(or “Are you an iPhone or Android phone advocate?”)
By Patrick Adamiak, VP Product Marketing, Liaison Technologies
It’s been almost a week since we introduced the Liaison Alloy Platform, the industry’s first Data Platform as a Service (dPaaS) offering. During this time, we have had the opportunity to answer quite a number of questions from customers who are quite intrigued by the dPaaS concept—and by the Liaison Alloy Platform in particular.
As I sit in the Chicago airport waiting for my flight, I thought I would take a little time to answer some of the questions that have been posed this past week. To keep this post to a manageable size, I have chosen to focus on three key questions.
(For those of you wondering about the iPhone/Android reference in the subtitle, the mystery will be resolved later in this blog post.)
What is Data Platform as a Service?
dPaaS is a unified, cloud-based approach to integration and data management. As a fully managed service, dPaaS insulates the integration and data management complexities from the customer, while still providing full transparency and control of the data. It takes a holistic view of the challenge by incorporating people, process, and technology dimensions.
Said even simpler, the dPaaS approach enables your staff to focus on building and executing on strategies aimed at harnessing your data assets to deliver maximum business value. The supporting functions such as integration, data cleansing, harmonization, etc. are provided out of the cloud as a service on your behalf from a unified (integration AND data management) platform.
When looking at the graphic of the Liaison Alloy Platform it looks like all my data must be highly centralized. This is just not realistic in my environment. Is my understanding correct?
The Liaison Alloy Platform was built with the fundamental assumption that much of today’s potentially useful data is ‘in the wild.’ For example, creating a complete picture of how your customers view your brand might require combining traditional customer survey results; customer contact center logs; and references on social media. Valid data can come from nearly anywhere and it is often impossible to forecast what sources and combinations will be required in the future.
So, you can use the Liaison Alloy Platform to harmonize and integrate data from anywhere on the planet as you see fit. What’s more, you can choose how much data—if any—you store on the platform. At one extreme, nothing is stored on the platform and it deals only with “data in motion.” At the other extreme, you can store massive amounts of data to support a data lake use case for example. The point is that the Alloy Platform can persist data as you choose and easily integrate with your other data sources and stores.
I have some talented integration people on my team. Why would I consider sourcing my integration services from the cloud?
A fully managed integration service in the cloud isn’t for everyone. After all, many people are iPhone devotees while many others advocate the Android phone platform. Whether to use a cloud integration solution is, in the end, a question of fit with the company’s IT strategy. That said, we are seeing many more firms that are open to giving it serious consideration as they hone their overall IT strategy to add greater value to the business. The case for focusing available staffing on manipulating the data for business projects is simply too strong to justify siphoning off staff for integration.
Companies who are considering a managed cloud service are wrestling with two strategic questions. First, how do they maximize the portion of their available staff that is dedicated to working on problems that directly impact business outcomes? Second, how do they provide world-class integration of their data and applications as a foundation to everything else that they do?
To the world-class integration question, the dPaaS model creates an integration “Center of Expertise” in the cloud. This is one of the core competencies of the dPaaS staff. They deal with it 24×7, have the sophisticated processes to drive productivity improvements and drive down risk, and have learned from use cases across a portfolio of companies, enabling them to rapidly move up the learning curve.
To the question of how to shift the maximum amount of talent to projects with direct business impact, many organizations face an additional challenge. Even if there is sufficient budget, an organization may be constrained in the number of people it can hire by a separate process. By bounding the overall permissible headcount, a situation of scarcity and opportunity cost is created. For every 10 people hired to do mundane but necessary projects such as integration, 10 fewer data scientists, data analysts, or data modelers can be hired. What is the optimal staffing mix? 20% data experts; 30% integration experts; 50% applications personnel? Or 45% data experts; 5% integrations experts; 50% applications personnel?
The IT leaders who choose to shift their staffing mix towards the data experts that work directly on business problems (the second case, above) are, in my experience, the best fit for a cloud-based fully managed service. Again, this choice is not for everyone.
After all, some people love Android phones and some love iPhones.