• Home
  • About
  • The Good Strategy Blog
  • Strategy
    • Data Warehousing
    • Ask Martyn

GOOD STRATEGY

~ for every significant challenge

GOOD STRATEGY

Tag Archives: aspiring tendencies in IM

Who’s afraid of the Big Data Contrarians? Here’s 500 reasons not to be

11 Wednesday Nov 2015

Posted by Martyn Jones in 4th generation Data Warehousing, All Data, Big Data, Business Intelligence, Cambriano, Consider this, Good Strategy, Strategy

≈ 1 Comment

Tags

All Data, Analytics, aspiring tendencies in IM, Big Data, cambriano, Martyn Jones, The Big Data Contrarians

If you enjoy this piece or find it useful then please consider joining The Big Data Contrarians:

Join The Big Data Contrarians here: https://www.linkedin.com/grp/home?gid=8338976

Many thanks.

When I first started The Big Data Contrarians group on LinkedIn I was thinking that maybe we would get 100 members within three or four months. Well, I was mistaken. Since the 1st of July, the membership ranks of The Big Data Contrarians has risen to over 500 members. However, it’s not about the quantity it’s about the quality, and The Big Data Contrarians is ‘the nicest Big Data community that you are ever likely to encoun Continue reading →

On Not Knowing Sentiment Analysis

12 Tuesday May 2015

Posted by Martyn Jones in Big Data, Big Data Analytics, Consider this, good start, goodstart, sentiment analysis

≈ Leave a comment

Tags

All Data, Analytics, aspiring tendencies in IM, awareness, good start, Good Strat, goodstart, Martyn Jones, Strategy

If you know all about Sentiment Analysis, you’ve come to the right place. Because I don’t have a clue if what I know about it is accurate or not.

I started to do a bit research into this Sentiment Analysis lark, in particular with the theoretical idea of using it to analyse and draw conclusions from comments on Pulse – assuming that this is what it can be used for.

To begin at the beginning, which is good place to start, I read the piece on Wikipedia, and this was how it began:

“Sentiment analysis (also known as opinion mining) refers to the use of natural language processing, text analysis and computational linguistics to identify and extract subjective information in source materials.

Generally speaking, sentiment analysis aims to determine the attitude of a speaker or a writer with respect to some topic or the overall contextual polarity of a document. The attitude may be his or her judgment or evaluation (see appraisal theory), affective state (that is to say, the emotional state of the author when writing), or the intended emotional communication (that is to say, the emotional effect the author wishes to have on the reader).” Source: Wikipedia Link:http://en.wikipedia.org/wiki/Sentiment_analysis

Well, that’s a fairly intuitive description. I could have almost have guessed as much.

But, back to the aim of analysing sentiment in Pulse comments, where to start and what to do.

What would sentiment analysis make of these:

On the death of an IT-business celebrity. What would sentiment analysis make of the very emotive comments of desolation, sadness and poignancy of people who didn’t personally know the departed, even remotely, or maybe didn’t even know of them until after they had ‘shuffled off life’s mortal coil’? How would that work? What would sentiment analysis make of the maudlin aphorisms, surrogate grief and bizarre sorrow of people separated by more degrees than Kofi Anan and Mork from Ork.  What additional insight does sentiment analysis tell us when these comments are analysed along with the body of the text and other comments that triggers these comments?

In a similar vein, how does sentiment analysis catch instances of sycophancy? Especially considering the fact that some of it is so ‘in your face’ and blatant that it often times seems to be a bad parody of a bad parody. “Oh, Ricky, why are you such a sexy brainbox?” How does it work in those situations?

Worse than that is the preening, gushing and obtuse texts of massive, errm… fabulators[i]. If it wasn’t about Big Data or Strategy or IT, it would be about something else, usually about the writer themselves. “I give Rafa and Rodge tips on tennis! I went to the University of the Universe and got a first! I challenged Superman to a race, and won! I have read the entire works of Dan Brown, 25 times…Neeeh!” What would sentiment analysis do with that sort of gold?

Also, what does sentiment analysis do with texts so ambiguously daft that they could mean anything? Okay, it might be able to pick up a few trigger words here or there, “rubbish”, “of”, “load”, “a”, “what”, etc. However, how does it know when “excellent” is being used in a way that means anything but excellent? For example, “Excellent Big Data job there”, with the silent “if you want a job doing properly then do it yourself”.

Finally, for the purpose of this little piece, what would sentiment analysis do with term abuse, if it could actually identify it? Going back to the use of the terms such as Big Data or Strategy, how can sentiment analysis discern between the dopey and wrong-headed use of the term, and when it is actually being used in a coherent, cohesive and consistent way, in line more or less with its formal definition? I suppose we can always write a mountain of rules to help us out:

If topic in focus of piece is strategy

And context of topic is business

And author of piece is Richard Rumelt

Then the credibility of text is good (with a certainty of 100%)

But you and try and maintain a rule base with isntances like that. It soon becomes a management nightmare.

Alternatively, maybe it could be used to analyse this text. It’ll have its work cut out, that’s for sure. Does sentiment analysis do sarcasm and cynicsm?

Anyway! I bet you might know how this sentiment analysis works, don’t you? On the other hand, if not, then it will be someone else who ‘knows’. But of course, all will not be revealed, because it’s a secret so powerful, that in the wrong hands it could be used to dominate the entire galaxy.

Only joking; and many thanks for reading.

[i]To engage in the composition of fables or stories, especially those featuring a strong element of fantasy: “a land which … had given itself up to dreaming, to fabulating, to tale-telling” (Lawrence Durrell).

lang: en_US

The World’s Best Data Quotes… Including Big Data quotes

17 Saturday Jan 2015

Posted by Martyn Jones in Analytics, Architecture, Big Data, Business Intelligence, Consider this, Data Warehousing, statistics

≈ 4 Comments

Tags

Analytics, aspiring tendencies in IM, Big Data, business intelligence, Core Statistics, enterprise data warehousing, Quotes

OLYMPUS DIGITAL CAMERA

A Random walk down Data Street

If you enjoy, abhor or are simply bored with the massive surfeit of hype surrounding Big Data, Data Warehousing and Analytics, then you might just hate these less than faithful quotes as well.

If you enjoy one or two of the quotes, well, then that’s an acceptable bonus too.

So, to begin at the beginning…xHound

Data Sources

“My data sources are unreliable, but their information is fascinating.” – Ashleigh Brilliant

“I give no data sources, because it is indifferent to me whether what data I have sourced has already been sourced before me by another.” – Ludwig Wittgenstein

“In the kitchen of a great Data Warehouse, the data source chef is a soloist.” – Fernand Point

“It is better to be hated for what data sources you have than to be loved for what data sources you do not have.” – André Gide

“In England, there are sixty different types of Data Warehouse and only one data source.” – Attributed to Voltaire

“It is a capital mistake to theorize before one has data sources. Insensibly one begins to twist facts to suit theories, instead of theories to suit facts.” – Arthur Conan Doyle, Sherlock Holmes

“From such a gentle thing, from such a source of all data, my every pain is born.” –Michelangelo

“Noise free data is a source of great strength.” – Lao Tzu

“In three words I can sum up everything I’ve learned about data: it goes on.” – Robert Frost

“Data enrichment improves a mighty fine data source” – Anonymous

xButcherBig Data

“Junk food, empty calories and carbs are the Big Data of the masses” – Karl Marx

“We live, I regret to say, in an age of Big Data hype.” – Oscar Wilde

“We are not rich by the Big Data we possess but by what Big Data we can do without.” – Immanuel Kant

“He who has Big Data hype on his side has no need of proof.” – Theodor Adorno

“The religion of Big Data sets itself the goal of fulfilling man’s unattainable desires, but for that very reason ignores her attainable needs.” – Ludwig Feuerbach

“The flesh endures the storms of the present alone; the mind in our social network interactions, those of the past and future as well as the present. Big Data is a covetousness of the mind.” – Thomas Hobbes

“Big Data is negative and dialectical, because it resolves the determinations of the understanding of things into nothings.” – Georg Wilhelm Friedrich Hegel

“I am trapped in this Big Data, and there is nothing I can do about it.” – Dudley Moore

“And remember, never take the ruby case off your iPad for a moment, or you will be at the mercy of the Big Data Witch of the West.” – The Wizard of Oz

“Imagine there’s no Big Data…” – John Lennon

Abacus3Data Transformation

“Analysis does not transform data.” – Jiddu Krishnamurtu

“I live in a data landscape, which every single day of my life is enriching data.” – Daniel Day-Lewis

“Data opportunities multiply as the data is transformed” – Sun Tzu

“He who integrates data badly is lost.” – Theodor Adorno

“Today we transform the data; tomorrow, the whole enchilada” – Leon Trotsky

“Well, it’s all about the ETL law of the transformation of data quantity into data quality, and vice versa. Innit!” – Friedrich Engels

“The management consultants have only interpreted the business data, in various ways. The point, however, is to transform it.” – Karl Marx

“Hey! What’s going down here in the Hollyweird of data?” – Joe McCarthy

“The Big Data alchemists in their transformational search for gold discovered much data of greater value.” – Arthur Schopenhauer

“That Schopenhauer yolk was a bit of an old Big Data ‘procurer’ wasn’t he now Rodge?” – Pádraig Judas O’Leprosy

IMGQBusiness Intelligence

“The trouble with the world is that the cocksure have Big Data and that Data Science and Business Intelligence are all sexed up.” – Bertrand Russell

If people never did silly things no Business Intelligence would ever get done.” – Ludwig Wittgenstein

“The best Business Intelligence user is intelligent, well-educated and a little drunk.” –Alben W Barkley

“The Master said, “If your conduct is determined solely by considerations of Business Intelligence and profit you will arouse great resentment.” ― Confucius

“That’s cricket, Harry, you get these sort of things in Business Intelligence” – Frank Bruno

“Business Intelligence without ambition is a bird without wings.” – Salvador Dali

“I would prefer a Business Intelligence hell to a Big Data paradise.” – Blaise Pascal

“Many much-learned business men have no Business Intelligence.” – Democritus

“We should not only use the brains we have, but all that we can borrow.” – Woodrow Wilson

“The reason we have Business Intelligence is so we don’t have to think all the time” –Homer Simpson

P3160034Data Warehousing

“The study of Data Warehousing, like the Nile, begins in Inmon and ends in magnificence.” – Charles Caleb Colton

“Big Data wins games, but Data Warehousing wins championships.” – Michael Jordan

“Big Data is no substitute for Data Warehousing.” – Frank Herbert

“It’s in me blood, Clive, without Data Warehousing I’d be nothing,” – Alan Latchley

“The trouble with the world is that the cocksure have Big Data and that Data Science is all sexed up.” – Bertrand Russell

If people never did silly things no Business Intelligence would ever get done.” – Ludwig Wittgenstein

“The best Business Intelligence user is intelligent, well-educated and a little drunk.” –Alben W Barkley

“You can catch all the whales in the ocean and stack them together and they still do not make a minnow.” – Ralph Wiggum

“Well, the smarter I practice Inmon Data Warehousing, the luckier I get.” – Gary Player

“Well, I’ve cleaned up facts and dimensions in a star-schema ‘data warehouse’. That was pretty terrible. But I can’t complain because I’m sure other people have done worse.” – Cee Lo Green

“You can give a person a bowl of Big Data Gruel and feed them for a day, or teach them Inmon Data Warehousing and feed them for a lifetime.” – Proverb

“A Data Warehouse is like a tea bag; you never know how strong it is until you are in hot water.” – Eleanor Roosevelt

” οἶδα δ᾽ ἐγὼ ψάμμου τ᾽ ἀριθμὸν καὶ μέτρα θαλάσσης, καὶ κωφοῦ συνίημι, καὶ οὐ φωνεῦντος ἀκούω. ὀδμή μ᾽ ἐς φρένας ἦλθε κραταιρίνοιο χελώνης ἑψομένης ἐν χαλκῷ ἅμ᾽ ἀρνείοισι κρέεσσιν, ᾗ χαλκὸς μὲν ὑπέστρωται, χαλκὸν δ᾽ ἐπιέσται.” – An Oracle to Croesus of Lydia

IMGThat’s all folks!

Well, now that that’s done I can always ask for forgiveness. Not that I will of course.

 Many thanks for reading.

abfab111

Martyn Jones

Founder and CEO, Cambriano Energy


File under: Good Strat, Good Strategy, Martyn Richard Jones, Martyn Jones, Cambriano Energy, Iniciativa Consulting, Iniciativa para Data Warehouse, Tiki Taka Pro

Continue reading →

Marty does… Big Data and the Vs

09 Tuesday Dec 2014

Posted by Martyn Jones in Big Data, Marty does

≈ 12 Comments

Tags

Analytics, aspiring tendencies in IM, Behavioural Economics, Big Data, Challenges, Vs

Clive: Yeah, well, you had to, didn’t you? You had to stand up for what you stood for, didn’t you? I mean, the only time I remember a similar occasion was, I was in, errm… I was at Spurs, Tottenham Hotspurs.

Derek: Yeah.

Clive: I was watching a game against Arsenal, and this bloke come up to me and said, “Hello”.

Derek: Oh no…

Derek and Clive – This Bloke Came Up to Me Continue reading →

The management and architecture of Information Assets: Ask Martyn!

15 Saturday Nov 2014

Posted by Martyn Jones in Ask Martyn, Data governance, information

≈ Leave a comment

Tags

aspiring tendencies in IM, Behavioural Economics, information management

The management and architecture of Information Assets

For more than two decades I have tried to convey the importance of treating information and knowledge as potential assets.

Around the world, the response has usually been mixed.

It is understandable that there is frequent reluctance to accept that information might have real value. Continue reading →

Aspiring Tendencies in IM: Strength and Innocence

03 Monday Nov 2014

Posted by Martyn Jones in accountability, Ask Martyn, Best principles, deceit, pain

≈ Leave a comment

Tags

accountability, aspiring tendencies in IM, ethics, good job, information management, Information Technology, IT business, Organisational Autism, organisational awareness, professionalism

“Anger is the enemy of nonviolence and pride is a monster that swallows it up.”

Mohandas Gandhi

Aspirational trends

The predominance of strength and innocence, better known as ignorance and arrogance, is undermining Information Management, and in turn is ensuring that many Data Warehousing and Decision Support initiatives are disappointments.

2015 will again give IM professionals the opportunity to regain some dignity and professional integrity.

First, by recognizing that there are grave problems within IM; then slowing down and halting the toxic trends, carelessness and bad practices; and then in subsequently, reversing, through intelligence, perseverance and integrity, the ingenuous and decrepit habits that still trouble the profession.

Present indications

In the rush to the bottom we throw excellence in analysis, architecture, engineering and business understanding, under the bus. In IM as well as in many other branches of IT (Information Technology), mediocrity has become the new excellent, regular the new exceptional, and shoddiness the new normal.

Whether it is in Data Warehousing, Big Data, Business Intelligence, Analytics, Decision Support or Data Integration, we see that professional integrity and ethical behaviour – already enough of a rarity in IT – is being repeatedly trumped by short-term expediency, wilful witlessness, and the cultivation and perpetuation of dogmas, dysfunctional behaviour and dubious doings.

The Information Management sector is rife with elaborate charlatanry, partisan expediency and wilful self-deception. There is not a day that goes by in which we are not submitted to an avalanche of contemptible claims from rogue IM evangelists, DW neophytes and unsophisticated opportunists, who chose to simply make things up as they go along.

Manifest requisites

It is in the best interests of IM to raise the profession out of the ditch; to reform the profession from the inside; to drive sea-change improvements in knowledge, quality and professional integrity; to ensure a drastic reduction in destructive hype, deception and dogma, and, to show the artless charlatans, chancers and snake-oil merchants the door.

Data Warehousing and Decision Support – if done right, and for the right reasons – can deliver tangible benefits to many organisations. Simply stated, if business information has a value in the realm of business and strategy then it should be treated as an asset, if it is an asset then it should be managed and nurtured as such, which means aiming to do the right thing right, first time, every time, whilst focusing on maximising confidence, availability and agility.


File under: Good Strat, Good Strategy, Martyn Richard Jones, Martyn Jones, Cambriano Energy, Iniciativa Consulting, Iniciativa para Data Warehouse, Tiki Taka Pro

Follow GOOD STRATEGY on WordPress.com

Top posts

  • Myth-busting: Data Mesh and Data Warehousing - Revisited
  • Why I called bullshit on the data lakehouse nonsense
  • Data warehousing explained to big-data, data-lake & data-lakehouse folk
  • Agile at Scale is bullshit by design
  • Agile@Scale is Corporate Terrorism - Discuss
  • Data Warehousing means having thousands of ETL jobs
  • The data warehouse is the repository for the post-transactional data
  • UK Government? Global Charlies!
  • USA: What Trumped Hillary?
  • Does your way of providing data have business value?

Enter your email address to follow this blog and receive notifications of new posts by email.

Join 2,439 other subscribers

Names in the cloud

4th generation Data Warehousing All Data Ask Martyn Big Data Big Data 7s Big Data Analytics Business Intelligence business strategy Consider this dark data data architecture Data governance Data Lake data management data science Data Supply Framework Data Warehouse Data Warehousing Good Strat goodstrat Good Strategy IT strategy Martyn does Martyn Jones Martyn Richard Jones pig data Politics Strategy The Amazing Big Data Challenge The Big Data Contrarians

The Good Strat Archives

  • March 2023
  • January 2022
  • December 2021
  • November 2021
  • June 2020
  • May 2020
  • April 2020
  • March 2020
  • July 2019
  • June 2019
  • May 2019
  • December 2018
  • January 2018
  • December 2017
  • October 2017
  • August 2017
  • July 2017
  • June 2017
  • May 2017
  • April 2017
  • March 2017
  • February 2017
  • January 2017
  • December 2016
  • September 2016
  • August 2016
  • May 2016
  • March 2016
  • February 2016
  • January 2016
  • December 2015
  • November 2015
  • August 2015
  • July 2015
  • June 2015
  • May 2015
  • April 2015
  • March 2015
  • February 2015
  • January 2015
  • December 2014
  • November 2014
  • October 2014
  • September 2014

The Stats

  • 99,678 hits

Recent posts

  • You don’t need a data warehouse to do data warehousing March 22, 2023
  • Data Warehousing means having thousands of ETL jobs March 21, 2023
  • The data warehouse is the repository for the post-transactional data March 20, 2023
  • Does your way of providing data have business value? March 19, 2023
  • Data warehousing stands in the way of progress March 18, 2023
  • Data Trailblazers: 2022 Vision January 2, 2022
  • Tea with The Data Contrarian: Afilonius Rex December 10, 2021
  • Reality Check: Data Mesh and Data Warehousing   December 5, 2021
  • Myth-busting: Data Mesh and Data Warehousing – Revisited November 25, 2021
  • Heaven help us! Have you seen the latest Virtual Data Warehouse bullshit? June 26, 2020

Hours & Info

Martyn Richard Jones
Madrid, Spain
+33 767 120 160
10:00 - 17:00
Follow GOOD STRATEGY on WordPress.com

Follow me on Twitter

My Tweets

Top Good Strat Posts & Pages

  • The Good Strategy Company
  • Myth-busting: Data Mesh and Data Warehousing - Revisited
  • Why I called bullshit on the data lakehouse nonsense
  • Data warehousing explained to big-data, data-lake & data-lakehouse folk
  • Agile at Scale is bullshit by design
  • Agile@Scale is Corporate Terrorism - Discuss
  • Data Warehousing means having thousands of ETL jobs
  • The data warehouse is the repository for the post-transactional data
  • UK Government? Global Charlies!
  • USA: What Trumped Hillary?

Good strat tag cloud

accountability advertising All Data Analytics aspiring tendencies in IM awareness Banking Behavioural Economics BI Big Data Bill Inmon Brexit BS Business business analysis Business Enablement business intelligence Business Management business strategy Challenges Commercial IT Consider this corporate assets Corporate IT Creativity data data analytics data architecture data integration data management Data Marts data science Data Warehouse Demagogism Dogma DW 3.0 Economics enterprise data warehousing EU Financial Goal Setting goodstart good start Good Strat goodstrat Good Strategy hadoop Information and Technology information management Information Technology IT business IT Strategy knowledge management leadership marketforces Marketing Martyn Jones Martyn Richard Jones MDM Offshoring operationalwareness Organisational Autism organisational awareness Outsourcing Pimps Politics project management Requirements management Risk Risk Management statistics Strategy trading traditional assets UK

Categories

  • 4th generation Data Warehousing
  • accountability
  • advertising
  • agile
  • agile way of working
  • agile@scale
  • AI
  • All Data
  • Analytics
  • anthropology
  • Architecture
  • Artificial Intelligence
  • Ask Martyn
  • Assets
  • awareness
  • bad strategy
  • Banking
  • behaviour
  • Best principles
  • Big Data
  • Big Data 7s
  • Big Data Analytics
  • blockchain
  • Books with influence
  • Brexit
  • BS
  • business
  • Business Intelligence
  • business strategy
  • Cambriano
  • Cambridge Analytica
  • China
  • Climate Change
  • Cloud
  • code of conduct
  • Commercial Analytics
  • community
  • Condiser this
  • Conservative Party
  • consider
  • Consider this
  • Consultation
  • Creativity
  • dark data
  • data
  • data architecture
  • Data governance
  • data hub
  • Data Lake
  • data management
  • Data Mart
  • data mesh
  • data science
  • Data Supply Framework
  • Data Warehouse
  • Data Warehousing
  • deceit
  • deep learning
  • Democracy
  • digital transformation
  • Diplomacy
  • disinformation
  • Dogma
  • Duties
  • DW 3.0
  • ECM
  • Economics
  • EDW
  • England
  • enterprise content management
  • ethics
  • EU
  • Europe
  • European Union
  • Excellence
  • Excerpt
  • Executive
  • Extract
  • Federalism
  • Financial Industry
  • fraud
  • Freedoms
  • Globalisation
  • good start
  • Good Strat
  • Good Strategy
  • Good Strategy Radio
  • goodstart
  • goodstartegy
  • goodstrat
  • goostart
  • governance
  • hadoop
  • hdfs
  • HR
  • humour
  • India
  • influencers
  • informatio Supply Framework
  • information
  • Information Management
  • Information Supply Frameowrk
  • Information Supply Framework
  • Infotrends
  • Inmon
  • instruments
  • IoT
  • IT Circus
  • IT fraud
  • IT strategy
  • IT World
  • iterations
  • java
  • Knowledge
  • knowledge management
  • Labour Party
  • leadership
  • Leadership 7s
  • life
  • listening
  • literature
  • LSE
  • machine learning
  • Management
  • market forces
  • Marketing
  • Marty does
  • Martyn does
  • Martyn Jones
  • Martyn Richard Jones
  • media
  • Memory lane
  • Methodology
  • nationalism
  • nine competitive forces
  • no limits
  • Northern Ireland
  • obituary
  • Obligations
  • offshore
  • Offshoring
  • operational
  • Outsourcing
  • Oxford
  • pain
  • Parliament
  • Peeves
  • Personal Integrity Key
  • Philosophy
  • pig data
  • PIK
  • PIR
  • Plaid Cymru
  • Planning
  • poem
  • poems
  • Poetry
  • Polemic
  • political science
  • Politics
  • pomo
  • postmodern
  • POTUS
  • Process
  • Professional Networking
  • professionalism
  • project management
  • Project to Excel
  • prose
  • public
  • Public Integrity Record
  • Quiz
  • Rant
  • Referendum
  • Remain
  • RIghts
  • Risk
  • Rivalry
  • Russia
  • Ruth Davidson
  • Sales
  • satire
  • Scotland
  • Scottish National Party
  • scrum
  • sentiment analysis
  • SMILES
  • Snippet
  • SNP
  • Social
  • Social Media
  • Sociology
  • spoof
  • statistics
  • Stories
  • Strategy
  • structured intellectual capital
  • supply chain management
  • tactics
  • Tax avoidance
  • Tax evasion
  • TEAM
  • technology
  • The Amazing Big Data Challenge
  • The Big Data Contrarians
  • The Greens
  • The Guardian
  • The hidden wealth of nations
  • Trade
  • UK
  • Uncategorized
  • United Kingdom
  • USA
  • Value
  • Wales
  • wisdom

Blog at WordPress.com.

  • Follow Following
    • GOOD STRATEGY
    • Join 131 other followers
    • Already have a WordPress.com account? Log in now.
    • GOOD STRATEGY
    • Customize
    • Follow Following
    • Sign up
    • Log in
    • Report this content
    • View site in Reader
    • Manage subscriptions
    • Collapse this bar
 

Loading Comments...
 

    Privacy & Cookies: This site uses cookies. By continuing to use this website, you agree to their use.
    To find out more, including how to control cookies, see here: Cookie Policy