Tag Archives: Data Warehouse

Understanding Exhaust Data in Data Warehousing

02 Wed Oct 2024

Posted by in Inform, educate and entertain.

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The data warehouse is the place to copy exhaust data to

Martyn Jones, Bilbao, 2nd October 2024

Narrator: Not all data we have is related to strictly business domains such as products, organisation structure and corporate real estate. A lot of data we collect is simply about monitoring all aspects of IT, applications, networking, security and governance. To name just a few.

Dud: What’s all this data in my exhaust? Is my data back-end going well, or do I have a mechanical data governance issue? All this OLTP exhaust data is so tedious and tiring.

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Orientation! Domain or Subject?

26 Thu Sep 2024

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Domain orientation or subject orientation?

Martyn Jones, New Jersey

Narrator: Here, in this piece, we wander down Differential Avenue to look at what people consider domain and subject orientation. This story is about the good, the embarrassingly lousy hyperbole and then the ugliest provocative nonsense.

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Consider this: Big Data Inertia

22 Tue Mar 2016

Posted by in All Data, Big Data, Big Data 7s, Big Data Analytics, dark data, data architecture, Data governance, Data Lake, data management, data science, Data Supply Framework, Data Warehouse, Data Warehousing, Inform, educate and entertain., pig data, The Amazing Big Data Challenge, The Big Data Contrarians

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“Half the time she did things not simply, not for themselves; but to make people think this or that; perfect idiocy she knew for no one was ever for a second taken in.”  Virginia Woolf, Mrs. Dalloway

It’s all very well for the blithering Big Data bullshitter savants to now claim, after a massive exercise in u-turning, that Big Data isn’t after all about data volumes, velocities and varieties, but about some minor variation on the theme of data architecture, management and processing.

But, look at the mess! Continue reading →

Too Much Information

16 Wed Mar 2016

Posted by in All Data, Ask Martyn, Big Data, Big Data 7s, Big Data Analytics, business strategy, dark data, Data governance, Data Lake, data management, data science, Data Supply Framework, Data Warehouse, Data Warehousing, Good Strat, Good Strategy, goodstrat, Inform, educate and entertain., IT strategy, Marty does, Martyn does, Martyn Jones, Martyn Richard Jones, pig data, Strategy, The Amazing Big Data Challenge, The Big Data Contrarians

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Martyn Richard Jones

I have questions about data.

Most of us who have more than a cursory knowledge of the English language have heard of the phrase ‘too much information’. We know what it means, even if we don’t always know when to apply it.

For those who don’t know, or are unsure, the Urban Dictionary describes ‘too much information’ as “An expression of exasperation and disgust when a person is divulging personal details of his sex life, toilet habits, or anything the listener finds disgusting, uninteresting, and unwelcome.”[1]

Sum, sum. Just because we know it, doesn’t mean we should share it or even try and remember it, never mind go about analysing the hell out of it.

This is where Big Data comes in. Continue reading →

Big Data 7s: Talking Points #1

09 Fri Jan 2015

Posted by in Big Data, Big Data 7s, Consider this, Data Warehouse

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Martyn Richard JonesJPR-Williams_181887k

To begin at the beginning

This is the first in a series of collections of talking points on the processing of extensive data sets by non-relational or pseudo-relational means, speculative data analytics with these large data sets which is typically non-operational data and social media data obtained from internet sources, and how usable outcomes, if any, are derived, can be integrated into strategic, tactical and operational decision support. Continue reading →

The Sources of Truth: Rarely Pure, Never Simple – 2026 Mix

19 Fri Dec 2014

Posted by in Data Warehouse, Data Warehousing, EDW

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Martyn Richard Jones

Remastered for 2026

Here We Go With the Truth

1.       To begin at the beginning

“A thing is not necessarily true because a man dies for it.”

Oscar Wilde

For well over two decades one of the most talked about benefits of Enterprise Data Warehousing (EDW) has been that it gives us a single source of business truth. Continue reading →

Consider this: Did Big Data Kill The Statistician? 2026

03 Wed Dec 2014

Posted by in consider, Consider this, data science, Polemic, statistics

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OLYMPUS DIGITAL CAMERA
Blue sky data

Martyn Rhisiart Jones

Hold this thought: ‘There are big lies, damn big lies and big data science’.

Statistics is a science. Some argue that it is the oldest of sciences. It can be traced back in history to the days of Augustus Caesar, and before.

In 1998, Lynn Billard wrote a paper that laid out the role of the Statistician and Statistics. She stated that “no science began until man mastered the concepts and arts of counting, measuring, and weighting”.[1]

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Consider this: Data Warehousing Without Tears – 2026 Mix

30 Sun Nov 2014

Posted by in Consider this, Data Warehouse, Data Warehousing

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 Old advice is still good advice, if it is truly good advice.

Martyn Richard Jones

It’s an older piece (from the nineties), but a lot of it is still relevant and pertinent.

So, here is a brief run-down on how to avoid crashing and burning Data Warehousing.

Understand that a Data Warehouse should only contain subject oriented, integrated, non-volatile and time-variant information to support strategic and tactical requirements of management – Keeping the purpose of the Data Warehouse highly focused will eliminate the dilution of a Data Warehouse solutions effectiveness. If what Bill Inmon said in this respect almost invariably results in successful DW projects – and that’s not speculation but proven fact – then I don’t see any rational reason at the moment to change our views on this. Continue reading →

Consider this: Ten thoughts on Data Warehousing – 2026 Mix

30 Sun Nov 2014

Posted by in Ask Martyn, Consider this, Data Warehouse, Data Warehousing

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©1997 Adobe Systems Incorporated
Dreamers

Martyn Richard Jones

More than 80% of advertising is ignored. More than 50% of Data Warehouse projects fail in one way or another. The information explosion has been accompanied by a massive increase in the ranks of the willfully stupid. Continue reading →