The purpose of this blog is to provide a forum for architecture, technology and data science topics from a practitioner's point of view. These are my own opinions. I would like to expand my horizons by sharing with you what has worked for me in the past with the hope that you will do the same by publishing your lessons learnt to enable commercial services, digital products, enterprise systems, business applications and platforms.
Has Anyone realized ROI with Cloud Computing ROI?
Question to the viewers of this blog is how many have used concepts of cloud computing (and I do not mean private clouds, here)? Are you looking at Cloud computing for reduction in infrastructure costs by moving to a pay as you use concept or to augment your peak capacity or else are you using cloud sofware as a service?
What is your experience and are you realizing the ROI as in a lowering of your TCO, or increase in operations efficiency and availability?
Fellow Bloggers – My role is to create & deliver digital products and solutions that help deliver value to the customer and increase customer loyalty. As an architect of these solutions I am constantly striving to effectively leverage Big Data, NLP and data science techniques. However, when it comes to data science I always struggle with the concepts of machine learning (ML) and artificial intelligence (AI) . In this blog I embark on a quest to find a way to set apart the concepts of ML & AI and to simplify the decision of when to apply which of these two concepts. In just the past couple of years, ML/ AI have magically penetrated into all aspects of our service industry - from automating a manual process to driving cars to offering self-help assistance to recommending next best offers to automation of complex decision making. So the question becomes are these algorithms "simulating" the human or just "mimicking" the human. Do they b
It is one thing to read about Internet of Things (IoT) and get dazzled by the commercial opportunities it offers based on the stats like the number of connected devises there are in the world today. Or how more and more consumer products are getting connected to the "grid" to enable remote monitoring/ operations. Despite all that, it is unclear as to how an enterprise would be able to make a strategic decision about benefits of an investment in IoT. How would it know if their business model or product portfolio or customer base would gain from this investment? I am looking for any case studies, market research material that might help in this analysis. Are there players (established industrial giants and/ or manufacturing heavy-hitters) who have adopted this technology and gained market share or helped make significant product improvements and /or branch out into services not possible before the advent of IoT. Some notable companies come to mind in this space -
A lot of talk has been heard lately about the concept of data lake. Variously known as, data refinery, data factory etc. I find it interesting that we now hear logical architectural terms that speak to the concepts and to the purpose of the big data technologies such as Hadoop / HDFS and Apache distributed database technologies such as HBase / Cassandra . This may be indicative of a shift. What I am not sure of is does this mean that there is a level of maturity that has been achieved by this suite of open source technologies? Or could this point to the fact that these technologies have practical applications that solve enterprise scale problems? Or does it show that enterprises have realized that they are no longer able to just deal with "structured data" and that a vast majority of information lies in the space of "unstructured content" leaving them no choice but to venture into the realm of big data technologies? Not really sure! The fact re