Posts

Showing posts from January, 2018

What is the easiest way to train a neural network?

-
Image
We've been surveying our customers since forever, but recently we've started to become more and more hungry on data. As an invoicing service provider for micro entrepreneurs, Zervant's  customers are of all varieties. One interesting data snippet we've found out is that roughly half of our customers are part-time entrepreneurs. But which half is it?
Post a Comment
Read more

Prioritize your features with the Kano method

-
Image
Prioritizing new features requires intuition, but it can definitely be made better by using data. As there's always a limited amount of bandwidth to do stuff, you need to relentlessly prioritize what to do next. An easy way to fail is to be too busy doing the wrong things.
Post a Comment
Read more

Popular posts from this blog

Snowflake UPSERT operation (aka MERGE)

-
You want to insert data to a table, but if a corresponding row already exists (by some rule, e.g. unique key) you want to update that instead of adding a new row, keeping the dataset's unique requirements intact. That's an "UPDATE AND INSERT" operation, or UPSERT. Some SQL languages have native support for it.  PostgreSQL has UPSERT as native. Also MySQL supports the operation with INSERT and ON DUPLICATE KEY UPDATE. How do you do UPSERT on Snowflake? Here's how: Snowflake UPSERT i.e. MERGE operation Snowflake's UPSERT is called MERGE and it works just as conveniently. It just has a different name. Here's the simple usage: MERGE INTO workspace.destination_table d USING workspace.source_table s ON d.id = s.id AND d.val1 = s.val1 WHEN MATCHED THEN update SET d.val2 = s.val2, d.val3 = s.val3 WHEN NOT MATCHED THEN INSERT (id, val1, val2, val3) VALUES (s.id, s.val1, s.val2, s.val3); Here the destination_table and source_table are of similar form,
Read more