Working with other company’s platforms is something that Talend is used to, which gives the company a pretty insightful view into the benefits and failings of different approaches to analytics.
Having just partnered with Salesforce’s Analytics Cloud Partner Ecosystem, it seems that Tuchen wasn’t too impressed by what he’s seen so far.
"They haven’t structured it in way that makes it particularly easy. It’s easier to put data into, for instance, AWS than it is in Salesforce wave."
While he understands the move by the application vendor to add analytics themselves, he points out that other solutions are better.
"You’ll find that something like Tableau will have more flexibility and more details, analytics options available. The other thing you’ll find with a 3rd party source you’re probably more likely to bring in other data sets easily."
Gathering the right data to understand sales to marketing economics can be a challenge, which is where Talend can step in, making it easier to pull data from Marketo, your CRM system and your ERP system.
Only when you have all three of those data sources can you start to ask interesting questions of your data. While Salesforce will have better integration with its own data, Tuchen expects: "Less flexibility around some of the third party data sets and a little less depth of analysis relative to something like a combination of AWS and Tableau."
The use of Big Data to drive business value is growing, but Tuchen sees issues that limit adoption.
Tuchen believes that the U.S. is probably a couple of years ahead of the UK in its adoption cycle, the fact that the UK is behind in its adoption means that there are less proof points which proves the value of a Big Data strategy.
The other problem, which has been covered extensively, is the skills gap. Not just generally with Big Data skills and the lack of Data Scientists but also with coding Hadoop.
"We are seeing both a lag as those sorts of skills set get developed in the market, we are also seeing a lot of vendors like ourselves that are building tools on top of Hadoop, to lower the amount of specific expertise needed to make use of them and deliver business value."
This isn’t to say that the Data Scientist will be removed from the equation by technology, he always see’s a role for them: "What the Data Scientist will always be doing is understanding what the meaning of the data is.
"What types of analyses are valuable to do that really have meaning and which will lead to great results. You really need to deeply understand the data, where it’s coming from, the semantic meaning of the data – that problem can’t be automated away."
As the industry tries desperately to catch up with the lack of Data Scientists and tries to automate as much as it can, Tuchen expects a growing trend for Analytics-as-a-Service.
In particular he highlighted Accenture as a company which is going down this route: "Accenture looks at that market and says we can uniquely provide both that Data Science business analytical skill set, as well as the technical horsepower to solve the other skill gap which is the Hadoop coding skill gap. Then provide that through an end-to end package through a cloud based service a-a-S."
