Data is now widely recognized as the most important asset that any company, public sector or private entity, possesses.
The latent power of data and recent technological advances, in the production and utilization of insight gained from extremely large volumes of varied, multi-modal and high-frequency data sets, has led to the recent rise of a new class of professional roles — Chief Data Officers, Chief Data Scientists, Chief Data Evangelists, Chief Data Strategists, etc.
It has been about 5 years since these roles have become “hot jobs”.
As someone who had the honor of being amongst the first wave of these professionals in the US Federal government and who achieved success in the role (read about my time as the Deputy Chief Data Officer for the US Department of Commerce here and see what we accomplished here), I want to share the lessons learned from my service.
From my experiences, effectiveness as a Chief Data Executive hinges on three critical factors:
Current expectations are that a Chief Data Executive should be a technologist, a developer (scoping, implementing, and transitioning data products and services), a steward (for improving data quality), an evangelist (for data sharing and novel data business model generation), and a strategic visionary (for the organization’s data assets).
It is impossible for a single person to be all these things and accomplish them all in any given work week. Thus, it becomes critically important that the Chief Data Executive is an excellent “manager by influence” — able to synergistically guide and work with other teams to execute on the data mission. This influence is the cornerstone of the collaborations necessary to achieve escape velocity and then have long-term success and sustainability.
Building these alliances, which lead to a pathway of success, is built upon the trust that one’s colleagues must have in you with regards to your word, and with regards to your moral compass and values. A Chief Data Executive whose actions and or words are not grounded in integrity will have a hard time achieving and maintaining the relationships necessary for any sort of success.
In this context, competence refers to “having sufficient skill, knowledge, and experience to perform the job”, i.e. being properly qualified. The common set of skills that are required to be a Chief Data Executive include knowledge of the business and mission, knowledge of computer science, data science, or both, and knowledge of product definition and delivery.
A competent Chief Data Executive is a rare mix of technical guru, businessperson, marketer, and adept executive leader — someone able to communicate in all spheres and that can easily translate between each.
At this moment in time, many organizations and employees are still struggling to understand what Chief Data Executives do, where they fit into the organization, what their essential skills should be (based on their needs), what these executives are responsible for, who they should report into, and how to measure their impact.
But these are all topics for another time. :-)
(This post is also available on Medium)
At the 2016 IEEE 2nd International Conference on Collaboration and Internet Computing (CIC 2016) in Pittsburgh, Pennsylvania this November, Star Ying and I will present a paper on Big Data Privacy (read paper here).
In this paper, we provide a simple description of something that should be obvious to most — there is no privacy when it comes to Big Data.
In the paper we describe the “as-is” state of the data privacy protection practice, and model the core of what constitutes Big Data. We then weaved the two worlds together using a probabilistic framework and take the framework to its obvious, natural conclusion.
This is the start of a critical discussion and introspection — one that we hope the community will engage in.
(This post is also available on LinkedIn)
Dr Tyrone Grandison
Executive. Technologist. Change Agent. Computer Scientist. Data Nerd. Privacy and Security Geek.