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Plus ça change, plus c’est la même chose.

Jean-Baptiste Alphonse Karr


I wrote a piece called ‘7 New Big Data Roles for 2015′. I published it on LinkedIn. Many people read it. Some people made suggestions. Others politely ignored it.

I listened to the suggestions, comment and criticisms, and revised the piece as a result.

So here, it is… I hope you like it. And if not, I might try again in six months’ time.

To begin at the beginning

I have been involved (all afternoon as a matter of fact) in an in-depth study of the changing face of IT, data architecture and data management, and the challenges that the profession faces.

In particular I have tried to focus on emerging and evolving roles and responsibilities, and in their significance, synergies and collaborative potential in a predictably high-speed, volatile and exotic future.

I know that many people will question the need to create new roles in statistical analysis, qualitative analysis, and data architecture and management. Therefore, I must admit that I also shy away from the invention of new terms, especially when they may seem to be superfluous and misleading. However, I feel that the spirit of the times is calling out for a revolution in how we view and appreciate the world of data professionals and the place of Big Data in the rich tapestry of life.

Some of the new roles detailed here may not be immediately familiar or intuitive, and some of the responsibilities may seem to be somewhat onerous or even trivial. Nevertheless, this is not accidental. As what has lead me here is the desire to formulate a coherent and cohesive response to the IT industries sea change with respect to disruptive and game-changing innovations such as Cloud data centres, the Internet of Things and Big Data.

Therefore, here is my take on what I see as being the new roles – 7+3 in all – and responsibilities within many if not all of the Next Generation Mega-Mega Data projects coming our way. The roles for discussion are:

  • Data Trader
  • Data Hound
  • Data Plumber
  • Data Butcher
  • Data Miners
  • Data Canary
  • Data Janitor
  • Data Cleaner
  • Data Pharmacist
  • Data Chef
  • Data Taster
  • Data Server
  • Data Whisperer
  • Data Czar
  • Data Shouterer

The roles, the responsibilities


Data Trader – The Data Trader is the highflying, shakin’, takin’ market maker of the wham-bam-thank-you-spam alternative-data universe. They are essentially the gears and oil of the data market, the oxygen of oxygen, the wheelers and dealers, introducing market providers of data to market consumers of data.

The Data Trader identifies potentially undervalued data, and price and quality discrepancies in alternative data sources, and then seeks to leverage these discrepancies in order to ‘monetise’ their valuable role in keeping the data market healthy. Data Traders also seek out data instruments on the instructions of a client. They may also issue and buy options and futures contracts on commoditised data, executed optionally and delivered later. Although it is technically feasible, Data Traders will rarely trade on their own account – especially if anyone of watching.

Official Endorsement: Gordon Gecko, featured above, supports The Big Data Contrarians (the professional group on LinkedIn for data, information, intellectual-capital and analytics professionals, from new recruits to chief executive officers). Gordon is on record as stating, “Before ‘The Big Data Contrarians’ came along, Big Data was all hat and no cattle! You know those hyperventilating hype guys? What schmucks! Who really needs more?” We heartily agree. So, Join The Big Data Contrarians here: https://www.linkedin.com/grp/home?gid=8338976 ß Link to group home page.

OLYMPUS DIGITAL CAMERAData Hound –Although the Data Hound is a special pedigree breed of data management role, the job of the Data Hound is essential to the work of the Data Trader.

When the Data Trader gets a new requirement for novel, fresh or new data, the job of the Data Hound is to search out the best, cheapest and most reliable sources for that data, and to identify the owners and vendors of that data.

Essentially, they assist in the data market-making responsibilities of the Data Trader.

However, there is more to the role than that. Only a Data Hound can bring infectious enthusiasm to a long saunter on the data landscape. Only a Data Hound can be such a perfect, patient distraction for the knowledge workers. Only a Data Hound can dispel all gloom, tension and work-stress with a single explosion of excitement every time you walk through the data portal.

Not for nothing shall the motto of the Data Hounds be Ad grandior data, Winalot!

Official Endorsement: Data Hound Coco, featured above, supports The Big Data Contrarians (the professional group on LinkedIn for data, information, intellectual-capital and analytics professionals, from new recruits to chief executive officers). Coco is on record as stating, “Before ‘The Big Data Contrarians’ came along, the Big Data groups on LinkedIn were kinda dog’s dinnerish, but now with one great Big Data group touching all the Big Data bases and keeping out the hype, who really needs more?” I heartily agree. So, Join The Big Data Contrarians here:https://www.linkedin.com/grp/home?gid=8338976 ß Link to group home page.

xPlumberData Plumber – The Data Plumber designs, builds and maintains the infrastructure to ensure that any validly supplied data reaches the data preparation stage prior to its selection, analysis and consumption. The Data Plumber is charged with ensuring that the required data correctly gets from the data provider to the data consumer, first time, every time.

Typical responsibilities of the Data Plumber may include:

Reading drawings and specifications to determine the layout of data supply, information repositories and knowledge systems.

Detecting faults in data plumbing appliances and systems, and correctly diagnosing their causes.

Locating and marking positions for data pipe adapters, ports and channels, and fixtures in data centre walls, ceilings and floors.

Official Endorsement: Data Plumber Sam, featured above, supports The Big Data Contrarians, and is on record as stating, “Before ‘The Big Data Contrarians’ came along, Big Data was a mere overfed bagatelle.” I heartily agree. So, Join The Big Data Contrarians here: https://www.linkedin.com/grp/home?gid=8338976 ß Link to group home page.

xButcherData Butcher – The Data Butcher works in conjunction with the Data Chef. The Data Butcher selects and prepares the desired parts of the supplied data, which they then pass on to the Data Chef for data mining, ad-hoc predictive analysis and visualisation. The Data Butcher removes the fat data from the lean data, and provides quality data that can then be subsequently ‘sliced, diced and spiced’ in downstream analytics applications.

In years from now, IT archaeologists will marvel at the Tau influences inherent in the role of the Data Butcher in particular, and data architecture and management, in general. By way of evidence, the following is a philosophical anecdote from the future:

Once a Data Butcher was preparing a piece of Big Data for a customer who had been coming to the establishment for many years.

“Pardon me, Sir” the customer asked, “But isn’t that the same ETL you used last year?”. “Why, I do believe it is” came the reply, “Why do you ask?” “Well” said the customer, “Don’t you ever need to upgrade it or maybe go for a more sophisticated and sharper solution?”

“No…” replied the kindly Data Butcher “It’s the same ETL I’ve been using for the last 17 years”. He stared wistfully into the distance for a few moments, looking for inspiration, and then continued. “And I haven’t had to upgrade it, sunset it or change it even once. For, when I select, transform and integrate raw data, I allow the trusty ETL to find its own way through it without effort or stress. Just like Bill told me. And when I come to a tricky bit with lots of disconnected, superfluous and erroneous data, I just slow down and allow the mystery to solve itself and in no time the good data comes right through the process.”

Adapted from Chuang Tzu: The Basic Writings, 1964

Official Endorsement: Data Sources close to the government are off record as stating, “Before ‘The Big Data Contrarians’ came along, everyone was all pissy about pig data, and no one really knew what it was, never mind how to do it! But now that has all changed.” Well Said, Dave!

I heartily agree with David Cameron’s sentiments on this subject.

So, Join The Big Data Contrarians here: https://www.linkedin.com/grp/home?gid=8338976 ß Link to group home page.

xMinerData Miner – Without any doubt, this is the hardest, most arduous and intense jobs in the whole collection of our new Big Data roles. The Data Miner job is in logically and physically discovering, revealing and extracting the data that is most difficult to get at. Which often involves very risky situations. The Data Miner will be the person who extracts the data that has the highest information value. They do not plough the Big Data fields, climb the Big Data peaks, nor navigate the Big Data lakes, but they do know their way around the Big Data Pit. The data that the Data Miner extracts is difficult to ignite but once it gets going will deliver concentrated and deep business value during a much longer time and at a much slower depletion rate than any other type of data. The Big Data Miner delivers the south Wales anthracite of all data, the Kuwaiti oil of all data and the strongest trade winds of all data; this is why the work of the Data Miner will always have a certain cachet in the world of data.

Official Endorsement: Dai Bando had this to say of the Data Miners: “In essence, the Data Miners are the nobility of the Big Data. But they are also the ethical side of Big Data, the human side, the diligent side, and, the big hearted side.”, “They are also the biggest contrarians in Big Data.”

I heartily agree with Dai’s hearty sentiments on this most hearty of subjects.

So, Join The Big Data Contrarians here: https://www.linkedin.com/grp/home?gid=8338976 ß Link to group home page.

xCanaryData Canary – Where would a Data Miner be without his Data Canary? The Data Canary is the arbiter of quality in the arduous and ambient world of Big Data Mining. We have all heard of the phrase “canary in the coal mine”, well the Data Canary is similar. To paraphrase Wikipedia, The “canary in the coal mine” is an allusion to caged canaries… that miners would carry underground with them. If dangerous gases such as carbon monoxide collected in the mine, it would affect the canaries well before affecting the miners, so it provided a type of early warning system.” Data Canaries are in no such mortal danger, but they still share the arduous and inhospitable corporate working environments as those experienced by the Data Miners.

Official Endorsement: The International League of Big Data Canary Workers (ILBDCW) says, “Join the Big Data Contrarians today!”

So, Join The Big Data Contrarians here: https://www.linkedin.com/grp/home?gid=8338976 ß Link to group home page.

xFarmacistData Pharmacist – The Data Pharmacist provides data remedies for data related ailments. Have you ingested more Big Data than you could manage? Have you put toxic Big Data through a viral business process? Are you suffering from a Big Data hangover? Then the Data Pharmacist will be at hand to sort things out. Data Pharmacists need strong mathematics skills to precisely prepare data medicines and explain dosing to the Big Data clients. Accuracy is critical to success in data pharmacies. Data Pharmacists need to accurately count data medicine and label data remedies correctly. Even minor errors can lead to incorrect usage. Data Pharmacists commonly multitask and deal with overwhelming activity. They continually take prescriptions from Big Data patients, fill them and consult with Big Data clients when they pick them up. Data Pharmacists need strong communication skills to interact with a variety of Big Data people in typical day. With Big Data customers, they have to listen, answer questions about prescriptions and clearly communicate proper use and side effects of Big Data medication. With data doctors, they need to listen well and make certain they get accurate Big Data prescription information. Therefore, Data Pharmacists needs good maths skills; a great attention to detail; a huge reserve of patience; and, excellent communications skills.

Join The Big Data Contrarians here: https://www.linkedin.com/grp/home?gid=8338976 ß Link to group home page.

xCaretakerData Caretaker – Also known as a Data Janitor or Data Custodian.

Data Caretakers look after installations such as data centres, clouds and data lakes. They make sure the installations and data are secure, clean and well maintained. If you like fixing things and enjoy Big Data DIY, you might consider becoming a Data Caretaker.

To become a Data Caretaker, you will need practical skills to carry out minor data centre repairs. You’ll need to be able to manage your own data caretaking workload. You’ll also need a good awareness of data governance health, data safety, data security and data hygiene issues.

Your skills and ability to do the job will often be more important than qualifications. Practical skills such as Python hacking, data scrambling and DIY data modelling would be useful. It could also be an advantage if you have relevant work experience.

Official Endorsement: The Union of Data Caretakers and Janitors (UDCJ) says, “Don’t delay! Join the Big Data Contrarians today!”

So, Join The Big Data Contrarians here: https://www.linkedin.com/grp/home?gid=8338976 ß Link to group home page.

xCleanerData Cleaner In many ways, the Data Cleaner role is a subset of the Data Janitor role. However, it is more than that. Behind the jovial nature, carefree exterior and personally disinterested motivation of the Data Cleaner lurks a surprise and a heart of gold. A thoroughly dedicated professional whose sole aim in their working life is to rid data, and the habitats in which it thrives, of toxic and viral elements that might otherwise place in peril the order of data things, unbalance the status data quo and disturb the nature of the data elements. The Data Cleaner ensures that the data is clean, respectable and fit for work.

xChefData Chef – If you’ve ever seen a great Chef working, up close and intimate (to use the west coast vernacular), then you will appreciate the need for the role of Data Chef.

First and foremost (or ‘primarily’, as Word tells me) the Data Chef is the curator of all the organisations data analytics ‘recipes’. They have the data analytics ‘knowledge’. Ideally, the Data Chef has a solid grounding in formal statistical methods and a solid appreciation of data architecture. A wide range of other skills may also augment this profile, such as an open attitude to Nouvelle analyse des données. The Data Chef also works in conjunction with the Data Trader and the Data Butcher to determine and identify prime data material in the data markets.

Based on the available prime data the Data Chef is able to determine a menu of data analytics approaches, even though these will change dynamically depending on what other accompanying data is also in season

Our resident Big Data Chef, Erik Ysbyty von Pimpollo says… “For me, The Big Data Contrarians is like the Michelin red guide to data. Indeed, what gourmet would be without that masterly tome of culinary references? So, you can join The Big Data Contrarians now, now or now”.

We agree! Thanks for the heads up, Erik! … Here we arehttps://www.linkedin.com/grp/home?gid=8338976 ß Link to group home page.

xTasterData Taster – A Data Taster is a person that takes data (or information) to be provided to a person or entity to confirm that it is safe to issue. This is perhaps one of the oldest professions in data, coming, as it does, from the ancient Roman role of praegustatoror data unini. The person or entity to whom the data is going to be issued is usually an important person or body (for example, a regulatory reporting body or an organisational strategy group) or any person or body that could possibly be placed at risk if the data (or information) is erroneous, misleading or compromised. For example, the Data Taster verifies the outcomes of Big Data Analytics and confirms that the data is plausible and that the models used are valid so that they do not permit either the accidental or the intentional introduction of data contamination. The Data Taster may also be accountable for the preparation and provision of data. The hope is that the Data Taster will be conscientious and meticulous in preventing contamination from being introduced into data, in order to safeguard their own reputation and that of their organisation.

Welsh Hollyweird wizard and Spartacus ‘clanner’ Catherine Alpha Omega Zeta Beta Jones (not featured) says… “I like data, I like Wales, I like lovely-jubbly, rolly-polly, downy-clowny, bed-clothes snuggling data… like buttered crumpets in a blanket… and Marty… so I say… Join The Big Data Contrarians, or be a right dummy, innit! Result!”. We agree! Thanks for the heads up, Cath! … Here we arehttps://www.linkedin.com/grp/home?gid=8338976 ß Link to group home page.

xServerData Server – The Data Server is a role that is closely tied to the roles of Data Whisperer and Data Czar.

At a superficial level, the Data Server presents the data menu and takes the data orders, then serves what has been ordered. The Data Server may also advise data clients on the optimal choices of data, based on the data that is available and the data preferences of other clients.

Because the role of the Data Server requires that they know a little about everything and a lot about something, the two most popular career progression paths for Data Servers are moves into the role of Data Whisperer or Data Shouterer.

The Big Data Contrarians “No Data Server left behind” – Here we arehttps://www.linkedin.com/grp/home?gid=8338976 ß Link to group home page

xWhispererData Whisperer – Is integrally associated with the roles of Data Server and Data Czar. This role is an extremely important key-stone position within an organisation.

The Data Whisperer is an explainer, a storyteller and a stand-up philosopher. The primary responsibility of the Data Whisperer is to avoid that any senior executive or regulatory body throws a ‘wobbly’ when they fail to correctly interpret the data that they are provided. Therefore, the responsibility of the Data Whisperer is to correctly socialise data analysis outcomes with the intended audiences for those outcomes, and to jointly present and explain those outcomes in plain and simple language. They are required to have courage, strength and a high degree of empathy both with the data and also with the consumers of that data.

The Big Data Contrarians “Data Whisperers are us” – Here we arehttps://www.linkedin.com/grp/home?gid=8338976 Link to group home page.

xCzarData Czar – Typically this is a senior board role, comparable to that of CFO. Indeed, the role of Data Czar (or Data Tsar, for the British) may also be held by the CFO. The role itself is that of visible figurehead of all data architecture and management activities within an organisation. Although it bears some striking resemblance with the now widely discredited role of bygone days, which I will delve into in subsequent articles, its remit goes much further. The Data Czar has the ability and the empowerment to break down barriers, cut through red tape and knock down walls that create organisational silos. They can free and easily engage with and involve senior organisation players in their data campaigns and battles, gaining commitment, trust and willing complicity along the way. Naturally, the Data Czar can also call on the skills, talents, knowledge and experience of the other 9 roles identified here.

The Big Data Contrarians “A noble cause” – Here we arehttps://www.linkedin.com/grp/home?gid=8338976 ß Link to group home page.

xShoutererData Shouterer (aka Data Shouter) – Finally, we come to the last of the roles. The Data Shouterer is primarily the role of the data evangelist, the extoller of grand data ‘truths’, the purveyor of serendipitous comfort, and the herald of a brave new data world.

When things go well the Data Shouterer is called upon to holler out the successes of data analysis from the rooftops.

When success is reluctant to come forth, they must be there to ‘big up’ the inherent potential for success, with brave tales of data buccaneering, ace information pilots and glorious exponents of the Art of Data.

The Big Data Contrarians “Shouting it from the rooftops in Finsbury Park” – Here we are https://www.linkedin.com/grp/home?gid=8338976 ß Link to group home page.

 To Conclude

There you have a brief explanation of the revised and expanded 7(+n) new Big Data roles for 2015. So, to conclude…

Necessity is the mother of invention and mother is the invention of necessity and just as the judicious use of parallel grepawk and bash could have been reinvented, rebadged and released as perhaps justifiably the next best thing in data, so too must there be concomitant and relevant roles to suit the revolutionary data spirit of the times. No?

However, to paraphrase John McEnroe, “surely this piece cannot be serious?” To which I might reply, maybe yes, or maybe no, it simply ‘depends’. But depend on what?

The English writer George Orwell once mused that “The most effective way to destroy people is to deny and obliterate their own understanding of their history”, to which I could add, “This may occur whether the act is intentional, accidental or systemic”. I think it is important that when we look at any new IT industry trend or fad, that we do so with a reasonable knowledge of IT history and the evolution of IT technology, and with a good understanding of contemporary and legacy technologies and architectures. This, to my mind, is how we respect both the IT/Information Architecture and Management profession and those whom we seek to help.

Finally, dear reader, although as I state my intention is quite serious, please do take this piece with a modicum of sodium chloride and a pinch of reality.

Please don’t forget to check out my Big Data predictions for 2015.

Also, Join The Big Data Contrarians “Simply the best Big Data group and community on LinkedIn” – Here we are https://www.linkedin.com/grp/home?gid=8338976 ß Link to group home page.

In subsequent blog pieces I will be sharing my views on the evolution of information management in general, and the incorporation novel and innovative techniques, technologies and methods into well architected mainstream information supply frameworks, for primarily strategic and tactical objectives.

As always, please reach out and share your questions, views and criticisms on this piece using the comment box below. I frequently write about strategy, organisational, leadership and information technology topics, trends and tendencies. You are more than welcome to keep up with my posts by clicking the ‘Follow’ link and perhaps you will even consider sending me a LinkedIn invite if you feel our data interests coincide. Also feel free to connect via TwitterFacebook and the Cambriano Energy website.


For more on this and other topics, check out some of my other posts:

Not banking on Big Data?https://www.linkedin.com/pulse/banking-big-data-martyn-jones?trk=prof-post

10 amazing reasons to join The Big Data Contrarians https://www.linkedin.com/pulse/10-amazing-reasons-join-big-data-contrarians-martyn-jones?trk=prof-post

Amazing Data Warehousing with Hadoop and Big Datahttps://www.linkedin.com/pulse/cloudera-kimball-dw-building-disinformation-factory-martyn-jones?trk=prof-post

The Big Data Contrarians: The Agora for Big Data dialogue https://www.linkedin.com/pulse/big-data-contrarians-agora-dialogue-martyn-jones?trk=mp-reader-card

The Big Data Shell Gamehttps://www.linkedin.com/pulse/big-data-shell-game-martyn-jones?trk=mp-reader-card

Aligning Data Warehousing and Big Datahttps://www.linkedin.com/pulse/aligning-data-warehousing-big-martyn-jones?trk=mp-reader-card

Big Data Ludditeshttps://www.linkedin.com/pulse/big-data-luddites-martyn-jones?trk=mp-reader-card

Data Warehousing Explained to Big Data Friendshttps://www.linkedin.com/pulse/data-warehousing-explained-big-friends-martyn-jones?trk=mp-reader-card

Big Data, a promised land where the Big Bucks growhttps://www.linkedin.com/pulse/big-data-promised-land-where-bucks-grow-martyn-jones-6023459994031177728?trk=mp-reader-card

The Big Data Contrarianshttps://www.linkedin.com/pulse/big-data-contrarians-martyn-jones?trk=mp-reader-card

Is big data really for you? Things to consider before diving inhttps://www.linkedin.com/pulse/big-data-really-you-things-consider-before-diving-martyn-jones?trk=mp-reader-card

Big Data Explained to My Grandchildren https://www.linkedin.com/pulse/big-data-explained-my-grandchildren-martyn-jones?trk=mp-reader-card


Many thanks to Richard Ordowich, Cari Jaquet, Claudia Pagliari.,  Error Warner,Rebecca Shomair, Rebecca Shomair, Almarie Meyer, Jennifer Christos, Joseph Adams, Terry Shen, Stephanie Vilner – Sheppard, and many others, for their valuable suggestions and support.