Data and Analytics Consultancies Valuations: Webinar Recap

On October 1, 2026, we hosted a live webinar titled “Data and Analytics Consultancies Valuations.” The webinar was presented by Marcin Majewski, Managing Director, and Filip Drazdou, M&A Director at Aventis Advisors.

You can now watch the full webinar replay below. If you would like to download the presentation material used during the session, you can easily do so by clicking the download report button on the right (if you are using a computer) or by scrolling at the very end (if you’re using a phone).

Below is the full transcript of the discussion, edited and paraphrased for clarity, flow, and briefness.

Why Data and Analytics Consultancies Command the Highest Valuations in IT Services

Marcin Majewski:

Welcome to our webinar about data and analytics companies. I’m Marcin Majewski, the founder of Aventis Advisors. We’re an M&A boutique and we advise mainly on tech deals. I’m here with Filip, who is a director at our firm.

Filip Drazdou:

Hi, everyone.

Marcin Majewski:

We’re very happy to share our findings and research about the data and analytics space, and we’ll give you a sense of why we decided to open our fall 2026 webinar season with this topic. A few words about logistics: we’re going to go for about 45 minutes, and then we’d be happy to take your questions in a short session of up to 15 minutes afterwards. Whenever you have questions, feel free to put them in the chat or the Q&A box, and we’ll address them at the end.

We have a lot prepared for you. It’s a very exciting space, very fast moving, and closely tied to the AI revolution.

The most striking thing for us, and the evidence that this space is worth a closer look, is the valuations of data and analytics companies. We’ve looked at more than 1,000 M&A transactions in IT services over the past 10 years, and data and analytics consulting and implementation came out on top on both the EV/Revenue multiple and the EV/EBITDA multiple. For context on the wider sector, you can compare these figures with our research on IT services valuation multiples.

So we thought, yes, this is worth further attention. This space has been on our minds for quite a while now, and we’ve been working on some deals in it, but we thought it would be interesting to share some of the knowledge we’ve gathered.

What Drives Demand for Data and Analytics Services: Why This Space, and Why Now?

Marcin Majewski:

The main question we’ve been asking ourselves is why. Why this space, and why now? The obvious answer would be AI. AI is driving this industry because you need quality data to build any agentic system, or really any AI implementation.

That said, we were surprised, because the wave of consolidation in this space started a bit earlier than the AI revolution. So there must be a different driver, and that driver is the explosion of data.

The data produced by the economy, essentially by all human activity, has been growing exponentially, and it’s very hard to wrap your head around it. In 2010 we were at 2 zettabytes, where one zettabyte is one trillion gigabytes. That’s a lot of zeros of bytes. Since 2010, we’ve grown almost 200-fold, and this coincided pretty much with the data and analytics consolidation wave. That’s been very interesting for us.

When you think about the future, robots and all the real-life applications will probably cause further exponential growth. Someone needs to take care of that data, to be the gardener of your data garden, so to speak.

What Does a Data and Analytics Consultancy Do?

Marcin Majewski:

This is a good point to touch on what data and analytics companies actually do. They help enterprises organize their data, which means the collection and storage of data, and then they move into inference: trying to understand what’s happening and getting valuable information out of that data.

What we’re seeing more and more now is predicting the future, so forecasting and projections. Part of that is AI inference, which is obviously also something these companies facilitate through their services.

Now that we understand what data companies do, we can jump quickly to the consolidation wave. Filip?

Data and Analytics M&A Activity Since 2015

Filip Drazdou:

We looked at M&A in the data analytics space, trying to understand what’s happening on a high level and what’s under the hood: who’s buying, and what types of data analytics companies are hot and being acquired, because it’s a very broad space.

As Marcin said, it’s number one in terms of valuations. This doesn’t only come from our research and our data; it’s also something we see in the market every day, with strategic buyers and corp dev teams looking specifically for this niche. So we decided to take a look at what’s under the hood with some data.

Overall, the number of transactions grew steadily from 2015 until around 2022, and then it flatlined at around 100 deals a year. Here we only looked at majority acquisitions and control transactions, so no capital raises or smaller minority stake deals. These are deals where the acquirer takes almost full ownership or a large stake.

That has been surprisingly stable over the past couple of years. One part of the explanation is that the overall IT services market isn’t doing that well, and the number of deals there is down since the peaks of 2021 and 2022. So as a share of overall IT services M&A, I think data analytics is growing, but in absolute numbers it’s more or less flat.

Who Buys Data and Analytics Companies: Strategic Acquirers vs. Private Equity

Filip Drazdou:

When we talk to sellers, they’re often interested in who the potential buyer for their company could be. So we looked at how the buyer groups have developed over the past 10 years in this space.

The first group is data analytics companies acquired by strategic investors, such as Accenture or Tata Consultancy Services. The second, larger group is all the private equity related deals, whether that’s a private equity fund buying a platform company or a private equity backed company purchasing add-ons as part of a roll-up strategy.

This second group has grown quite significantly. In 2015, 2016 and 2017 there wasn’t much activity there, but by 2024, 2025 and 2026 it’s basically 40 to 50% of all deals. These roll-up strategies are becoming more and more popular. A private equity fund first buys a platform, let’s say a business with 200 to 500 people, and then grows it through acquisitions across the globe or in adjacent spaces, buying companies with, let’s say, 50 to 100 employees.

For a lot of founders of data analytics companies, that’s a very good exit strategy. Those buyers are always in the market and they’re looking for something specific, so if a seller wants to sell their business, they’re a good buyer.

There’s always the strategic route too, going to a big strategic buyer, but the deal sizes there are larger and it’s, I would say, more uncertain. It depends on the strategy of that big company, and you never know. But if your particular space or technology is in their focus, you can get a very good deal there.

So the private equity share is growing, as in many places, and strategic investors are still active. Overall, if someone is looking to sell a data company, I think the buyers are definitely out there.

Which Data and Analytics Segments Are Buyers Acquiring?

Filip Drazdou:

Not all data analytics is created equal, I would say. Behind these growing deal numbers, we tried to see what’s happening under the hood and which particular segments are interesting for buyers. We mapped data companies across a number of segments.

BI, reporting and CPM: This covers Power BI, Qlik and Tableau, building reports and dashboards, as well as corporate performance management on platforms like IBM Planning Analytics, OneStream, and so on. This has been declining as a share of overall deals. I think this part of the market is changing and it’s really mature. Power BI is already well penetrated; it’s the number one platform in the world. The companies that implement and integrate it are also very prevalent, so it’s tough competition, and a lot of businesses do it.

Many of the customers there are not enterprise customers but SMEs and mid-sized businesses. So honestly, in this space we’re not seeing a lot of activity, a lot of interest, or the highest valuations, for those reasons. The barriers to entry are also quite low. You don’t need a lot of capital or a big team to start putting out Power BI reports and have a company there.

Cloud data platforms and engineering: What’s been growing, on the other hand, as a share of overall data transactions, is cloud data platforms and engineering. Under this name are basically all the modern, up-and-coming platforms like Snowflake, Databricks and Microsoft Fabric, putting out data warehouses, data lakes and so on, primarily for enterprise clients. Together with the growth of those platforms, their ecosystems grew, and then private equity funds started to look at them. This is actually where most of the private equity transactions are happening.

AI/ML and GenAI solutions: These are also growing, from around 11 to 12% in 2019 and 2020 to 27% today. These are all the companies implementing generative AI platforms and AI analytics, the cloud partners and OpenAI partners. This is still up and coming. There aren’t many pure-play companies, and a lot of companies are just venturing into it, but the interest is out there.

What we’re even seeing is the top LLM providers like Anthropic and OpenAI building their own consultancies, with forward-deployed engineers, as they call them, and they’re buying companies to do it. OpenAI did two deals in the last couple of months, and Anthropic did a deal where they acquired a consultancy. Overall, I think this space is going to grow further, which is something we also track in our research on M&A in AI.

Vertical and domain analytics: One more domain that has been declining is vertical and domain analytics. I took a more detailed look at what’s behind that, and it’s mostly because marketing analytics companies have become less popular. In 2015, 2016 and 2017 there were a lot of transactions where buyers acquired companies doing Google Analytics or all kinds of advertising analytics. Nowadays, with AI and the changes to SEO, that space is becoming much more competitive and less profitable.

So we’re seeing a decline there, primarily in marketing, while areas like retail analytics or healthcare-specific analytics are keeping up. If a company operates in a specific vertical or domain that is very niche, I think it’s still a good place to be.

Going forward, I think cloud data engineering and AI will continue to grow and take a larger and larger share of the deals.

Data and Analytics Valuation Multiples: What Drives EBITDA Multiples?

Filip Drazdou:

That is reflected in valuations as well. The overall median valuation for data analytics companies was 16x EBITDA, but here we tried to show the different valuations for different financial profiles of businesses and the ecosystems they’re in.

To get to the top valuation, a company should usually have:

• Revenue size: large, with $10 million plus in revenue
• Revenue growth: 30% or more. A big part of the high valuations for data companies is that they’re simply growing faster than everyone else
• EBITDA margin: rather profitable, at 20% plus
• Recurring or reoccurring revenue: 50% plus. There’s a lot of project revenue in this space, and that’s not a big problem; it’s a very different segment from, let’s say, MSPs, where MSP valuation multiples are driven by contracted recurring revenue. But having customers that come back to you with new projects, or for ongoing maintenance of their data, is always good
• Customer concentration: less than 10%
• Ecosystem: a significant share of work on modern platforms such as Snowflake and Databricks

With that profile, I think a 15x EBITDA multiple is basically guaranteed.

If you move left, to a more difficult financial profile with more legacy platforms, you get to standard IT services valuations of around 6 to 8 times EBITDA. And for smaller businesses that aren’t growing and are barely profitable, we often tell them that it’s going to be very difficult to sell, or that it will be at a low valuation that doesn’t make sense for the sellers.

So that’s, on a high level, where we see valuations in the space right now. Anything to add here, Marcin?

How Vendor Ecosystems Shape M&A: Snowflake, Databricks, OpenAI and Anthropic

Marcin Majewski:

Yes. I think this is a good segue to our next slide about ecosystems, because they’re one of the things that drive valuations and interest from strategic and financial buyers alike.

We’ve done some interesting research into M&A by ecosystem, and this is particularly relevant to data and analytics companies, which typically tend to be aligned to one, two or three vendors.

What we have seen, looking at the last decades of markets consolidating, is that vendor ecosystems go through a lifecycle. They start small, with an open-door policy, where becoming a partner of a vendor is very easy. But over time, the gates to reach a given partnership tier get tighter and tighter, and you have to try a bit harder.

There comes a point when it’s easier to acquire a company with a higher partnership level than to go through all the motions to reach the desired partnership level yourself. That’s when M&A activity peaks.

Some ecosystems are already past that peak, like SAP, Oracle and Microsoft Dynamics. Right now, I think we are seeing the peak of interest in the Snowflake and Databricks ecosystems, which are going through this inflection point, and we’ve seen huge interest from strategic buyers in acquiring assets in those ecosystems.

Conversely, in the OpenAI and Anthropic ecosystems, we feel that what’s going on is not that well understood, and it’s not very transparent who’s getting in and who’s not. The wave of consolidation is still ahead of us there. That’s also because the companies working with OpenAI and Anthropic are doing so well that there’s little incentive for the founders to sell. We look at how this plays out in pricing in our research on AI valuation multiples.

The main takeaway from this section is that the difference in EBITDA multiples can, to a large extent, be attributed to the ecosystem and the value of the ticket into that ecosystem. It can explain, for example, a difference of 2x between a mature Oracle consultancy and a Snowflake consultancy; two times the valuation, essentially, although they do pretty much the same thing to a large extent. The scope of their services can overlap a lot.

There’s more research on ecosystems on our website if you’d be interested to learn more. We can also have a quick glance at the more comprehensive list of ecosystems that relate to data. These are basically the leaders. Some are more mature and some less, but these tend to be the hotter consolidation sectors.

Scarcity Premium: Why Pure-Play Specialists Are So Rare

Filip Drazdou:

I’d also say that part of the premium for some of those companies is simply scarcity. If you’re a private equity fund looking to invest in this space and you’re looking for, say, a $20 million business with $5 million of EBITDA, there just aren’t many companies that satisfy that requirement. So once a company like that is on the market, there’s pretty big competition to get it, especially if it’s a specialist in Databricks or a specialist in Snowflake.

Most companies are rather diversified. You’re buying into one great ecosystem, but you’ll have to take over some legacy work as well. So a pure play is very rare.

Is Now a Good Time to Sell a Data and Analytics Company?

Marcin Majewski:

The big question for a lot of founders and investors in data and analytics right now is whether this is a good time to sell. We break it down into three options: sell now, take on a minority partner, or wait and grow.

Obviously, like in many situations, it depends. But it’s definitely a great time to sell, as valuations are high. Without getting too much into whether we’re in a bubble or not, looking at historical trends, valuations are quite good.

This is one pocket of IT services that still maintains a high multiple. We’ve seen a huge repricing of a lot of IT services assets, which you can follow in the Aventis IT Services Index, but we haven’t seen it touch this particular sector. So for many IT services founders it’s not a great time to sell, but for data and analytics it’s still a seller’s market, and there’s more interest than there are good deals going around.

It’s also a great time to grow, with or without a minority partner. We think there are many great years to come for data and analytics companies, driven by the sheer volume of data being produced and the needs of AI. So I think if you are in this space, you’ll be well off whether you sell or continue, with or without a partner.

I think that’s a wrap for what we have to say today. Filip, if you’d like to comment, feel free, and we can wait a little bit to see if there are any questions from our audience.

Filip Drazdou:

Yes, I think everything goes through cycles, and we’ve seen cycles in IT services with different technologies and platforms. At one point e-commerce was super hot because of COVID, and the top multiples were in the commerce space.

Then the market saturated and growth slowed, and economics took hold as more and more people saw it: wow, that’s a hot space, it’s growing, valuations are strong. So people started developing those practices in their companies, and employees started to train on those platforms. Then we reach the maturity stage, where valuations are still strong and good, and there’s still good interest from buyers because of some secular tailwinds, but maybe not as premium as now.

So in terms of valuations, now is one of the best times, but waiting and growing can also be an option. It’s always a calculation: do I sell now for, let’s say, 15 times on a $2 million business, or later for 7 times on a $4 million business? It can come to a similar number, or a slightly better one if you wait and grow, simply because you have a bigger business.

As is often the case in M&A, it’s a personal decision for the founder: their personal situation, and how they see themselves over the next 5 to 10 years.

Marcin Majewski:

Thank you, Filip. This concludes our session, so thank you everybody for your time. We’ll make the slides available on our website, and you can watch the recording of this session on YouTube. We’d welcome you to our next event, which will probably be at the end of October or beginning of November. Thank you all, and see you at the next one.

If you are considering any type of M&A transaction in the data and analytics or IT services space, whether as a buyer, seller, or investor, we would encourage you to get in touch and speak with us directly. You can also explore our latest data on IT services valuation multiples for more context.