Data with AR
Stories About Data {Science, Engineering and Architecture}
Data and Dough
Tradevesting Notes
Note: These are my notes from online classes available on
Why some organizations with ML/AI use cases are moving away from the cloud?
Cloud computing isn’t going anywhere, but some companies using ML/AI are shifting to on-premis...
Skills Required for a Data Engineer
There is no formal path for a data engineer, but there are knowledge-base and skills a data en...
My Journey in Data Technology Field
Today, I have completed 17 years in IT industry,
From Data Science to Data Engineering to Data Architecture
How is the focus of the industry is shifting from data science to data engineering to data arc...
Evolution of Data Engineering Field
How data engineering field has evolved over the years?
Data Industry has (kind of) come to a Full Circle
Back in 2012, I was working as a data architect when I first time heard about data science and...
Reliability in Data Systems
Reliability can be defined as continuing to work correctly, even when things go wrong.
3 Aspects of Data Systems Design
While designing a data system, apart from functional requirements, we need to tackle non-funct...
Why a generic term named Data Systems?
Why a generic Data Systems term is more suitable than Data Storage, Processing and Analytics S...
Challenges of Data Systems
~ Notes from ‘Foundations of Data Systems’ part of ‘Designing Data-Intensive Applications’
How to build a data-driven organization?
There has not been an exciting time than this to talk about data. Data iseverywhere, it is be...
Building Data Analytics Ecosystem
In this post, I am going to cover how you can build a data analytics ecosystemin your organiz...
Deep Learning Landscape
Here we try to understand Deep Learning landscape….
Data Science vs Data Engineering vs Data Architecture
In this article, lets understand what is the difference between Data Scientists, Data Engineer...
End-to-End Data Science Process
9 Movies Every Data Scientist Should Watch
5 Data Science Use Cases for Every Business
5 Books Every Data Professional Should Read
Data Science is a Team Sport
Kaggle Vs Real-world Projects
How to approach Data Science in 2020?
SQL for Data Professionals (Beginner)
Data & AI Session @ RBS
Data Professionals, and NOT Data Scientist, is the Job of the Century
Cloud Computing for Data Professionals
Becoming Data & AI Specialist on AWS Platform (for free)
A Brief History of Data Systems
From Data To Actionable Insights
AI Sells, Data Delivers!
5 Data Science Use Cases for Every Business
Data & AI Platforms — Open Source Vs Managed Services
Architecting Modern Data Platforms
5 Tips for DS/AI Beginners & Enthusiasts
Useful Resources to Learn Artificial Intelligence
Artificial Intelligence from Novice to Professional
Building Blocks of Artificial Intelligence
How to Navigate Artificial Intelligence Landscape?
AI For Everyone Course Review & Key Takeaways
How to build your career in Artificial Intelligence?
Artificial Intelligence for Business Leaders
4 Types of Challenges in DS/AI Projects & Initiatives
Getting into Machine Learning & Artificial Intelligence
Making Your ML/AI Career Future-Proof
Networking & Landing the Job
Building Your Portfolio in Data & AI
Utilizing the Resources
Becoming Data-Driven with Data Catalog
Working on Building Blocks
Navigating the Landscape
Understanding the Big Picture
Data Science Self-Starter Handbook (Preview)
Data Science Introduction
AMA Session with AR on Data Science
Dealing with Noisy Data in Data Science
To Kaggle Or Not To Kaggle?
Bayesian Statistics for Data Science
Descriptive Statistics for Data Science
Data Science Beginners’ FAQs
Data Science Learn Apply Compete Ask Connect Stay Updated
Who needs a Data Engineer?
Having only Data Scientists is not Enough
Deep Reinforcement Learning
Data Science Digest
Data Literacy for Professionals (Series)
Becoming Data-Driven (Series)
Data Science Framework
A ...
Data Lakes in Modern Data Architecture
Da...