Work Musings...

  Photos from Unsplash.com: Srikanth D (Indian flag)  and Danny Gallegos (USA flag) Friday, June 25th 2021 @ 10.26am... I took the oath of allegiance to become a naturalized citizen of the US. It is the culmination of a 21-year process of my move from India to the US: being an international grad student applicant to Virginia Tech to a non-immigrant (Student, Temporary work visa) to an immigrant (Permanent Resident/Green Card Holder) to a US citizen. The biggest time was spent in going from work visa to Permanent resident with the long wait times for an Indian citizen. It is the end of a lot of waiting, a lot of checking the status of various applications on the USCIS site, and a LOT of documents including a notarized statement from my mom attesting to my birth! The two overwhelming emotions I felt after the oath ceremony, getting my certificate of naturalization, and walking out of the office were Acceptance and Relief.  Acceptance: It felt really good to be welcomed and...

It's a blog after a 1.5-year gap...  Recently, I had the chance to attend a webinar/zoom panel discussion on Building Effective Data Science Teams organized by RStudio. It was an interesting conversation - I highly recommend spending the hour to watch if you are interested in this field.  I'll summarize some key takeaways from the discussions for me and some thoughts from my side.  1. Communication, Communication, Communication! The panel could not have stressed more the need for MORE communication between the data science team and the various stakeholders (business/functional team, internal customers, etc.)  Data Science(DS) teams/Software Developers tend to like to work in a cave and only like to emerge with a shiny (pun intended!) new object - this is a high-risk game. More communication with the stakeholders allows for the project to be focused/aligned with everyone's expectations and more importantly, creates a sense of 'joint-ownership' of the project and th...

I would like to post updates here with samples of some of my data science work. This is the first post of such work done in R and published on RPubs http://rpubs.com/Prabha/National_Parks_1

This is the AI panel discussion content post. The panel was sponsored by RSM. George Casey  - Panel Moderator, Principal at RSM Larry Fulton  - Professor of Data Science at Texas State University Dale Sayers  - Cloud Solution Architect at Microsoft The discussion centered around the current use and best practices of ML/AI in industry. Here are some of the key takeaways and my thoughts from the panel discussion. This is also based on follow-up conversations with various members of the audience. 1. AI/ML application, implementation is still low and unclear to most organizations Based on my interaction with people at this conference, the companies present were closer to the beginning of the AI/ML journey. To be honest, there were not a lot of pointed questions from the audience. The discussions were more around specific software tools - ML/AI is not a piece of software or a toolset. The application of AI/ML has to align with the strategies of each organization and ...

Public speaking has been an aspirational goal. I've not had too much opportunity before nor have I actively sought it out. It was this 'thing' that looked sooooo cool and people doing it were really cool! However, there was a fear of failure that was overwhelming enough for me to not make that leap - public failure, nonetheless :) In the last year or so, I have applied to speak at a few conferences on the topic of Analytics/Artificial Intelligence(AI)/Machine Learning(ML) applied in the space of Supply Chain Management. What I have learned in many cases is that the conference organizers are engaged in a 'Pay for Play' scheme. A speaking slot is up for sale with the purchase of a display booth or being a sponsor of the whole conference. I am not judging the conference organizers - I fully realize, agree and support the commercial realities of putting on a show. The shock was the pervasiveness of this model and that clash against my naivety.  An opportunity poppe...

Last week, I was happy to attend a conference on AI in San Francisco - AI Summit SF 2019 . There were some good talks at the conference. Here is  a summary of some learning, highlights and take-away from this conference. 1. ML/AI advantages and value are real:   Companies are creating tangible value from 'institutionalizing' AI technology to their competitive advantage.  The trend is seen to be spreading across the various large corporations much beyond the major players . There was a good presentation from American Express on how AI was used to create 90+% (!!!) efficiency in their Analytics team work. However, the Big Four are clear leaders in this space 2. Competitive Differentiation and Enterprise Adoption:   KPMG made a good presentation on top trends in AI space and key takeaway here is that AI will be a key differentiation in competitive landscape of various industry verticals (Not exactly breaking news). 3. Stumbling blocks: The third topic is a li...

Hello World! Some introduction is in order 😀. I am Prabhakar, a mid-level manager in a fairly large company. For the last 9 months or so, I've been wanting to start a work related blog. A valid excuse for the last 4+ months can be our new daughter! But, I have no excuses for the ~ 5 months prior to that. Lately for work, my main interest topics have been in the field of Data Science, AI, ML and building a team to execute on these technologies. It's been slow going, to say the least. On a personal level, it is super exciting to be involved in this focus area at work in my company. There is a bit of a pioneering spirit involved as a lot of the projects being worked on are treading new ground, raising a bunch of questions and creating opportunity. And, I like to hike and be outside. So, will make this blog more enjoyable with some random pictures - this is a recent one from last week @  Marina State Beach, Monterey CA .