Saying and doing

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Just because you can say it doesn’t mean that you can do it

Martyn Jones, New York, 25th September 2024

Narrator: There is a fascinating famous saying, “Just because you can write something, draw something, or say something, doesn’t mean that you can do it”, that I think could be further explored in the context of data and analytics. It seems to go hand in hand with expressions such as “It must be true because I read it on the internet”. Also, it can be pretty surprising how many businesses expect their people to lie where it’s practical and commercially beneficial.

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Make data silos to avoid data silos – Data Dialogues

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The best way to avoid creating data silos is to develop a plethora of data silos?

Narrator: Data Warehousing is an excellent integrator; it is the cohesive melting pot of data and the best-known way of providing multiple valid versions of the truth depending on who is looking at the data, when they are doing so, and from what perspective.

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The Data Dialogues (Nov 2024) – Physician, heal thyself!

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Physician, heal thyself!

Narrator: Consider this. If the originators, acolytes and sycophants of data mesh hadn’t been so free and easy with how they created and perpetrated technical debt, especially data model and data quality-related technical debt, then we wouldn’t need data mesh to try and get us out of the mess these sloppy developer people put us into in the first place.

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Data warehousing stands in the way of progress? (The Data Dialogues, Nov 2024)

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Data warehousing stands in the way of progress?

“Never discourage anyone who continually makes progress, no matter how slow.”

Plato

Narrator: Let us start with a softball question. The kind that even your granny could have knocked out of the park.

How does a business describe the value it gets from accessing and analysing fresh quality data to decide what is strategically, tactically and operationally preferable for the future of the industry?

It’s not a trick question, but a tricky one that is as hard to grasp and come to terms with as a mightily greasy piglet with a very questioning tail.

What do Pete and Dud think about that? Get ready kiddies. Let’s take a peek…

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The Data Dialogues (Nov 24) If in doubt, blame the data

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If in doubt, blame ‘data quality’

Narrator: It doesn’t matter what you are trying to do, or even if you know what you are trying to do, but if in doubt, blame the quality of the data. There was a time when data quality was a massive impediment to business data integration.

Data quality assurance was a glint in IT’s eye. A far-away place that nobody knew how to get to.

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The Data Dialogues (Nov 2024) – Talking Book

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Talking Book

Remember

To set the scene, get to the point, and give this thing the well-deserved impulse, impetus, and notoriety, I will begin like Dylan Thomas in Under Milk Wood—that is, at the beginning.

And for folk who struggle with big words? That’s the start.

So, to get things rolling modestly, I will explain where I am coming from with this demanding, triumphant and considered endeavour of mirth, myth and mysticism.

And, if that fails, we move on. Right? Right!

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The Data Dialogues (to be published November 2024) – Take a look inside #2


To begin at the beginning

“The data warehouse is dead. Long live the data warehouse.”

Afilonius Rex

“Ignore the hyper-nonsense about the data lakehouse, the digital doghouse, the information outhouse and the big bricking-it massive. Even if some really smartish dude tells you otherwise.”

Seneca

Heads up data, information, and knowledge people. Listen to me! If you are so of a mind.

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User Stories: Understanding Data through Laughter and Irony


Informal Introduction

Informal Introduction

US President Donald Trump and German Chancellor Angela Merkel meet in the Oval Office of the White House in Washington, DC, on March 17, 2017. / AFP PHOTO / SAUL LOEB (Photo credit should read SAUL LOEB/AFP/Getty Images)

To paraphrase Manuel Azaña,  Prime Minister of the Second Spanish Republic, “If the data punters, grifters and chancers were only allowed to talk about what they really knew about, there would be a great silence. Which would allow us data professionals to actually think about data.” 

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Data Warehousing means having thousands of ETL jobs


Data Warehousing means having thousands of ETL jobs

Narrator: Another absurdly tetric myth being pushed by a cross-section of the expansive, permissive and obtuse talking-head data-mesh massive is that data warehousing necessarily means that enterprises have to have thousands of complex, expensive and unmanageable ETL jobs in order to build, maintain and expand their data warehousing reach.

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