Insight platforms as a service: What they are and why they matter
An integrated set of data management, analytics, and insight application development and management components, offered as a platform the enterprise does not own or control, may sound scary, or cryptic.
Scary or not, that’s the definition of Insight platforms as a service (IPaaS) by Forrester. The scary part has to do with the lack of ownership of control. Many enterprises would be put off, as the need to exercise precisely that is engraved in their DNA.
The move to the cloud however, much debated in its early years, is pretty much a given now. Ownership and control have been central issues there, and yet somehow the pro-cloud arguments have prevailed and the majority of enterprises is now on that camp.
Pace of innovation, economies of scale, elasticity, and flexibility seem to outweigh ownership and control. Initially applied to infrastructure, the trend soon expanded to applications and platforms. The end result is that by now a big part of enterprise applications and data live in the cloud.
If those are valid reasons for moving to the cloud, then would it not make sense to have the tools needed to get insights from that data in the cloud too? Why move your data back and forth?
The notion of the cloud as an integral part of data-driven analysis has been around for years. What is new however is that now we are not just talking about cloud-based tools, but entire platforms that offer everything in a bundle: from the mechanics of server provisioning and data ingestion to analytics, automation, and collaboration facilities.
Automation (powered by machine learning mostly) has gone from stand-alone libraries to integrated environments to automating automation. Automation is no longer offered solely as a capability or even a service to end users, but also internally in big data tools and platforms to boost their own capabilities and efficiency.
Solutions for empowering intra and inter team collaboration are flourishing. From collaborative exploration among data scientists, to productizing solutions and managing infrastructure working with data engineers and ops, to serving insights for business users, data-driven analysis is a team sport and needs software that supports this.
Managed cloud big data services are becoming established as a realistic path by which big data analytics and machine learning will make it out to the mainstream. So, to quote fellow contributor Tony Baer, this will be the next great platform decision.
Qubole, the company founded by ex-Facebook Thusoo and Sarma, seems to be among the ones who get this. That was evident when discussing with Thusoo the concept of DataOps, or how infrastructure, process, and culture can work together to empower decision making in organizations.
Now Qubole just launched a new incarnation of what it calls Qubole Data Service, which falls under the definition of IPaaS and was included in Forrester Wave™: Insight Platforms-As-A-Service, Q3 2017.
In fact, Qubole’s originally planned release date almost coincided with Forrester’s report. Although being included in the first place is an achievement in and by itself, considering Qubole is up against the likes of Google, Amazon, and IBM, in the report QDS was pictured as lagging compared to other options.
As the release was rescheduled, when connecting with David Hsieh, Qubole VP of marketing, one of the first things we discussed was whether the two events were related, if Qubole used the extra time to add to its offering, and what is their view of and response to Forrester’s critique.
Hsieh said that moving from a single product to three was a significant business development for Qubole, and in order to ensure that everything functioned as perfect as possible on both the technical back end and business front, they took the extra time necessary to polish the fine details.
