements, so they can knock out one by one in a very logical and very structured way? Well, when you’re just starting out, an analytics team requires quite a bit of creativity. And the requirements aren’t going to be quite as obvious as most of us would prefer, honestly. But that’s just the nature of the game at the moment. And so you’re going to have to have somebody who’s not going to get frustrated, and who can deal with various data elements when there’s no metadata available to understand what’s going on with those data elements. And someone who can work well with other business units. Because at the end of the day, chances are you have a lot of siloed data through various business units or verticals within your organization, and lots of those people aren’t going to want to give that data away for free.
And so your DB is going to have to be able to speak intelligently, but also carefully and clearly, to these people who might not be technical at all. And so you have to have a DB who won’t be like a typical developer, and that they can go in front of a large audience sometimes of senior leadership.
And while they’re there, be able to explain away everything they’re doing. And also at the end of it, everyone can leave with an understanding of exactly what’s going on. And this is absolutely essential to one of these first few hires that you make in your analytics team, you you don’t want people coming away, thinking oh, this person thinks they’re so much smarter than me, because at the end of the day, yeah, they’re probably significantly better at the tech side of things. But they know nothing more than likely and let’s be honest about the particular business you know, or that the particular business processes or the problems for that matter that those business units are trying to solve.
And so those people are the true experts in that area. And so by building a common language of respect, and by building up this relationship, you’re setting forward, your team to have the greatest success. This might be foreign to many of you who are looking for a developer, I should say, Excuse the noise of the plane going by I am once again on the road in Vegas for the conference, as I mentioned on Monday. So anyways, back to what I’m saying, this might be very foreign to somebody who’s used to hiring a typical developer. But it’s, it’s part of the requirements for these early stage analytics teams.
Now of course, if your analytics program is in a much greater scale of maturity, if they’ve gone through all of this process already, then yeah, you can hire your typical DB a to help optimize your warehouses that are built also to help optimize at all processes help optimize various views and various tables for your analytics folks to then develop against. And those people are easier I should say to find then this kind of mixed technical, PR interpersonal abilities person speaking of for the state of engineering role, in case I love to hear your thoughts down below. Be sure to subscribe and I will talk to you next time.
That’s it for the show. Thank you for listening. And if you liked what you’ve heard, then consider leaving a comment or like down below. Stay up to date on everything data couture, be sure to follow us on Twitter at data couture pod. consider becoming a firstname.lastname@example.org forward slash data couture music for the podcast. It’s called foolish game. God don’t work on commission by the artist spinmeister us under a Creative Commons Attribution 3.0 license,
writing, editing and production of the podcast is by
your host Jordan bohall.