Why Google Internal Search for Sheets and other objects Sucks – Google Sheets Example

Google is currently going to trial about being a monopoly.

I’m not going to comment on that right now but I will say they have never worked to “mature” or “improve” their internal search tools.
I find that search on Google Drive for my google sheets and all my other Google Workspace objects … has always sucked.

Here is a really really great example I came across today but this happens all the time and its disgusting that they haven’t made this search better.

First Search:  https://docs.google.com/spreadsheets/u/0/?q=ITS3 – NOTICE – NO RESULTS.
Second Search:  https://docs.google.com/spreadsheets/u/0/?q=ITS%203 – NOTICE at least 5 results.

I mean, seriously, for 20++ years do you think Google Search for their money maker Google Ads and Search Engine Marketing has been identifying the difference between a search string with 1 space difference?
That just goes to show that after all this bullshit about “do no evil” which is complete crap because any company the size of Google is doing some evil.  Probably more evil than we even dreamed of.  Its just the law of numbers.  I don’t care what HR and Recruiting bullshit dreams up to think they are preventing evil from being done by the company employees.

This is a clear example of how most PUBLIC companies typically FOCUS only on what makes money.  What drives revenue and profits.
The fact that so many of their internal tools are so bad shows the lack of customer focus internally.

Moving Towards an Automation and AI Mindset

One of the challenges I see daily with using Chatgpt, Bard, and other AI LLM based chatbots as with AI and Automation in general is most humans do not have a mindset or a thinking paradigm in how to apply these technologies and capabilities with data.

Since I am a data guy I’m completely focusing on the data aspects of this.  I will give some simple examples here of how if you want to be more productive with Generative AI right now you must change the way you approach working with any information related tool that has data or elements of data.

Let me start with the basics of describing the current mindset related to Office documents and slides.  Many people create knowledge and share knowledge in unstructured (i guess you can say semi-structured) formats like Word, Powerpoint, Google Docs and Slides.  While there are elements of structure within these objects of knowledge, most people do not utilize them effectively.  Excel and Google Sheets can really be structured data but again most humans do not use them effectively.  One of the worst practices I see everyday (assuming you actually want to harness automation!) is how humans instead of organizing data within a structured grid format with columns and rows with Excel and Google Sheets they add in blank rows or blank columns at the beginning or the middle of structured data sets for I “guess” visualization purposes.  This inhibits automation around data set analysis and updating and really overall organization for a human.

I want to keep this article short so this will be the start of a series around …

Moving Towards an Automation and AI Mindset.



Snowflake Summit 2023 By The Numbers

Here is our Snowflake Summit 2023 By The Numbers

It is truly amazing to see how much the Snowflake Summit has changed from 2019 to 2023.  For now I’m just going to show a summary of 2023 and then below we will show the differences from 2022 to 2023.

Snowflake Summit 2023 (What data we have so far)

440 Sessions (this includes everything we see listed)
100+ Parties (let us know if you are interested in the ones that are public)
11 Tracks
179 Partners Listed

*Disclaimer:  This is NOT Official at all.  We think the data is correct but this is by our own independent tracking and NOT Related to Snowflake Corporation AT ALL.

Snowflake Summit 2023 versus 2022 – By The Numbers

Snowgrid Evolution on Snowflake

Snowgrid Evolution Background

Snowflake introduced their concept of Snowgrid back in 2019.  From our view it was their way to evolve the Snowflake Data Warehouse into the Snowflake Data Cloud.  Previously, it was very very difficult to operate between cloud provider regions.

Snowgrid was basically the backbone that connected all the cloud provider regions (from AWS, Azure, GCP) to each other.  At first it introduced somewhat cumbersome replication code that had to be mostly manually coded to replicate from region to region.  But as Snowflake usually does they improved and automated more and more of how the 

Snowgrid V1

As mentioned above, when Snowgrid and basic replication initially rolled out it was pretty cumbersome and limited.  You could only replicate entire databases and you could only write and execute manual code to do it.  Discuss how tasks were involved as well.

Snowgrid V2

Placeholder.  Discuss how it evolved to be better.

Snowgrid V3 – Now

How far Snowgrid and Snowflake Replication has come since 2019.  Now even with the GUI any Snowflake User with the appropriate rights can replicate to every region very easily.  (Just remember it ALSO comes at a cost.  See our documentation on Replication Costs.)

Further details on what Snowgrid is.