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

GOOD STRATEGY

~ for every significant challenge

GOOD STRATEGY

Category Archives: DW 3.0

A data superhero is something to be

02 Wednesday Mar 2016

Posted by Martyn Jones in 4th generation Data Warehousing, Consider this, Data Supply Framework, Data Warehouse, Data Warehousing, DW 3.0, EDW, Excellence, Good Strat, Good Strategy, Information Management, Information Supply Frameowrk, Knowledge, leadership, Methodology, Professional Networking, The Big Data Contrarians

≈ Leave a comment

SuperHeroA data warehousing superhero is something to be

Not all that glitters is Big Data, and Big Data has a long way to go before it can deliver anything like the same satisfying results, tangible benefits and organisational agility that a properly implemented Inmon Enterprise Data Warehouse can provide.

Therefore, I have a question for you.

Continue reading →

In the beginning was the Big Data Plan

23 Tuesday Feb 2016

Posted by Martyn Jones in 4th generation Data Warehousing, Big Data, Big Data 7s, Big Data Analytics, Data governance, Data Lake, data science, Data Warehouse, Dogma, DW 3.0, Information Management, Information Supply Frameowrk, Infotrends, Inmon, sentiment analysis

≈ Leave a comment

Lucas_Cranach_d._Ä._035

In the beginning was the Big Iron, the Big Data, and the Big Data Plan.

And then came the Big Data Assumptions.

And the Big Data Assumptions were without form.

And the Big Data Plan was without substance.

And the Big Iron was without movement.

And the Big Data was without velocity, variety and volume.

And darkness was upon the face of the data workers.

And they spoke amongst themselves, saying: “Big Data, is a crock of shit, and it stinketh mucho”.

And the data workers went unto their Data Supervisors and said: “This here Big Data is a pile of putrid crappy keech”, for they were from Govan, and continued, “and none may abide the odour thereof”.

And the Data Supervisors went unto their Information Managers, saying: “Big Data is a container of excrement, and it is very strong, such that none may abide by it.”

And the Information Managers went unto their Business Directors, saying: “This here Big Data doodoo is a vessel of fertilizer, and none may abide its strength.”

And the Business Directors spoke amongst themselves, saying to one another: “Big Data contains that which aids plant growth, and it is very powerful.”

And the Vice Presidents went unto the President, saying unto him: “This new Big Data will actively promote the growth and vigour of the company, with powerful effects.”

And the President looked upon the Big Iron, the Big Data and the Big Data Plan, and saw that they were good.

Many thanks for reading

Join The Big Data Contrarians

The Big Data Contrarians

All Data: It’s about statistics

30 Friday Jan 2015

Posted by Martyn Jones in All Data, Consider this, DW 3.0, Good Strat, Good Strategy, Information Supply Frameowrk, Martyn Jones, Martyn Richard Jones, statistics

≈ Leave a comment

Tags

All Data, Big Data, business intelligence, Good Strat, Good Strategy, Martyn Jones, Martyn Richard Jones, statistics

LinkedInHeader1

A big computer, a complex algorithm and a long time does not equal science.

Robert Gentleman

To begin at the beginning

Fueled by the new fashions on the block, principally Big Data, the Internet of Things, and to a lesser extent Cloud computing, there’s a debate quietly taking please over what statistics is and is not, and where it fits in the whole new brave world of data architecture and management. For this piece I would like to put aspects of this discussion into context, by asking what ‘Core Statistics’ means in the context of the DW 3.0 Information Supply Framework.

Core Statistics on the DW 3.0 Landscape

The following diagram illustrates the overall DW 3.0 framework:

There are three main concepts in this diagram: Data Sources; Core Data Warehousing; and, Core Statistics.

Data Sources: All current sources, varieties, velocities and volumes of data available.

Core Data Warehousing: All required content, including data, information and outcomes derived from statistical analysis.

Core Statistics: This is the body of statistical competence, and the data used by that competence. A key data component of Core Statistics is the Analytics Data Store, which is designed to support the requirements of statisticians.

The focus of this piece is on Core Statistics. It briefly looks at the aspect of demand driven data provisioning for statistical analysis and what ‘statistics’ means in the context of the DW 3.0 framework.

Demand Driven Data Provisioning

The DW 3.0 Information Supply Framework isn’t primarily about statistics it’s about data supply. However, the provision of adequate, appropriate and timely demand-driven data to statisticians for statistical analysis is very much an integral part of the DW 3.0 philosophy, framework and architecture.

Within DW 3.0 there are a number of key activities and artifacts that support the effective functioning of all associated processes. Here are some examples:

All Data Investigation: An activity centre that carries out research into potential new sources of data and analyses the effectiveness of existing sources of data and its usage. It is also responsible for identifying markets for data owned by the organization.

All Data Brokerage: An activity that focuses on all aspects of matching data demand to data supply, including negotiating supply, service levels and quality agreements with data suppliers and data users. It also deals with contractual and technical arrangements to supply data to corporate subsidiaries and external data customers.

All Data Quality: Much of the requirements for clean and useable data, regardless of data volumes, variety and velocity, have been addressed by methods, tools and techniques developed over the last four decades. Data migration, data conversion, data integration, and data warehousing have all brought about advances in the field of data quality. The All Data Quality function focuses on providing quality in all aspects of information supply, including data quality, data suitability, quality and appropriateness of data structures, and data use.

All Data Catalogue: The creation and maintenance of a catalogue of internal and external sources of data, its provenance, quality, format, etc. It is compiled based on explicit demand and implicit anticipation of demand, and is the result of an active scanning of the ‘data markets’, ‘potential new sources’ of data and existing and emerging data suppliers.

All Data Inventory: This is a subset of the All Data Catalogue. It identifies, describes and quantifies the data in terms of a full range of metadata elements, including provenance, quality, and transformation rules. It encompasses business, management and technical metadata; usage data; and, qualitative and quantitative contribution data.

Of course there are many more activities and artifacts involved in the overall DW 3.0 framework.

Yes, but is it all statistics?

Statistics, it is said, is the study of the collection, organization, analysis, interpretation and presentation of data. It deals with all aspects of data, including the planning of data collection in terms of the design of surveys and experiments; learning from data, and of measuring, controlling, and communicating uncertainty; and it provides the navigation essential for controlling the course of scientific and societal advances[i]. It is also about applying statistical thinking and methods to a wide variety of scientific, social, and business endeavors in such areas as astronomy, biology, education, economics, engineering, genetics, marketing, medicine, psychology, public health, sports, among many.

Core Statistics supports micro and macro oriented statistical data, and metadata for syntactical projection (representation-orientation); semantic projection (content-orientation); and, pragmatic projection (purpose-orientation).

The Core Statistics approach provides a full range of data artifacts, logistics and controls to meet an ever growing and varied demand for data to support the statistician, including the areas of data mining and predictive analytics. Moreover, and this is going to be tough for some people to accept, the focus of Core Statistics is on professional statistical analysis of all relevant data of all varieties, volumes and velocities, and not, for example, on the fanciful and unsubstantiated data requirements of amateur ‘analysts’ and ‘scientists’ dedicated to finding causation free correlations and interesting shapes in clouds.

That’s all folks

This has been a brief look at the role of DW 3.0 in supplying data to statisticians.

One key aspect of the Core Statistics element of the DW 3.0 framework is that it renders irrelevant the hyperbolic claims that statisticians are not equipped to deal with data variety, volumes and velocity.

Even with the advent of Big Data alchemy is still alchemy, and data analysis is still about statistics.

If you have any questions about this aspect of the framework then please feel free to contact me, or to leave a comment below.

Many thanks for reading.

Catalogue under: #bigdata #technology

[i] Davidian, M. and Louis, T. A., 10.1126/science.1218685


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
  • The World's Best Data Quotes... Including Big Data quotes
  • Why I called bullshit on the data lakehouse nonsense
  • Reality Check: Data Mesh and Data Warehousing  
  • USA: What Trumped Hillary?
  • Data warehousing explained to big-data, data-lake & data-lakehouse folk
  • DATA! STRATEGY, INNOVATION AND VALUE BULLSHIT
  • Data Trailblazers: 2022 Vision
  • Extracts: And, what would the Ladies and Gentlemen like?
  • 7 New Big Data Roles for 2015

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

Join 2,336 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

  • 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

  • 98,867 hits

Recent posts

  • 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
  • DATA! STRATEGY, INNOVATION AND VALUE BULLSHIT June 9, 2020
  • Big data’s unvirtuous circus and twelve v-words May 17, 2020
  • Laughing at Big Data – What’s on the inside May 16, 2020
  • Why I called bullshit on the data lakehouse nonsense May 16, 2020
  • Laugh at Big Data – download my ebook for free on 17th May. May 16, 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
  • The World's Best Data Quotes... Including Big Data quotes
  • Why I called bullshit on the data lakehouse nonsense
  • Reality Check: Data Mesh and Data Warehousing  
  • USA: What Trumped Hillary?
  • Data warehousing explained to big-data, data-lake & data-lakehouse folk
  • DATA! STRATEGY, INNOVATION AND VALUE BULLSHIT
  • Data Trailblazers: 2022 Vision
  • About

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 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