Navin Chaddha
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Editor’s note: Navin Chaddha is managing director of Mayfield, an early-stage venture capital firm. Some of the companies he is currently championing include Gigya, Elastica, Lyft, MapR and Poshmark.
As we enter the second half of 2014, it would be fair to say that big data has gone mainstream, attracting coffee table books, multiple industry landscapes, consumer applications, and large amounts of funding. Having seen many technology cycles during our 45 years in venture capital — including the birth of the PC era, the transition to client-server computing and then web-based computing, and the emergence of the cloud and SaaS models — we have pattern recognition on what it takes for a company to go from startup to leader.
Here are some observations we’ve made about what it would take to build a lasting big data company:
1. Transition from a platform to an ecosystem
One of the clearest ways to see whether a technology platform is taking hold is to look at how fast the ecosystem is growing around it. For example, in the SaaS era, Salesforce rapidly became a giant because of its expansive ecosystem. Big data will be no different.
One thriving big data company that is transitioning from platform to ecosystem is MapR. It is the only distribution for Hadoop that combines the benefits of open source (community innovation, portability and flexibility) with unique architectural enhancements that provide enterprise-grade dependability, security, and performance.
The MapR ecosystem embraces both the flourishing Hadoop open source community as well a rapidly expanding portfolio of partner solutions in the MapR App Gallery. This enables enterprise customers to easily expand and implement their big data initiatives with ready-made, big data utilities and applications.
Another example is MongoDB, an open-source and leading NoSQL database used by companies for a wide variety of applications. MongoDB is building a significant ecosystem of partners across industries.
2. Solve the messy, hard problems no one wants to touch
This is not a particularly glamorous part of the big data world; however, we believe that many big companies will be built doing this work. In the client-server era, data integration pioneer Informatica became a giant by tackling tough data integration challenges and has maintained its edge by being positioned as a leader in the Gartner Data Integration Magic Quadrant eight years running.
An example of a company to watch in this space is Trifacta, which enables both technical and non-technical analysts to access and transform raw data into actionable data.
3. Reinvent business intelligence for the big data age by providing insights, not just data
Companies such as Business Objects that empowered line of business executives to gain insights grew into giants in the client-server era. We believe that a similar class of big data companies are in the making with companies such as Platfora, which are built natively on Hadoop and rapidly deliver insights visually and iteratively.
4. Embed deep domain expertise
Ensure that valuable expertise from your specific domain is embedded into your analytics application so that it cannot be dislodged. SAP became a giant in the software industry using this strategy.
We see this valuable domain expertise in big data analytics companies such as Palantir which provides human-driven, machine-assisted solutions for specific use cases like anti-fraud and cybersecurity as well as to vertical industries like defense, insurance, healthcare, & law enforcement; and Splunk which transforms machine data into insights.
5. Delight your customers with an intuitive interface
Give your IT and line of business customers compelling interfaces to interact with their data. Understand how users interact with your application and invest in the details of the user experience to make it intuitive and delightful. For example, Dropbox became a giant after creating a simple, intuitive approach to file sharing that is now shared by more than 200 million users around the world.
Big data companies with intuitive interfaces include Tableau, which can create visualizations to help enterprises easily see, understand and derive insights from their data, and Elasticsearch, the open-source solution that offers a fast and rich search experience.
And what’s coming next?
And one more thing, keep your eye on how the Internet of Things will transform the landscape by serving up data in all kinds of new forms. Today it’s thermostats, phones, watches, even drink glasses… tomorrow data will come from places we have not yet dreamed of. The whole idea of data ownership, lifecycle and ingestion will have to be rethought, spawning new companies. This will give rise to a wave of innovation and companies creating new products and services never thought of or possible before, and existing ones re-imagined.
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