Some artifacts about the Data ecosystem of today, revolves around a few touch points. Firstly the volumes as well as the variety of Data will only increase with time. Thereby, the volumes and variety of Data Models would also increase. That would trigger a need for Speed of Insights Generation. Also, all of this would most likely be driven through an Open Source ecosystem, with the advent of internet driven technologies such as IoT, ML, AI and the likes. Hence Businesses would demand for outcomes sooner. How do you manage all of this ?

Cloud is definitely the answer for most of the above going forward, and it can be managed over Public, Private or Hybrid environments. Also the advent of Serverless Technology ensures that a cloud service provider will give provisions to its subscribers to run their produced code on the Cloud Fabric, which can also lead to distributed ecosystems.
We combine our Data prowess with a Cloud frontal approach with expertise on specific services with Amazon Web Services (AWS) and Microsoft Azure. We can devise a number of quasi or hybrid ecosystem merging Edge with Cloud, our IoT with Cloud, in terms of deriving the optimal data benefits for our customers. A typical Cloud hierarchy, from an approach standpoint would look like: