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11 Companies to Look at to Stay Ahead in the Data & Analytics Space

Here is my take on companies you should be keeping track of in the analytics space. My hope is to curate a list like the one below every quarter to reflect changes in the analytics marketplace and inform on technologies that are gaining momentum and market traction. It’s also a forcing function for me to be keeping tabs on a number of these companies. If you want to continue to see these lists, please add a comment!

I love to see the continued proliferation of teams building products needed out there. One growing theme, as you can imagine if you pay attention to headlines, is that many companies starting today claim AI capabilities or that they’re building the next AI for x industry that will be game changing. Some are interesting, most are not. In the list below, there areonly 2–4 companies that have machine learning and AI as a part of their product offering. Some are making model development and deployment easier (DataRobot) and some are incorporating these ML techniques into their core product (Alation, Looker, etc).

The age of “Smarter” applications (enhanced through ML, Deep Learning, etc) is upon us and you should be excited about that! That’s hype I can get behind…

Now, moving on to the list of 11 companies which I’ve categorized broadly. The 4 categories of companies cover product maturity, market traction and funding. Those categories are:

1. The “We’ve been funded SUPER well and have tons of market traction” Companies
2. The “We’re starting to take off, so hurry up and follow” Companies
3. The “We have an interesting v0 — vX of our product, strong founders, so please take our demo” Companies
4. The “We are well funded but haven’t released our product yet” Companies

I won’t be providing a lot of commentary on certain companies which I’ve written about in the past but if you have a question on them please leave a comment.

The “We’ve been funded SUPER well and have tons of market traction” Companies

1. Snowflake ($263M* — Series E in January ‘18)
   One of the more interesting data platform companies to come around in some time. They are making the modern data platform much easier, sitting on AWS. Many new data platform builds are occurring with Snowflake. Lots of funding and strong market traction.
2. Looker ($81.5M — Series D in March ‘17)
   Looker continues to make traction in the market and have received more and more funding in 2017. I really like their product, but I’m hopeful they’ll continue to invest in “ease-of-use” to start to capture more of the casual analyst and user demographic.
3. Databricks ($140M — Series D in August ‘17)
   Databricks continues to make waves as the productized / enterprise-ified version of Apache Spark. I like that they are now supporting AWS & Azure, but they need to get that 3rd cloud support of GCP. Lots of funding and strong market traction. I wonder how they will grow as cloud providers start providing the same direct services at much lower costs…
4. Segment ($64M — Series C in July ‘17)
   Segment bridges the gap between front end and back end systems, allowing for easy data integration across 200+ connectors. Segment also has a strong streaming capability and their new personas Beta is super, super interesting. They continue to gain market traction and have one of the better user experiences in the space.

The “We’re starting to take off, so hurry up and follow” Companies

1. Alation ($23M — Series B in July ’17)
   I’ve written a decent amount in the past about Alation, but I continue to like the problem they’re tackling. Data discoverability within an organization to streamline governance, common metrics and data usage.
2. DataRobot ($67.2M — Series C in July ’17)
   Lowering the barrier of entry for Machine Learning and accelerating development / deployment of ML models…seems like a win, win, win, right? Indeed and they’re gaining more and more market traction. As I’ve said in other articles, it’s more important now than ever to be able to translate these models and the business impact. Nice to see some publications are saying the same thing.
3. Usermind ($23.5M — Series C in January ’18)
   Usermind built a customer hub product. It integrates customer touch point systems IE CRM, MKT Automation, etc. Solving a top challenge for many companies especially in Retail, Ent. Software, Fin Services.

My opinion: having led a # of projects where we’ve built similar “hubs”, I love to see a company productizing customer data hub. For this to really be appealing, they need to solve for data quality issues in all of these source systems (or rely on upstream data quality functionality from the sources — BUT none of those sources are prioritizing this yet as features). Just integrating these sources isn’t enough, the biggest challenge companies face is not data integration but single customer records and clean data!

Competitors: ActionIQ is similar with same funding from Andreessen as well. Amperity is another, similar company with $28M in their latest Series B round.

4. Tamr ($41.2M — total funding, latest round undisclosed)
Machine learning applied to master data domains within an organization. Taking a lot of the manual analysis, connecting disparate data schemas, and identifying mastering elements out of the equation. That’s all lovely and needed, but I do want to see some additional governance capabilities to make this an even more compelling solution for enterprise data governance and management.

5. Streamsets ($20M — Series B May ’17)
Data operations platform focus on streaming data from many sources (APIs, IoT, clickstream, etc) to intermediate sources to eventually power analytics, applications, etc. former Informatica and Cloudera engineering. Well funded by top VCs.

My opinion: they are solving for a challenge in IoT, Marketing and Product areas via real-time data needs. I like they are not tied to a single cloud provider but work across all 3. It will be interesting to see if they start to expand a bit beyond streaming and challenge the traditional ETL industry as well.

The “We have an interesting v0 — vX of our product, strong founders, so please take our demo” Companies

1. Insight Engines ($15.8M — Series A in July ‘17)
A product that sits on top of Splunk and allows users to ask questions of their machine data. Relies on natural language processing.

My opinion: a lot of potential for this to lower the barrier of Splunk adoption in an enterprise, especially for less development focused users. However, unless bought by Splunk, I don’t love companies that are tied so directly to another tech product (unless that product is more of an ecosystem, like AWS, GCP, etc)

The “We are well funded but haven’t released our product yet” Companies

1. Ascend.io ($15M — Series A in May ‘17)
   Prominent VCs behind this startup. Ex founder of ooyala. Set to productize data operations and the data lifecycle. Strong founding team. Typically these are interesting products to keep an eye if they make it to GA before faltering or getting acquired.

My opinion: No strong opinion yet. To be updated once I see more but conceptually I’m interested.

Is there an interesting startup or high growth analytics company I missed? Would love to hear about it in the comments. I’ll be updating this list via another post in the next few months.

*Funding amounts for each company were sourced via www.crunchbase.com