Category: Trends

Your entire analytics stack, just a few lines of code away

Your entire analytics stack, just a few lines of code away

Amrutha GujjarAmrutha Gujjar11/15/20244 min read

With a code-first approach, you can automate the entire setup process and start running analytics directly on structured data with minimal effort.

AWS, S3, Iceberg, data lakes and the future of simplicity

AWS, S3, Iceberg, data lakes and the future of simplicity

Amrutha GujjarAmrutha Gujjar12/04/20245 min read

For the past decade, data lakes have become a standard way for companies to manage massive amounts of data. But they’ve also become a minefield of complexity.

B2A: The future of analytics isn’t human

B2A: The future of analytics isn’t human

Amrutha GujjarAmrutha Gujjar02/10/20255 min read

“Make something people want” has long been the mantra of startups. But what happens when humans aren’t the ones making decisions anymore? The analytics tools we’ve built are fundamentally broken for this new world.

Building a configuration-driven analytics stack

Building a configuration-driven analytics stack

Amrutha GujjarAmrutha Gujjar11/10/20245 min read

If you deploy a containerized app, it behaves the same on your laptop as it does in production. So why can’t our analytics dashboards do the same?

CSVs are not databases

CSVs are not databases

Amrutha GujjarAmrutha Gujjar02/23/20254 min read

CSV files seem simple. Just plain text, right? But when they get large, they are not great formats for data exploration. CSVs lack indexing, compression, and structured access.

The rise of DIY software (and why developer tools matter more than ever)

The rise of DIY software (and why developer tools matter more than ever)

Amrutha GujjarAmrutha Gujjar02/02/20254 min read

We’re moving away from rigid, one-size-fits-all enterprise solutions and toward a world where individuals can quickly build the exact tools they need. And that means developer tools (especially open-source ones) are more important than ever.

If data apps were 10x or 100x easier to build, what would get built?

If data apps were 10x or 100x easier to build, what would get built?

Amrutha GujjarAmrutha Gujjar12/12/20246 min read

If you could build data apps at the speed of thought—what would happen? When building data apps becomes this fast, this cheap, and this effortless.

The “Electric Tea Kettle” problem in data tooling

The “Electric Tea Kettle” problem in data tooling

Amrutha GujjarAmrutha Gujjar12/19/20244 min read

Sometimes the shiny, purpose-built solution isn’t actually better. Sometimes, what we need isn’t another feature-rich gadget, but something simpler, more versatile, and less likely to create chaos down the line.

LLMs for Analytics is more than ‘text2sql’

LLMs for Analytics is more than ‘text2sql’

Amrutha GujjarAmrutha Gujjar01/10/20254 min read

Sure that chat-with-your-data app was cute in 2022. If you’re handing over the keys to an LLM without interrogating its output, you’re outsourcing the very thing that makes analytics valuable: human curiosity and creativity.

Local testing for analytics

Local testing for analytics

Amrutha GujjarAmrutha Gujjar11/13/20246 min read

Testing in production? Brave. Testing locally? Smart. This way, you can catch issues early, handle edge cases, and keep data secure.

Notebooks, data app builders, and IDEs in the Age of AI

Notebooks, data app builders, and IDEs in the Age of AI

Amrutha GujjarAmrutha Gujjar12/03/20244 min read

The best tools change how you think. Spreadsheets turned numbers into something interactive. Notebooks made code a storytelling medium.

Why isn’t there a BI Tool designed just for parquet files?

Why isn’t there a BI Tool designed just for parquet files?

Amrutha GujjarAmrutha Gujjar01/16/20254 min read

If you’re new to Parquet, think of it as a data format optimized for analytics. Unlike a traditional spreadsheet or a database table that stores data row-by-row, Parquet stores data column-by-column.