Martyn Richard Jones

This article is in English.

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

Jean-Baptiste Alphonse Karr

To Begin at the Beginning

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

In particular, I have focused on emerging and evolving roles and responsibilities. I have examined their significance and synergies. Additionally, I considered their collaborative potential in a future marked by high-speed, volatile, and unpredictable conditions.

Many people will question the need to create new roles in statistical analysis, qualitative analysis, and data architecture and management. I must admit that I also shy away from inventing new terms, especially when they may seem superfluous and misleading. However, I feel that the spirit of the times calls for a revolution. It is time to change how we view and appreciate the world of data professionals.

Some of the new roles detailed here may not be immediately familiar or intuitive, and some of the responsibilities may seem either onerous or trivial. But this is not accidental. What has led me here is the desire to formulate a coherent and cohesive response to the IT industry’s sea change with respect to disruptive and game-changing innovations, such as Cloud data centres, the Internet of Things, and Big Data.

Here is my take on what I see as the new roles and responsibilities within many, if not all, of the Next Generation Mega-Mega Data projects coming our way. The roles that will be discussed here are as follows:

• Data Trader
• Data Hound
• Data Plumber
• Data Butcher
• Data Chef
• Data Taster
• Data Server
• Data Whisperer
• Data Czar
• Data Shouterer

The roles, the responsibilities

Data Trader – The Data Trader is the high-flying market maker of the alternative data universe. They are essentially the gears and oil of the data market, 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 to ‘monetise’ their valuable role in keeping the data market healthy. Data Traders also seek out data instruments at the client’s instruction. They may also issue and buy options and futures contracts on commoditised data, to be optionally executed and delivered at a later date. Although it is technically feasible, Data Traders will rarely trade on their own account.

Data Hound – Although the Data Hound is a specialised breed of data management role, the job of the Data Hound is essential to the work of the Data Trader.

When the Data Trader receives a new requirement for novel, fresh, or new data, the Data Hound is tasked with identifying the best, cheapest, and most reliable sources for that data, as well as the owners and vendors of that data. Essentially, they assist in the data market-making responsibilities of the Data Trader. But there is more to the role than that. Only a Data Hound can bring infectious enthusiasm to a long walk on the data landscape. Only a Data Hound can be such a perfect, patient distraction for the knowledge workers. And 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!

Data 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 responsible for ensuring that the required data is transmitted from the data provider to the data consumer, the 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.

Data 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 to come, 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:

There was once a Data Butcher who was preparing a piece of Big Data for a customer who had been coming for many years.

“Pardon me, Sir”, the customer asked, “But isn’t that the same ETL you used last year? 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. 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

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

First and foremost, the Data Chef is the curator of all the organisation’s data analytics ‘recipes’. They have the data analytics ‘knowledge’. Ideally, the Data Chef has a solid foundation in formal statistical methods and a thorough understanding of data architecture. This may also be augmented by a wide range of other skills, such as in 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 availability of prime data, the Data Chef can evaluate a menu of data analysis approaches that dynamically change depending on the data in season and available on the data market.

Data Taster – A Data Taster is a person who verifies that data (or information) is accurate and suitable for a person or entity to confirm that it is safe to issue. This is perhaps one of the oldest professions in data, dating back to the ancient Roman role of praegustator or 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, ensuring they do not permit either the accidental or intentional introduction of data contamination. The Data Taster may also be responsible for preparing and providing data. The hope is that the Data Taster will be conscientious and meticulous in preventing contamination from being introduced into data, to safeguard their own reputation and that of their organisation.

Data 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 data orders, then serves the requested data. The Data Server may also advise data clients on the optimal choices of data, based on the available data and the data preferences of other clients.

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

Data Whisperer – Is integrally associated with the roles of Data Server and Data Czar. This role is a 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 any senior executive or regulatory body throwing a ‘wobbly’ when they fail to correctly interpret the data that they are provided. Therefore, the responsibility of the Data Whisperer is to effectively communicate data analysis outcomes to the intended audiences and to jointly present and explain those outcomes in clear and simple language. Thea are required to have courage, strength and a high degree of empathy both with the data and also with the consumers of that data.

Data 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 a visible figurehead of all data architecture and management activities within an organisation. Although it bears some striking resemblance to 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 freely 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 draw on the skills, talents, knowledge, and experience of the other nine roles identified here.

Data 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.

To Conclude

There you have a brief explanation of the 7 (plus 3) new big data roles for 2015. So, to conclude…

Necessity is the mother of invention. Mother is also the invention of necessity. The judicious use of parallel grep, awk, and bash could have been reinvented. It could have been rebadged and released as the next best thing in data. Relevant roles must suit the revolutionary data spirit of the times. No?

But, 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 on the destruction of people through the denial of their historical understanding. He emphasised the importance of acknowledging this understanding. He also said it is crucial to obliterate this understanding. I could add, “This may occur whether the act is intentional, accidental or systemic.” We should have a solid understanding of IT history and the evolution of IT technology.

Finally, dear reader, my intention is quite severe. Still, please take this piece with a grain of salt.

In subsequent blog pieces, I will share my views on the evolution of information management. I will also discuss the incorporation of novel and innovative techniques, technologies, and approaches. These will be integrated into well-designed mainstream information supply frameworks. The focus is primarily on strategic and tactical objectives.

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