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As organizations try to analyze the vast amounts of information they've collected, they need to overcome data integration problems before they can extract meaningful insights.
Decades of data exist for enterprises that have stood the test of time, and it's often housed in different locales and spread across disparate systems.
Enter vendors that specialize in solving data integration issues, whose service is helping other companies curate the vast amounts of information they possess and put it in a place -- and in a format -- where it can be accessed and used to produce meaningful BI.
In the second part of a two-part Q&A, Talend CEO discusses different data integration problems large enterprises face compared with their small and midsize brethren, as well as Talend's strategy in helping companies address their sudden abundance of data.
In part one, Tuchen talks about the massive challenges that have developed over the last 10 to 15 years as organizations have begun to digitize and pool their data.
Are there different data integration problems a small- to medium-sized business might face compared to a large organization in terms of extracting data from a vast pool of information it has collected over the years?
Mike Tuchen: For a small or medium-sized company, for the most part they know where their systems are. There's a much more human understandable set of sources where you're going to get your data from, so for the most part cataloging for them isn't required upfront. It's something you can choose to do later and optionally. They can say, 'I'm going to pull data from using Salesforce and NetSuite, and HubSpot and Salesforce and NetSuite, and Zendesk for support.' They can pull data from all those systems, make sure they have a consistent definition of who's a customer and what they're doing, and then can start analyzing what the most effective campaigns are, who the most likely customers to convert are, who the most likely customers to retain or upsell are, or whatever they're trying to do with the core analytics. Since you have a small number of systems -- a small number of sources -- you can go directly there and it turns more into a 'let's drive the integration process, let's drive the cleaning process' and the initial cleaning process is a simpler problem.
So in essence, even though they may not have the financial wherewithal to invest in a team of data scientists, is the process of solving data integration issues actually easier for them?
Tuchen: For sure. Size creates complexity. It creates an opportunity as well, but the bigger you get the more sources. Think about at one end of the spectrum you've got a large multinational company that has a whole bunch of different divisions spread out across the world, some of them brought in through acquisitions. Think about the plethora of different sources you have. We're working with a customer that has a dozen different ERP systems that they've done and that they're now trying to bring data together from, and that's just in one type of data -- transactional data around financial transactions. Think about that kind of complexity versus a small company.
What is the core service Talend provides?
Tuchen: Talend is a data integration company, and our core approach is to help companies collect, govern, transform and share their data. What we're seeing is that data, more and more, is becoming a critical strategic asset. We're seeing, worldwide, that as companies are more and more digitized they're seeing that data managed correctly is a competitive advantage, and at the heart of every single industry is a strategic data battle that if you solve that well there's an advantage and you'll be out executing your competitors. With that recognition, the importance of the problem that we're solving is going up in our customers' minds, and that creates an opportunity for us.
How does what Talend does help customers overcome data integration problems?
Tuchen: We have a cloud-based offering called Talend Data Fabric that includes a number of different components, including a lot of the different capabilities we talked about. There's a data catalog that solves that discovery process and the data definition issue, making sure that we have a consistent definition, lineage of where does data start and where does it end, what happens to it along the way so you can understand impact analysis, and so on. That's one part of our offering. And we have an [application programming interface] offering that allows you to share that with customers or partners or suppliers.
As you look at where data integration and mining are headed, what is Talend's roadmap for the next one to three years?
Tuchen: Right now we're doubling and tripling down on the cloud. Our cloud business is exploding. It's growing well over 100% a year. What we're seeing is the entire IT landscape is moving to the cloud. In particular in the data analytics, data warehouses, just over the last couple of years we've reached the tipping point. Now we're at the point where cloud data warehouses are significantly better than anything you can get on premises -- they're higher performance, more flexible, more scalable, you can plug in machine learning, you can plug in real-time flows to them, there's no upfront commitment, they're always up to date. It's now at the point where the benefits are so dramatic that every company in the world has either moved or is planning to move and do most of their analytical processing in the cloud. That creates an enormous opportunity for us, and one that we're maniacally focused on. We're putting an enormous amount of effort into maintaining and extending our leadership in cloud-based data integration and governance.
Editor's note: This interview has been edited for clarity and conciseness.