Re-thinking Insights

Until now, the analytics and insights functions have been shaped up incrementally, and as data has increased, tools have evolved, the way to reach insights has transformed. Insights and analytics is significant for a business simply because it helps the way business makes decisions, and evaluates whether the current strategies

Transitioning from Narrow AI

How is the ideology of AGI slowly changing the fiction into reality? Sci-fi movies have always provoked us to think beyond our reality. Some of the reality came to life in the past few years - with LLMs, image and video models changing the way we think and work. These

Databricks AI/BI Genie - how good of a Genie it is?

With AI penetrating the analytics industry, maturity of solutions across different analytics lifecycle varies. Amongst different analytics areas, exploratory data analysis or EDA is relatively an easier space for AI to mature in the next few years. Companies across all industries have been trying out solutions to automate this relatively

Good Reads Books Analysis

Books fascinate me a lot and I really enjoy learning about interesting books, what are the likes and dislike of readers, and what could be my next potential read. I leveraged the dataset available on Kaggle - and decided to create a dashboard. I have been wanting to do some hands

The Art of Saying 'I Don’t Know

Data scientists are shaped through asking the right questions. Many of the things in the world are easy explainable. However, many are not. One of my favorite fields within analytics is forecasting. This is because its beautiful in my ways - forecasts can never be perfect, they are always full of

Blogs

How Will Data Teams Look Like in 2030?

A. How does data team look like today? When I took my first role in a data team, I was working alongside my consultant and supporting a group of clients, and my job was to curate datasets, often turn them into a report, and draw insights from the report to

World of Consulting v/s Corporate

As I have experiences across both - the world of consulting and4 industry, I often get asked about this question as to what is the difference, which one is better and which one leads to better growth opportunities. Since the answer is not too straightforward and totally depends, I have tried

Book Review

Why should we read Ikigai?

Have you ever thought of - what affects our ageing, purpose, life elements and well being? Humans age at different rates, and their happiness quotient changes as they age. Some people become happier, while for some, the purpose starts to subside. Ikigai has been one of the best reads to help

Why People Ignore Good Data – and Trust Their Gut

We have always learnt that mathematics is a concrete field wherein we can expect right or wrong answers. Statistics is composed of deep mathematical concepts and is a way of taking significant decisions across every sphere and sector. The question then arises - is statistics an explicitly reliable field? Can we

Blogs

Hands on exercise - LangGraph

In the LLM world, LangGraph is something most of you might have heard of at least. In my last post, I explained the Lang series including LangChain, LangGraph and LangSmith. LangGraph is an extensive version of LangChain and helps us create Agents. According to the textbook definition of LangGraph - "

What are LangChain, LangGraph and LangSmith - simply explained

I have come across the terms: langchain, langgraph and langsmith so many times since the agentic AI world took off. These terms and their classical textbook definitions always confused me, and the clarity came only by reading a lot, and doing some hands on exercises. Post understanding the fundamentals clearly,

Blogs

How to calculate ROI for studying abroad?

So many aspirants have pinged me on LinkedIn to ask me questions about pursuing a masters abroad, and how has my journey been. One of the common questions I get a lot is - whether the ROI of the education would be good enough? In this blog, I will try to

Blogs

Generative Machine Learning: is it the next big revolution?

As AI tends to take over the world, the revolution is deepening at a fast pace. This pace is probably higher than what was expected. The reason for this high pace is the opportunity - to operationalize, automate, create, and save costs. Everyone wants to do AI today - however, only some

Blogs

Great things take time: the world of medicine breakthroughs

My mentor advised me to read this book called Breakthrough: The quest for life-changing medicines. I did read it, and I loved it. It is not only insightful and knowledgeable, but it is also an eye opener. I did always know that drug discovery is very difficult with years

Blogs

I analyzed my website through LLMs - OpenAI API integration

Introduction LLM APIs has made so many things possible today. The integration simply makes it possible to speak to the LLMs like never before and perform and automate so many tasks for us. We can integrate it to summarize documents, ask questions, perform chat completions, generate images, and n number

Blogs

Turning my goals into a framework

While working through my goals for 2025, I was trying to make goals which are achievable, fun and exciting. Otherwise, goals are made and then just forgotten through the rest of the year. I tried to do something different this time. I usually love structuring things, and creating frameworks; it

Blogs Featured

How will AI revolutionize data & analytics?

Introduction AI is the cornerstone pillar of many industries and with this relatively new area in terms of its maturity, AI is being explored in multiple industries and functional areas. Similarly, AI has had a huge impact on how data analytics industry is operated, perceived, and disrupted. Data Analytics is

Book Review

Book review for one of my most favorite books of all time: 438 days

Have you ever read a book like its a movie going on and you cannot stop but keep reading the book to know what happens next? This book is exactly that! And that is the reason this is one of my favorite reads till date. What this books is about?

Book Review Featured

Is our Economic Perspective right?

How do we generalize and perceive the world has an impact on our success and failure factors. Success is not set in stone, it is subjective and can be interpreted in millions of formats. For instance, a person could have a millions of dollars and still might lack the necessary

Blogs

GenAI: where to tap so we don't fail?

Why is this area so hazy? Predictive analytics & self serve has been in the market for sometime and with this new area, it is becoming not just exciting but also blurry. With so much pressure from senior leadership to do GenAI proof of concepts, some of the concepts are

The Ideal Data Analytics Method

Section 1: Design Better Questions Robert Peng explains why he reads John Tukey's paper on The Future of Data Analysis every year and every time he reads it, he finds a different outcome and learning. He shares a spectacular line in the paper saying: Far better an approximate

Book Review

Book Review - The Drunkards Walk: How Randomness Rules our lives

The book was just waoo! Why I read this book? I wanted to read a book well connected to the depth of statistics but is not a classic statistics textbook. A book that goes out and speaks about statistics through the roots. This book was just that book - it has

Blogs

Bayesian v/s Frequentist Statistics

Introduction In the intricate world of statistics, it's akin to navigating two distinct clubs with their unique vibes—welcome to the realms of frequentists and Bayesians. Starting your stats journey often involves joining the frequentists, and exploring classic techniques such as t-tests and ANOVA. Yet, as you

Blogs

Bayesian Statistics Implementation

Welcome to the blog where we dive into the world of Bayesian inference models! In this exploration, we'll unravel the magic of Bayesian statistics by implementing it in two practical examples. Get ready to demystify the Bayesian approach as we walk through real-world applications, sampling posterior distributions,

Blogs

Connect the dots for Generative AI: where it all got started?

GenAI, ML