On September 3, the CompTIA Volley podcast focused on the steps companies need to take as they build their data capabilities. Senior Director, Industry Analysis, Carolyn April and Senior Director, Technology Analysis, Seth Robinson say most companies need to start with building comprehensive plans for all their data, including storage options, classification schemes and breaking down data silos. From there, they can move into the analysis that adds new value.
Businesses may have to explore many different options for adding data skills, since they are often looking for a significant amount of job experience. Individuals interested in a role in data analysis may have the necessary business experience but lack specific technical skills, which is where training and certification can play a role.
Listen to the full podcast using the embedded player below, or keep scrolling to read the edited transcript.
Carolyn: Today, we're going to talk about data. Seth, you've got this very cool new white paper, Closing the Data Skills Gap, that I enjoyed. It's about how important data is and where it functions within our work environments. You also talk about the demand for data skills. Why don’t you kick it off?
Seth: The reason I wrote the paper is that the certification business is starting to move into the data space. Next year, CompTIA is launching a brand-new certification called CompTIA Data+.* It's targeting data analysts, and that's a new space for us. We've traditionally been focused on the infrastructure and the cybersecurity space. That covers about half of the IT world – more than half if we’re just talking about the number of workers out there – but half in terms of the different disciplines that we've defined in our functional IT framework.
That framework started with infrastructure. Many people still think of IT as infrastructure. There's lots of people working in infrastructure, like help desk [technicians], server administrators and network administrators. It does provide the foundation for building your architecture and your technology.
The next biggest one, which is probably the biggest by volume, is software development. This is where companies layer on some value on top of that base infrastructure. They're building out the applications they need and there's a lot of customization going on. That’s the value layer, and a lot of companies have done that for a long time. Now more companies are getting into software development.
That's number one and number two, and then you have cybersecurity, which has really been developing as its own discipline for maybe the past 20 years. I would say cybersecurity as a discipline is well on its way to maturity.
The last one is the data discipline. I don't think it's nearly as mature as the security discipline. That said, the white paper starts there and sets it all up. It talks about the ways that companies are starting to form data teams. They may have a chief data officer, or the data specialists may be spread throughout the business, both in the IT function and in the business units. There are a lot of different ways companies are doing this.
We actually have a front row seat at CompTIA because we do have a data team. We have some data specialists, and not too many companies that are our size would have those. It’s unique to be able to see how those roles integrate with the overall business and get some insights into where businesses are probably heading with their data teams.
But yes, data as a discipline is really coming into its own. That's the starting point for talking about the different roles there may be and the different skills that companies will need.
Carolyn: When I think about data, it's sort of a catch basin for a whole bunch of things. It's just one word, but there are now a million skills that need to be applied in order to tackle it correctly. I sort of think of data, as fathoming the size of the universe.
When you start to think about it, it can make your head hurt. So, before we get into some of the really detailed information about skills, when you think about data, how do you define it?
Seth: I think the way that you described but there is pretty accurate. It’s this vast ocean of digital information that a business might have. In a lot of cases, when businesses are thinking about wanting to get value out of their data, they are starting from a limited viewpoint.
They might say, we've got this set of customer data and we want to get more value out of it. I think the real value, and where it becomes very complicated for companies, is the value isn't in taking that one data set and trying to massage it in different ways. The value is in taking that data set and putting it up against every other data set you have, and looking for those connections that might not be obvious.
If you haven't been managing your data very well, it becomes very difficult to figure out how to correlate it all, or determine which data is important and which data is not important. That’s where a lot of companies are today. They know they might have a data set. This is where they might be saying, we need a data analyst to tell us what we can get out of this data set.
But in reality, they need to start at the beginning and ask themselves how they manage their data. How do they structure it? How are they dealing with the storage? How are they pulling it all together? How are they classifying the data? And then how are they analyzing it?
That's a much more advanced view. But when you talk about the companies that are on the leading edge of this, they’re trying to manage the data and mine it and get insights out of it. It’s this huge, hairy problem. And that's why you need specialists, but why you need an organization-wide approach to dealing with data.
Carolyn: I'm curious, because we did talk a lot about big data five years ago, and then that term sort of went away. Now, in this white paper, you've written there are organizations that recognize a database administrator is not sufficient. In a relational database, you can collect all kinds of information, but it can live in silos all over your organization – and then you're not really doing much with it. So, how to exploit it becomes the next question.
I think most companies aren't there yet. I follow mostly small companies and SMBs, and they have a lot of data. But I don't think they are positioned to know what to do and how to be able to hire the people that can take advantage of it. I guess that it starts at the larger firms and then trickles down to those smaller firms. But I was really interested in the number of job role types and the very fine delineations between them and what they do.
It looks like we're moving away from the database administrator role to employing all the specialists and putting analytics at the forefront. Let’s talk about these roles, and some of the skills that many companies are looking for right now.
Seth: The role that I've mentioned a few times here, and that I think most companies are heading toward, and the role that we're targeting with CompTIA Data+ is the data analyst.
Again, a lot of companies know they have the data and want it analyzed. They’re not starting with how to manage it. There may also be companies that don't have any kind of data specialist at all. They think they need a data analyst first, but they should be looking for a database administrator first.
There are three main roles that I defined in this white paper:
Originally, I thought that data analysts and data scientists were kind of lumped together. But as I looked at the job postings, you do see a difference. Data scientists need to understand statistics, algorithms and machine learning. Whereas the data analyst is a little bit more traditional. They have experience working with SQL and databases, but they also have the analytic and business skills. They are two distinct roles. A database administrator sits a little bit more on the infrastructure side.
The bottom line is, companies shouldn't only be focused on the data analyst role. Instead, they need to understand that data needs to be managed and decide if that falls to the infrastructure team or the database administrator. Or maybe it’s a third party they hire to take on that data management part, and then keep some of the analysis in house. There’s lots of ways to do it. But these roles are the primary functions we see in terms of the volume of job postings out there.
When I was writing the white paper, I was struck by the number of companies that are not doing much data work whatsoever. The other thing I found interesting is how willing companies are to look beyond requiring a four-year degree. Instead, they're really looking for somebody with a skill set. That could be someone who has earned a certification.
We’re seeing companies that are willing to think outside the box, but at the same time, they're looking for experience. There’s some information in the white paper about the level of experience that companies think they want out of any data specialists that they might be hiring. And it's clearly not entry level.
Carolyn: If everyone's looking for a data analyst with 10 years of experience, the supply is going to run short pretty quickly. Companies are having to think about how they are building these teams. And as they're thinking about building, I think they'll find that those roles are not necessarily a linear pathway.
It’s not that someone has to start as a database administrator and then move into data analytics. You could have empty roles in both the database administration and the infrastructure side as well as the analytic side. But those empty roles only mean they are the first data job available. It doesn't necessarily mean that you can do a two-week boot camp and step into a data analyst role – you need a fair amount of experience.
For an analyst that might be on the business side, you might have somebody that's been sitting in a business unit for a while who wants to specialize in data. They probably have a lot of experience, but may need to pick up a few skills. That's where a certification or some training can really fill those gaps. I think there's going to be a fair amount of that type of demand out there, even as companies are thinking about what an entry-level data role looks like.
Seth: I agree. Companies who really want to fill these roles internally could be plucking somebody who has been a business analyst within the organization and has an interest in data. But that's going to require the company to provide some resources that will help train that employee. I think that's something that smart companies will do, as opposed to putting the burden on the employee themselves.
Larger companies should be able to send an employee off and let them get whatever credential or certification they need. That would just be a good business practice. There are probably two streams here: hiring from the outside and also building people up from the inside within the organization.
Carolyn: It's important to understand which skills you need to build up. When you look at data analyst, job postings, many of the skills listed could bleed into both of the other roles. For example, some of the statistics and machine learning skills.
But more than that, you've got some database administrator skills, like knowing how to manipulate databases using SQL or other methods. If we're focusing on real-time analytics, then I think that leads them down a path of asking which types of data structures do you know and which types of manipulation are going to be best suited for real-time analytics. That might be an investment.
It's almost like cybersecurity. Just like you can't get perfect security on every piece of your IT architecture, you probably can't get real-time heavy-duty analytics on every piece of data that you have in your in your organization. And that's where you have to start classifying the data and understanding which data has the most value.
Again, all of these skills could fit into an analyst role. Or companies may want to expand their data team and hire a database administrator that's managing the data, helping set up the structures and maybe building the policies around them.
This wasn't part of the white paper, but in my most recent study on the state of the channel, we always ask: What's in your portfolio? What are you selling today? What do you expect to sell in the next couple of years? And slowly but surely, data analytics has crept up the list, and it's pretty high this year.
I'm wondering what your take is on the viability of companies? They're trying to build their data function within their organization, and I'm looking for people with the right skills to look to a third party to help them with that, because it's a bit dicey. Analytics means getting a lot of access to a lot of business information. There's a trust factor that goes with that. But I'm curious what you think about the use of third parties?
Seth: The white paper was definitely focused on IT pros – people moving into data analytics at an individual level. But from a company perspective, I think there are parallels to cybersecurity. Companies may not want to build the entire function in house. They may want to figure out which functions are the most important to have in house and which functions they can outsource.
And like cybersecurity, we're going to see end clients looking for fairly specialized things. These are solutions or business activities – there’s not necessarily a lot of product here. There's not a lot of things that can be managed remotely.
I think a lot of traditional channel companies may be taking a left turn in a whole new direction. There are a lot of new companies out there that specialize in this space. Companies are specializing in Hadoop installations, real-time analytics, data science and machine learning. That’s where the end clients are starting to look.
But at the same time, they're always going to have the partners that they've had for a long time. And there are so many pieces of this. There could be structural pieces, in terms of setting up a storage scheme, working with cloud storage, getting cloud storage and on-prem storage to work hand in hand for an overall storage architecture. Those things would probably lend themselves to a traditional VAR or MSP.
Carolyn: It just sounds like a great opportunity for anyone who is interested in a technology career, or who is already in a tech or business analyst type career to move ahead. I'm assuming most of these jobs are fairly lucrative too.
My takeaway is that we're drowning in data. How much of this do we really need? Somebody should be the gatekeeper – that should be a role. It seems to me that of all the data that you have, there's got to be a percentage of it that is not worth your time.
Seth: One of the lines that I use in the white paper is, when we talk about data these days, we've entered a situation where we have abundance without intelligence. So, yes, companies need a Marie Kondo of data to come in and say: Which one of these are you ready to let go?
We've talked a lot about data analyst and database administrator, but we haven't talked as much about data science – that’s the one that tends to get the headlines. It’s new and flashy. But I don't think many companies are ready for that.
A data scientist is going to come in and apply some heavy-duty techniques to a situation that's already well-structured. But so many companies today are not in a well-structured place. They need to get there first before they can apply those advanced techniques.
Carolyn: The one role we didn't talk about is data architect. It sounds like they are the project managers, or something along those lines. It’s like they are the contractor and all the others are the sub-contractors, and they're helping them do their thing.
Seth: I view the architect role as the final level. They have built their skill in all of the areas within that pillar – and they’ve added at least some level of skill in the other areas. If you're a data architect, you understand how to structure the data like a database administrator would, you understand how to analyze it and you understand the security of it. You might even understand DevOps and how that's working. I don’t think many companies are ready for this role.
Of course, at the biggest companies you do see data architects and chief data officers. You seem them at companies that have been dealing with huge amounts of data for a long time – and their primary business is in extracting the value from that data. I think most companies will eventually get to that point.
Carolyn: I don't think this is a topic that we are going to stop talking about, that's for sure. The white paper is a good one, by the way.
Seth: Thank you. I'm really excited to see how it develops throughout the next year as we launch the CompTIA Data+ certification and training.* It will be great to see some traction with that and start getting some market feedback. It's very exciting to be entering this new space.
CompTIA Data+ covers the skills you need in data analytics. Start gaining skills like data visualization, data mining and more with CompTIA CertMaster Learn + Labs for Data+. Sign up for a free trial today!
*CompTIA Data+ is now available! View exam details here.
Read more about Data and Analytics.
Tags : Data and Analytics