Databricks Data Intelligence Platform

What do you like best about the product?

Databricks has been solid for our workloads. Delta Lake and Unity Catalog simplify governance, and Spark SQL speeds up SQL processing. I love the improved cost visibility for the AI functions used and the faster deployment of clusters and DBX resources.

What do you dislike about the product?

Nothing in particular, but I feel the dashboard charts are pretty basic.

What problems is the product solving and how is that benefiting you?

DBX’s document intelligence function has a lower extraction cost per document than traditional agents like Claude or ChatGPT.

What do you like best about the product?

Combo of lake house with lakebase supports advanced metadata management. We created a metadata oltp like metadata model in lakebase supporting advanced automated pipeline builds, PHI protection and governed tagging for dlp

What do you dislike about the product?

Finops particularly with ever expanding genie offerings that sometimes seem like it’s doing simple actions with added token overhead costs

What problems is the product solving and how is that benefiting you?

Isolating phi from metadata management allows us to use various sourced labor to build and maintain the metadata foundation while protecting our data

What do you like best about the product?

Genie is a game changer for us. Using it to build data pipelines makes my life 10 times easier.

What do you dislike about the product?

Not much. I like a lot more things than I dislike. If I had to decide, I would say that sometimes the compute costs can get pretty high, and things can sometimes get slow.

What problems is the product solving and how is that benefiting you?

It’s helping me reach more people in my organization. As a data scientist, one of my responsibilities is to try to automate manual processes and make other people’s lives easier. Databricks makes me look like a magician, when in reality the platform is the one with the magic.

What do you like best about the product?

I use Databricks to bring scattered client data from older systems into one workspace and prepare clean tables for our consultants. Scheduled jobs keep the tables current, so we can work from reliable figures, and I can trace numbers back to source records to support the advice we give clients. Its data connectors bring in exports with little friction, and setup was quicker than I expected—I had a working workspace and my first pipeline running within a few hours. Genie gives me a first draft of a table or transformation, so I can spend my time checking the logic instead of writing routine code. I also value Delta Lake time travel for comparing an earlier table version with the previous load, and Unity Catalog’s lineage view for seeing which source tables feed downstream tables and assessing the impact before I change a transformation.

What do you dislike about the product?

My main reservation is the Python editor. Smarter autocomplete, clearer inline error highlighting, and stronger debugging tools would make custom scripting less laborious. Too often, I only find a small mistake after running a notebook. I’d also like clearer cost visibility, since it’s hard to tell in advance how much a large job will consume.

What problems is the product solving and how is that benefiting you?

I use Databricks to bring scattered client data from older systems into one workspace and keep clean tables current with scheduled jobs, so our consultants can analyze reliable figures. I can quickly trace questioned numbers to source records, keeping our advice to clients well supported.

What do you like best about the product?

Lots of helpful vendors willing to assist with questions or issues

What do you dislike about the product?

Not much just that Genie does not have a powerpoint creation feature

What problems is the product solving and how is that benefiting you?

Conversational analytics for dashboards

What do you like best about the product?

Everything in one place. SQL and Python in the same notebook, right on top of the medallion tables, no moving data around. Delta history is lifesaver when numbers don't match

What do you dislike about the product?

While it has significantly become better, still clusters can take a while to be activated. Also the dashboard has significantly improved though not there yet tbh.

What problems is the product solving and how is that benefiting you?

Before the data was spread across different places and checking report numbers took forever. Now the whole pipeline lives in one place, so I can trace a number from raw events to the final reports and validate it much faster.

What do you like best about the product?

What I like is that, from day one—on that very same day—I can move straight into a production workflow without having to set up the infrastructure from scratch or request permissions from another team. I really like that.

What do you dislike about the product?

For now, I’d simply like the costs to be more predictable and transparent, both at the project level and across the team.

What problems is the product solving and how is that benefiting you?

Now, with Databricks, everything works smoothly because it brings processing, storage, orchestration, governance, and collaboration together in one place. I couldn’t ask for more, and that’s why we’re so happy with it.

What do you like best about the product?

I appreciate how the platform adapts to my scaling needs, even when my workload fluctuates—ranging from small-scale tasks one day to processing historical behavioral data the next. Throughout these shifts, the system remains reliable. I also particularly value that it serves as a shared space where my Growth Marketing team can collaborate with the engineering, data science, and sales teams, all within Databricks.

What do you dislike about the product?

I expect the control panel to become more intuitive for business users, and for a more natural bridge to be created between campaign-related queries and analysis notebooks.

What problems is the product solving and how is that benefiting you?

It resolves metric-related issues that arise when marketing, sales, and product teams measure different things using different definitions, which can make decision-making political rather than analytical. It also addresses, in particular, the need for speed in experimentation: testing a growth hypothesis requires up-to-date, reliable data.

What do you like best about the product?

Good tool for engineers even with low coding knowledge

What do you dislike about the product?

Need to spend good amount of time to figure out optimal settings to optimize usage cost

What problems is the product solving and how is that benefiting you?

Helping with connect with internal datalake and run optimization problems