5 Data Startups To Watch Out For In 2017

The next 12 months could be big for these companies


The market for data analytics solutions is growing rapidly. According to a recent report by IDC, worldwide revenues for big data and business analytics (BDA) will rise 12.4% year-on-year in 2017 to $150.8 billion in 2017, while commercial purchases of BDA-related hardware, software, and services will see a compound annual growth rate (CAGR) of 11.9% through 2020, when revenues will reach in excess of $210 billion. Just last week, self-service analytics giant Alteryx went public, raising $120 million to give them a market cap of around $828 million. And they are not alone. Firms are now producing solutions that enable organizations to store and analyze their data in ways never before dreamt of, and venture capital is recognizing the opportunities present in the space.

We’ve looked at 5 companies making the biggest impression in the space this year.

1. Treasure Data

Treasure Data is a cloud-based live data management platform provider with a mission to help customers ‘harness and analyze the information you need to create a data-driven enterprise.’ Founded in 2011 by its CEO Hiro Yoshikawa, it enables organizations to instantly collect and unify data from varied sources so that everyone across the enterprise can utilize it for real-time insights. Yoshikawa describes it as ‘basically a fully-managed data pipeline and the data analytics platform service on the cloud, which includes data collection and ingestion software, highly scalable data, backend storage, and analytics front-end.’

The California-based company raised $25M in a Series C round in November 2016, bringing its total up to $60.05 million, and it now has more than 250 customers, including Mitsubishi Heavy Industries, Pioneer, Subaru, Wish, and GE Healthcare.

We recently spoke to the organization’s VP of Marketing, Kiyoto Tamura, about their success.

How important to you feel cloud technology is for data analytics today?

Cloud technology is part of every data analytics project. As businesses demand more agility and time to insight, analytics team will deploy cloud solutions, many of them designed to solve a few (or one) problem well. This is why, for example, the Martech Supergraphic has grown from ~100 to 5000+ in just 6 years. Every data analytics team has a data silo problem, resulting in many premature optimizations that result in ‘sum of its part is less than a whole’. In that sense, cloud technology has been both enabling (agility) and disabling (encouraging data silos). We are trying to solve this problem by introducing our customer data platform, aimed at unifying customer data across all these data silos.

Can you tell us a bit about your growth as a company thus far?

We’ve grown quite a bit over the last few years. Our revenue and number of customers have doubled over the last year and started to move up-market, with large insurers like AXA, automakers like SUBARU, entertainment giants like Warner Bros., B2B businesses like GE Healthcare. They all share one big problem: creating a consistent, unified view of each customer and delivering more personalized experience to acquire, retain and grow their customer base.

What are the main challenges you will have to overcome this year?

Both our challenges and opportunities is the proliferation of cloud technology: as more and more ‘tools’ become available in the market, there will be an opportunity for customer data ‘platforms’ to unify data and orchestrate customer interactions across these systems. Another big challenge is security and privacy: the more customer data you have, the greater your responsibility to safeguard their data. We’ve done a lot of work on security, including attaining key certifications and attestations. We feel confident that we will be able to keep up with the ever-evolving needs to secure customer data and protect their privacy.

What does the year ahead hold for Treasure Data?

This is the first year Treasure Data is positioning itself as a customer data platform (CDP). This is hardly a pivot but a natural evolution: we realized that the best-in-class data platform we’ve built and packaged as a robust, scalable platform that can collect, unify, analyze and activate all kinds of customer data. This year is going to be about educating the market and customers on the potential of what they can do with their customer data. We take the point of view that the world’s highest growth companies are the world’s largest CDPs (Facebook, Amazon, Google). And we are here to level the playing field for the rest of us who know their customers better than anyone else.

2. Dataiku

French startup Dataiku saw growth of over 300% in 2016, and it is set to go from strength-to-strength this year, having raised $14 million in a Series A funding round last November. It now has more than 100 customers, including AXA, Trainline, L’Oréal, Hostelworld, and Bechtel, despite having only been founded in 2013, won the best enterprise startup at The Techies awards 2017, and was named as one of 14 strong performers by Forrester in ‘The Forrester Wave: Predictive Analytics And Machine Learning Solutions, Q1 2017.’

Dataiku's guiding objective is ‘to offer a data science platform that lets coders use a notebook when they must, but use visual tools to build workflows when productivity is at a premium.’ Its main product is Dataiku Data Science Studio, an advanced analytics software solution that provides companies with all features and tools necessary to develop and deploy their own data products. It connects to more than 25 different data storage systems, including closed source and open source databases such as SQL Server, HDFS, and NoSQL. Florian Douetteau, CEO of Dataiku, explains that ‘We like to think of Dataiku as a ‘control room’ of the wildly dynamic and diverse plethora of open source technologies — whether you use Hive or Pig, or code in Python, R or Scala, Dataiku will let you use whatever solution you already have and know and seamlessly integrate it with the next step in the process. And because we’ve built a visual interface on top of these open source solutions, you can still use many of these solutions even if you don’t know how to code in a particular language — or at all.’

With the benefits of a data-driven culture and open source technologies now being realized by organizations looking to properly exploit the wealth of information they are collecting, Dataiku is perfectly placed to take advantage, and we will likely see it grow rapidly over the next year.

3. Couchbase

As the quantity and variety of data has exploded, so too has the need for NoSQL databases, and Couchbase is among those leading the charge. It is a high-powered open source NoSQL, document-oriented database for building interactive applications. It has Amadeus, Tesco, British Gas, and Ryanair among its customers, and has raised $146 million in funding to date, including a $30 million Series F round in March 2016.

Founded in 2011, the Mountain View-based company recently replaced CEO Bob Wiederhold with former Veritas president Matt Cain. Widerhold noted of the move that, ’Our focus on delivering mission-critical, enterprise-class database solutions that allow digital businesses to deliver great customer experiences has allowed us to grow by over 50% in 2016 with even greater growth expected in 2017. I am thrilled to have Matt join the company as CEO to take us through our next phase of growth and excited to work with him to build the next great database company.’ Mature open source databases are no longer niche products, with tech giants from Google to Facebook all adopting the technology, and while Couchbase has some strong competition, it is well positioned to lead the charge.

4. Striim

Striim is a streaming analytics startup that provides companies with end-to-end, real-time data integration and streaming analytics. It helps the user make sense of large amounts of data from sources such as enterprise databases, IoT sensors, and log files in miliseconds. It also recently announced the introduction of Striim for IoT, which is designed to help enterprises address three of the most difficult data challenges of IoT infrastructure: 1) managing the huge volume of data generated by IoT devices; 2) integrating IoT data with the enterprise and analyzing it in real time; and 3) addressing security issues associated with the explosion of connected devices.’

Katherine Rincon, Senior Vice President of Marketing, Striim, notes that ‘As data volumes continue to grow exponentially, it is increasingly critical for enterprises to pre-process and analyze data in-flight, in real time, before it lands a Data Lake. All of us at Striim are working hard to create a user-friendly platform that allows companies to harness and utilize the whitewater flow of data that is continuously streaming into their enterprise.’ This has also been recognized by investors, with the start up having raised total equity funding of $42M in 3 Rounds from 7 Investors already.

5. 6sense

6sense is b2b predictive analytics engine that enables companies such as Cisco and IBM to predict everything sales and marketing departments need. It monitors billions of time-sensitive intent signals across the web to reveal new prospects at every stage of the funnel and determine any prospects that are available to buy, how much they would be willing to spend, and when.

It has now raised total equity funding of $36M in 3 rounds from a list of investors that includes Bain Capital Ventures, Battery Ventures, Venrock, and Salesforce.


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