Employed early in my career as a turnaround specialist, my interest in data was there from the outset. Understanding marketing, sales and financial trends and the culture at those companies were key elements to being able to help build a strategy to turn around their performance. A subsequent move into consulting and data services started my formal journey as a data management professional. I have held operational and customer-facing roles spanning start-ups and market-leading businesses. These roles have focused on business intelligence, analytics, electronic marketplaces, and data acquisition and curation and have given me the opportunity to work and live in New Zealand, Australia, Singapore, the United Kingdom and Germany. As data becomes a currency used to drive the growth in many sectors, I am now principally focused on the challenges for businesses around data strategy, culture, ethics and risk in data governance, data protection, artificial intelligence and machine learning.
Right now, it’s a very exciting time to be a data management professional, as AI and machine learning start to become more mainstream. The discussions with businesses on data ownership, portability, ethics and value create an exciting environment in which to consider new ideas and the data governance models necessary to both support the business and protect the customer. In addition, GDPR in the EU created a new regulatory baseline for data protection, which has had broader impacts across the globe and is changing the way that many companies - and consumers - now think about the fundamentals around personal data.
We have new technologies, data and jobs constantly being invented, so be super-adaptive, super-mobile and super-willing to learn. Be adventurous, put ideas out there for comment and then be open to learn from others’ different perspectives. Ask questions, as there are ideas for data we have not yet thought of.The introduction of GDPR and the ongoing discussions on Brexit brought many external and regulatory factors to the table for many data practitioners. Data use, ownership, portability and governance were among the topics linked to those factors. Thankfully, the discussion on data ethics came quite quickly to the forefront in an environment in which AI and machine learning started to mean something. Alongside this, discussions have started to gather pace on what is being described as “adaptive governance” and how such considerations need to be applied to meet the different challenges brought by AI, machine learning and blockchain environments.
AI and machine learning will move out of proof of concept into production as more companies recognise that they can deploy at scale. Data governance models will adapt in an attempt to meet data protection issues associated with these technologies. Discussions on data ethics will develop and risk or decision-based frameworks to assess and govern projects and the uses of data in these environments will emerge. Approaches to audit the “black box” effect brought by AI and ML will enter the market. More companies will want to ascribe value to data on their balance sheet as a part of financial reporting.
Against a background of scarcity of data professionals, Crowe’s approach has been to recognise that combining broader business capabilities and experience with pure data specialisms offers the best way to drive insight and value for our clients. Our recruitment programme reflects that. Cross-skilling programmes provide opportunities for our change managers, actuaries and risk consultants to develop data engineering, analytics and solution architecture skills to enhance their own propositions, in addition to our data management propositions. We are leveraging Crowe’s global consulting and offshore capabilities, recognising that our data scientists and specialists can often deliver on engagements, regardless of location.
The future virtualisation of data where physical infrastructure and organisational boundaries are disregarded, the data pool globally is our data lake, and data ownership becomes a metadata layer, supported by a blockchain-style governance model within which data is accessible to all parties through that ownership layer.Business and professional services inc. recruitment