By Bill Franks, Sep 12, 2019
The vast majority of people building analytics and data science processes have every intention of being good and ethical. As a result, most potentially unethical and evil processes arise in situations where that wasn’t the intention. The problem is typically that proper focus and governance is not in place to keep analytics and data science processes on the side of good. On top of that, what is good and what is evil isn’t nearly as clear cut as we’d wish it to be.
By Bill Franks, Aug 08, 2019
We’ve had technical people focused on the ingestion and management of data for decades. But, only recently has data engineering become a critical, widespread role. Why is that? This post will outline a somewhat contrarian view as to why data engineering has become a critical function and how we might expect the role to evolve over time.
By Bill Franks, Aug 07, 2019
Lately I’ve had a lot of conversations with clients about the intersection of ethics and analytics. I’ve also been presenting on the topic at a number of conferences. The interest in ethics has exploded recently, driven in large part by the rise of artificial intelligence. One common question I get is what my top tip would be for a company to get started in becoming a leader in analytical ethics. I’ll discuss my answer in this post: intentionality.
By Bill Franks, Jun 12, 2019
Not long ago, the role of Data Scientist was what most companies wanted to discuss with me in terms of roles they needed to understand and add to their organizations. Then, the role of Data Engineer became a big topic of discussion. In the past year, there has been a massive increase of attention being paid to yet another role that is still new enough that its title hasn’t been standardized. This role is referred to by a range of names from Analytics Translator, to Analytics Catalyst, to Analytics Liaison, and more.
By Bill Franks, May 09, 2019
Historically, concerns about over-zealous censorship have focused on repressive governments. In recent times, however, a new path to censorship has arisen in the form of search engine and social media companies that are building analytically-based censorship algorithms. This post outlines why using analytics for centralized censorship is a steep and slippery slope and also lay out an alternative that will enable those same censorship analytics to provide people with a choice rather than a dictate.
By Bill Franks, Apr 11, 2019
While there are many advantages to the cloud, it is also necessary to use caution to make sure that the risks of the cloud are mitigated while pursuing the advantages.
By Vania Ahmad, Mar 20, 2019
Nearly 200 of IIA’s clients, analytics experts, and members of the analytics community gathered in Portland, Oregon this week for the spring Analytics Symposium. IIA also hosted its first Women in Analytics networking event, an interactive Analytics Workshop, and introduced two tracks of sessions to bring the most value to attendees. This blog covers key themes of the conference and highlights from each session.
By Bill Franks, Mar 14, 2019
As data science and analytics teams continue to feel pressure to deliver more value from analytics, many organizations still struggle with the processes and technology required to deploy models into production and more rapidly make data-driven decisions. When evaluating how to best undertake these activities, organizations should consider an important distinction to determine the best path forward.
By Bill Franks, Feb 14, 2019
Over the years, I’ve seen analytics professionals of all stripes blow their credibility and lessen their impact by falling into a common trap. I have to admit that I fell victim to the same trap early in my career. While our intentions are pure, our analytical minds and approaches can get the best of us and we explain too much. We’ll be better off if we learn to provide less detail and stop talking sooner than we are naturally inclined to.
By Bill Franks, Jan 10, 2019
With the hype surrounding Artificial Intelligence (AI) today, almost everyone in the analytics and data science space has been asked about AI by their business partners. Unfortunately, during these conversations it often becomes apparent that the business person really doesn’t have a clue what AI really is or what AI is best able to solve.