The Data Warrior

Changing the world, one data model at a time. How can I help you?

Archive for the tag “Data Warehouse”

To Train or Not to Train – Is That Still a Question?

For years I have been an advocate for training, of all kinds. In my recent post for DataRebels, I dicuss the pros and cons of getting trained along with reasons peopleoften give for not investing in professional training.

Sadly, for decades now, I have seen way too many people and organizations give professional training, and certification, short shrift

.Much to their detriment in the end.

This has always baffled me because I have always found value in attending training classes, workshops, seminar, technical conferences, and the like. Even if the class was not great, the contacts I made were always invaluable.I find I learn best working directly with an experienced professional who has “been there and done that”. Or, putting it another way, I like to learn from other people’s mistakes! For me nothing replaces the ability to be interactive and ask questions of a qualified instructor.

The reasons people have given me for NOT taking a training class are basic (i.e., typical):

1. It costs too much (i.e., no budget)

2. I can’t take time away from the daily job (or I can’t afford to have my team out of the office that long)

3. “It’s really not that hard – we can figure it out ourselves reading books and blogs”

Check out how I combat these attitudes by reading the rest of the post at To Train or Not to Train.

Enjoy (and get thee trained!)

Kent

The Data Warrior

It Depends (or Does It?) – Episode 13

A few weeks back, right after attending Snowflake Summit, I had the pleasure of chatting with Sanjeev Mohan on his podcast – It Depends. We spent an hour or so chatting about trends in modern data management, data mesh, data vault, my now semi-retired life as an advisor to several Snowflake partners, and my love of martial arts.

So sit back, relax (I did), and enjoy!

Aloha.

Kent

The Data Warrior

Data Vault and Data Mesh – A Match Made in the Cloud?

Check out my latest thoughts about Data Vault and Data Mesh:

Over the last six years (after I joined Snowflake basically), I have witnessed a massive increase in the interest and implementation of Data Vault 2.0. I have talked to literally hundreds of companies across the globe and across all industries about changing their approach to building an enterprise data platform. It was sort of mind boggling how many folks wanted to speak to me about this. So why, after almost two decades of successful data vault implementations, have so many people “suddenly” got interested in Data Vault?

Well, a few reasons:

1. They are moving to the cloud (in this case, Snowflake) and figured it was time to look at their approach to data warehousing and data lakes.

2. What they had been doing for decades, on critical review, really was not working (i.e., lots of expensive re-engineering all the time) and definitely could not scale.

3. Things are changing so rapidly, they needed to find a way to be more agile.

Read the rest of the post here on the Data Rebels site to find out how Data Vault relates to Data Mesh – Data Vault and Data Mesh

What do you think?

Have a great week!

Kent

The Data Warrior

Life and Times of The Data Warrior

Please join me on March 30th at 11AM CDT for my first official post-retirement talk!

I will be chatting with Mike Lampa from Great Data Minds about my career and plans post-Snowflake. I expect we will cover a wide range of topics including what community and technical evangelism is all about, as well as what made me jump from nearly 30 years in the Oracle world to a small startup with less than 100 people that claimed to have re-invented data warehousing in the cloud.

You can register here for this free event.

See you then!

Kent

The Data Warrior

Mass Data Fragmentation: Reducing ‘Data Puddles’

Shortly before leaving Snowflake last year, I was interviewed for this post about one of the worst case examples of data siloes I had seen – we called them data puddles!

A few years ago, Kent Graziano joined a big organization to work on its data. The first problem was that nobody really knew what and where all the data was. Graziano took his first three months on the job investigating data sources and targets, ultimately creating an enterprise data map to illustrate all the flows. It wasn’t pretty.

“In the end, I discovered that the same data was being sent to three or four places,” he said. In one case raw data was transformed and stored in a data warehouse, then moved from there into another warehouse—which was also pulling in the original raw data.

Graziano, who recently retired from his post as Chief Technical Evangelist at Snowflake, said this scenario is entirely common. Data scattered and copied in lakes, warehouses, data marts, SaaS platforms, spreadsheets, test systems, and more. That’s mass data fragmentation, or, more colloquially, data sprawl or data puddles. 

Indeed, 75% of organizations do not have a complete architecture in place to manage an end-to-end set of data activities including integration, access, governance, and protection, according to IDC’s State of the CDO research, December 2021. This lack of governance combines with legacy systems, shadow IT, and good intentions to pave the road to a lot of fragmentation.

Check out the rest of the post to learn how data sprawl hurts businesses and what to do about it. Read it all here!

Try not to step into any of those puddles!

Kent

The Data Warrior

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