Parquet data your whole team can question, not just the person who wrote it.
Load a Parquet file and every column is described in plain English and graded for quality, so a colleague who has never opened one can ask it questions. Headers and blank values are cleaned on arrival, and nothing is guessed at.
On Arrival
Your Parquet file is tidied on upload
without anything being guessed.
Every Parquet upload goes through the same pass of hygiene before anything reads it.
Done for you, every time
AutomaticHeaders normalised
Trimmed, spacing collapsed, unsafe characters replaced. Unnamed columns get real names, and duplicate names are made unique.
Spreadsheet error cells emptied
Values like #N/A, #REF! and #DIV/0! are not data. They become empty rather than text that would distort the column's grade.
Invisible characters removed
Zero-width characters, non-breaking spaces and mixed line endings - the things that make two identical-looking values fail to match.
Blank cells made genuinely empty
Many exports write an empty string instead of a real blank. Left alone, the column scores as complete when it is not.
Date separators made consistent
A column mixing 15-01-2024 with 20/02/2024 stops being readable as dates. Only the separator changes - never the order of the numbers.
Empty rows and columns dropped
A column that arrives entirely empty is dropped, and you are told which - because in a spreadsheet that usually means a formula was never calculated before saving.
Nested fields opened out
A field containing further fields becomes one column per value, at any depth. Nothing is lost or combined.
Left for you to decide
Never automaticDuplicate rows are not removed
Removing them assumes what makes a row unique. Two identical order lines can be two real orders.
Blanks are never filled in
Substituting an average or a nearby value invents data and quietly bends every statistic computed afterwards.
Types are not forced
Dates and numbers are detected only when every value in the column agrees. An ambiguous column stays text rather than being guessed at.
Lists are not split into rows
Splitting one row into several changes what a row means, and every count computed from it.
Each of these changes what your numbers mean, so each one stays a choice you make and can see in Transform
What You Can Do With It
Connect Parquet once,
then use it four ways.
Upload Parquet and see what is in it
Your file is virus-scanned and encrypted into isolated storage before anything reads it. Every column is then graded A to F and described in plain English from its structure and statistics, never from the values inside it.
Clean and reshape Parquet data without SQL
Filter, join, group, deduplicate and repair by pointing and clicking, with quality rescored after every single step. The finished table is written to a database you choose, never stored by us.
Track it on a dashboard that rebuilds itself
Describe what you want to understand and the charts that answer it arrive already built, chosen only from columns your data can support. No metric can be invented inside a chart.
Ask it questions in plain English
Every answer carries the exact query that ran, the grade of the data behind it, and the statistical test used. Zero raw rows are sent to any AI provider.
Why You Can Trust The Answer
Know what your Parquet data is worth
before you trust a number from it.
- The moment it connects
Every column graded A to F, with no setup
Completeness counts for half the grade, uniqueness and type compliance for a quarter each. ID, key and date columns are weighted three times heavier, because everything downstream depends on them being right.
- Before anyone asks a question
Every column described in plain English
Descriptions are drafted from a column's structure and statistics, never from the values inside it. So the meaning of your data gets written down without any of your records being read to do it.
- Once your team agrees
Your wording wins, permanently
Approve a description and it is locked. No later refresh overwrites what a person on your team decided a column means, which is what stops the definitions drifting back to a machine's best guess.
Write analytics-ready Parquet data
to any destination.
Transform your Parquet data and write the results directly to any major cloud warehouse or database. Clean, governed, and ready to use - no export scripts, no manual handoffs.
Go Deeper
Parquet is the starting point.
Here is what it feeds.
How grading, descriptions and drift detection work across every source, not just Parquet.
The 25 point-and-click operations, and why quality is rescored after every single step.
Dashboards built from a description, and why no metric can be invented inside a chart.
How an answer arrives with its query, its data grade and its statistical test attached.
Everything you need to know about the Parquet Connector.
Get answers to common questions about connecting Parquet to your data stack.