Sunday, June 19

Don't waste your evening at office. Your kids have somuch more to give to you! Happy Fathers Day!

Most wonderful day of the year to be with my son Ishaan, my niece Alisha, dad & mom. Feels wonderful to have the little ones spread all the joy in my life & cherish the love showered by our parents.

Every year take couple of day off, get away from laptop, tablets & phone and spend the day exclusively with your kids. You realize that there is so much more in life than Big Data & Digital! There  is so much more than keeping your clients and boss happy. There is Figaro the cat, Hot wheel cars, making cardboard Car Garages & Doll houses, playing pretend cooking & hunting non existant Dinosaurs that come in the night! Spending time with kids is so much fun and super exciting! So don;t waste your evenings at office


Thursday, June 16

Digital India before Digital World

Past one year Indians have been riding the Digital Wave, from the prime minister to the local MP everybody wants to do something to be part of the Digital India wave. Funny thing is when I came across our local Member of Parliament he told me his idea of going Digital was to launch his long pending website ! I could not resist and I ended giving him a 5 mins Booster Lecture on Digital. I will share my view of Digital India and how India is implementing Digital at various level at a later date. As 2016 begins to settle in, now is the ideal time to look at how technology will be driving digital transformation in businesses.
The digital transformation wave
While new technologies continue to provide the ability to transform business models, effectively engage customers and improve efficiency of business operations, the majority of organisations were still struggling with the basics in 2015, trying to keep up with the application backlog and managing IT infrastructure and user devices. At the same time,  forward-looking organisations are putting user or customer engagement at the top of their technology agendas. Led by the need to think about the entire customer engagement journey, across all digital platforms (mobile, web sites and so on) and in-person interaction, more and more companies will focus their efforts on their own digital transformation in 2016. They will extend traditional systems or systems of record that house core data assets, by delivering applications that engage customers and employees more effectively and provide analytical insight. Organisations that don’t make this transition will be left behind.

From leveraging Big Data to the modernization of core business applications, the to-do list for everyone from the CTO to the CIO to your developer team has never been greater. So what are the key factors driving digital transformation? 
1) The modernization of core business applications
To compete in this increasingly mobile, social world, companies must find ways to engage customers and prospects in a more digital way. Modernising apps to play well in the digital space will be a must. The websites built by sophisticated market players who realize digitizing the enterprise is a critical component of future success will proliferate; no longer is the website a simple billboard for the company, it is an interactive, dynamic resource that encompasses the next generation of application development. 
2) Digital interactions merge channels and break down silos

In 2016, biggest realization for organizations should be 'There is no web & mobile strategy : only a customer-centric digital strategy, regardless of channel'. There is no marketing data, sales data and support data : only the customer life-cycle data. Companies will endeavor to provide the best experience based on the combination of individuals and where they are in the lifespan of their relationship with the organisation, from new prospect to long-term buyer. In 2016, digital strategy will mature as companies get serious about bringing together all customer and prospect information and goals, and how best to serve them with a single, continuous digital strategy. Recently Airtel has decided to share the location of their mobile towers with their customers to bring in more transparency, a month back the mobile companies refused to share the data with customers! The past five years were about bringing commerce, marketing, sales and support online. The next five will be about bringing them together by understanding the journey and making it better, cheaper and faster. 
3) Big data insights will be extended to the enterprise including mobile devices 
today the choice of applications that leverage big data, machine learning and so on is where the advantage lies. This first wave of big data focused on the infrastructure stack–storage, scale and integration. It’s actually the next wave of technology that is more exciting because it will make big data mainstream and consumable by everyone. Companies will stop thinking about big data as a big data warehouse to be managed and scaled. Instead, they’ll think about the marketing analytics application that automatically provides the next best piece of content to users and drives higher conversion levels. True big data value will emerge from this next wave of applications and services.

From 2016 to mid 2017 we should see 'Watchers' evolve from reading about Big Data transformation to actively implementing it themselves. The success of the competitors is going to drive the late starters to evolve to survive if not to succeed.



Sunday, June 12

Should you learn Phyton or R ? - For Aspiring Data Science Students

Why Python is preferred for data science

  • Guido van Rossum created Python
  • Python was released in 1989. It has been around for a long time, and it is object-oriented
  • IPython / Jupyter’s notebook IDE is excellent.
  • There’s a large ecosystem. For example, Scikit-Learn’s page receives 150,000 – 160,000 unique visitors per month.
  • There’s Anaconda from Continuum Analytics, making package management very easy.
  • The Pandas library makes it simple to work with data frames and time series data.

Why R is preferred for data science

  • John Chambers created R and prior to that he created S
  • R was created in 1992, after Python, and was therefore able to learn from Python’s lessons.
  • Rcpp makes it very easy to extend R with C++.
  • RStudio is a mature and excellent IDE.
  • CRAN has many machine learning algorithms and statistical tools.
  • The Caret package makes it easy to use different algorithms from 1 single interface, much like what Scikit-Learn in Python
I started by learning R and then picked up Phyton. I personally think Phyton is much more versatile than R but it is good to learn both the languages.

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