What will this investment mean for Talend
This investment ushers in the next step for us as a company as we double down on product innovation and scale up our go-to-market initiatives.
How does this investment improve Talends big data offering
Well be investing in a number of areas in and around big data and NoSQL. One important area is real-time.
How did you select / choose your investors
They actually came to us. BPI is the investment arm of the French government, chartered with fostering innovation in France. They look for innovative high-growth companies with a strong presence in France, especially ones in targeted areas were they see huge opportunity like big data. With this in mind Talend was a perfect fit, so it’s not surprising that they found us.
What role will the investors play in the business moving forward
BPI will be represented on Talends Board of Directors.
How will this funding be used
Were investing in both product innovation and accelerating our go-to-market. On the product side well double down on big data, an area thats exploding for us. We already have a unique solution with strong customer adoption, and this investment will increase our lead over the next year. On the go-to-market side well invest in inside sales and building out our community and partner ecosystems.
How do you currently see the big data market
The big data market is currently crossing the chasm in Geoffrey Moores iconic market development framework. Were seeing early adopter customers finding unique benefits and strong ROI in a range of scenarios, and consequently many more mainstream customers are investigating and experimenting with it. As a result the market overall is experiencing hypergrowth, though from a relatively small base measured in the low hundreds of millions of pounds.
Its worth pointing out that Im using a fairly strict definition of big data here – there are many different things that could be included, and some companies and analysts are categorising everything to do with any kind of data management as big data the same things that we would have called traditional data warehousing, analytics, or business intelligence a few years ago. Using that approach yields large multi-billion pound market sizes, but it’s less meaningful in my opinion.
What are the main challenges you are finding customers are facing with big data
Gartner published a great research paper that mirrors our own experience: ‘Survey Analysis: Big Data Adoption in 2013 Shows Substance Behind the Hype.’ Overall, we see three sets of customers: those that are trying to figure what big data really is given all the hype and rush to paint every technology that has anything to do with data with the trendy big data label; those that have figured out what it is and are identifying scenarios where they might find strong ROI; and finally those that are actively experimenting with it or running it in production. For the latter customers, the challenges fall into several areas:
- Skills – Do you have the skills necessary to succeed with a big data implementation, from Hadoop, MapReduce, NoSQL, data science, and many more Given how new the market is, there are very few people in the world outside of Google & Facebook with those skillsets so this is a widespread issue.
- Architecture – What architecture and tools should you choose that will allow you to have a flexible, scalable, manageable and cost effective solution
- Governance – How to solve the same governance issues that I have in your existing data infrastructure including things like data quality, data mastering, privacy and security
- Budget and cost – How do you find the budget for the solution as the pilot succeeds and scale it up from a few servers to dozens or hundreds
How do you see the big data landscape changing in the near future
I think well see four things happening in parallel. First, well see increasing numbers of early adopter success examples leading to a widespread understanding of mainstream use cases where big data provides unique benefits. This is another way of saying that well see big data successfully cross the chasm . Were on the verge of that now.
Second, well see the vendor solutions mature to simplify planning, deployment, management, and ongoing maintenance. Today, the solutions have a number of moving parts and some rough edges as the customer pain points above demonstrate.
Third, well see the big data stack getting more fully fleshed out, including solutions for the many areas outside of data storage and querying supplied by the core Hadoop distros. This includes the areas that Talend offers (data integration, data quality, master data management), as well as things like analytics, visualisation, and reporting.
Finally, well see a number of new use cases emerge as the technology continues to evolve in areas such as real time querying and streaming data. These are a step behind the early, more batch oriented scenarios since the supporting technology is just coming together now.