data-nerd.blog

Looking Back to Go Forward: 20 years in Software

You know when someone casually mentions they’ve been working for 20 years, and you think, “Wow, that’s a long time” only to realize…wait, you’re that person? Yep, that’s me. This year marks 20 years in software, and it feels surreal.

In 2004, I started as a fresh graduate at McKinsey & Company. I was excited, nervous, clueless, and had no idea where this path would lead me. Two decades later, I’ve worked with some of the best teams at McKinsey, Microsoft, Target, and, yes, Microsoft again—because sometimes you come full circle.

So, here’s my look back at 20 years in software—20 moments, lessons, and memories that shaped this journey:

Why I’m Excited for POSETTE 2024: An Event for Postgres

I’m happy to share that I’ll be speaking at POSETTE: An Event for Postgres from June 11-13, 2024! 🚀 It’s a huge honor to be chosen to speak at this awesome event, and I’m thrilled to be part of such an amazing lineup of speakers.

About My Talk

My talk, “What Makes Azure Database for PostgreSQL Great for Developers?“, is something I’m particularly excited about. I’ll cover key features like integrating essential extensions such as pgvector and PostGIS, and simplifying deployments for Azure Database for PostgreSQL Flexible Server. It’s all about making cloud development smoother and more efficient for developers.

Mastering Data Manipulation with MERGE Command in PostgreSQL 15

Two years back, I wrote a blog post titled “PostgreSQL – Mastering UPSERT“, in which I explored the nuances of the INSERT ON CONFLICT command that allows conditional inserts or updates of rows.

Continuing its database technology innovation, PostgreSQL 15 has introduced an exciting new feature – the MERGE command. This command offers a more versatile approach to INSERT, UPDATE, or even DELETE rows in a table based on specific conditions. In this post, we’ll delve into the intricacies of this new MERGE command.

My talk at Citus Con 2023

I’m excited to be speaking at Citus Con 2023 on April 18-19 on reducing your PostgreSQL costs on Azure managed Postgres.

In my talk, I’ll be sharing tips and tricks that can help you save money without sacrificing performance. Join me at the upcoming conference to learn more about how you can optimize your Azure PostgreSQL deployment and reduce your costs.

https://www.citusdata.com/cituscon/2023/schedule/#od-session-dhawan

Whether you’re just getting started with Azure Postgres or you’re a seasoned pro, my talk will provide valuable insights and tips for optimizing your use of the platform. I’m looking forward to sharing my knowledge with the PostgreSQL community and learning from other experts in the field. See you at Citus Con 2023!

“Sharing your knowledge and learnings about Postgres—or Postgres extensions (like the Citus database extension)—is a useful way to give back to the community. Your talk can help other teams & projects learn from your successes (and mistakes) with Postgres.”
@clairegiordano

Thank Claire, for your inspiring words. They have really motivated me and given me the encouragement I needed for giving this talk. 🙌

2022 – My Year in Books 📚

It’s that time of year when I am excited to share the books I have read! It’s one of the self-created traditions that I look forward to every year.

This year in 2022, I’ve read some great books and watched a few amazing documentaries — some are new releases, some older, but each one of them truly made me a better person this year.

I’ve been posting my “My Year in Books” for last couple of years. I believe that sharing books is an easy way to connect with like minded folks. ❤️

In no particular order- let’s go!

PostgreSQL Advanced Pattern Matching – Beyond LIKE Operator

Whenever you are dealing with pattern matching in PostgreSQL, it is often required to write queries to match string patterns. The conventional wisdom to do pattern match was using the LIKE operator, which is not very effective for many reasons. PostgreSQL now offers more advanced pattern matching options such as SIMILAR TO expressions, POSIX regular expressions, and ANY operator. In this article, we’ll compare the LIKE operator with these other advanced pattern matching features.

Data Science with PostgreSQL – Using the Window frame_clause

This is my 5th (and final) post on Window Function in PostgreSQL series. In previous posts on this topic, I have covered window function basics, using aggregate window functions, ranking window function and value window functions. While you’re here, I’ll recommend to you check the previous posts on this topic.

In this article, we’ll learn a new concept frame_clause. Let’s jump right in!

Data Science with PostgreSQL – Value Window Functions

This far in the Window Function in PostgreSQL series I have covered window function basics, and how to use aggregate window functions and ranking window function. I suggest you check the previous posts out 🙂

In this 4^th post, I’ll show you how to use Value window functions – that can be used to calculate various “value” type aggregations such as Lag, Lead, First_Value and Last_Value within each group of rows referred here as “window” or “partition”.

Data Science with PostgreSQL – Ranking Window Functions

This is 3rd post in my series featuring Window Function in PostgreSQL. In this post, I’ll explain how to use Ranking window functions – that we can use to calculate various aggregations such as Row Number, Rank, and Dense Rank within each window or partition.