I have spent my professional career crawling around large IT systems as a university professor and as a software entrepreneur. For the last twenty years, I have been an independent industry analyst in Business Intelligence, documenting innovative applications that extend current technology.
Over recent years, I have focused on analytics and completed over a dozen courses, using the label BizSmartAnalytics.com. In particular, I became the topic of Deep Learning systems (as enabled by artificial neural networks) within typical corporations. In Spring 2018, I completed the 5-course Coursera specialization in Deep Learning, taught by Andrew Ng of Stanford.
My a-ha moment was the discussions of analytics showing predictions that exceed human-level performance. I concluded that: We humans have created tools smart enough to out-smart ourselves! I wrote my reflections in this article, the latter half of which addresses this point.
Excited by the technology but also concerned by social and ethical issues, I started to think how IT managers should approach analytical systems enabled by Deep Learning. The issues & challenges just exploded in my mind. I concluded that most IT professionals are woefully unprepared to manage properly or even to understand Deep Learning as applied to enterprise systems.
- Confronting Deep Learning Systems: How Much Things Have Changed and How Much We Do Not Know — Analysis of recent Strata surveys on implications for corporations about next-gen analytics (i.e., deep learning). (link, pdf)
- Shifts & Twists in Business Analytics: Reflections from Qlik Qonnections and Alteryx Inspire — Reflects from the Qlik and Alteryx conferences about the shift-and-twists challenges with next-gen analytics. (link, pdf)
- How Managers Should Prepare for Deep Learning: New Paradigms — Preparing for next-gen analytics by adopting new paradigms. (link, pdf)
- How Managers Should Prepare for Deep Learning: New Values — Preparing for next-gen analytics by focusing on new value propositions. (link, pdf)
- Vendors — Define Your Usage of #AI — The term Artificial Intelligence has become pervasive but meaningless. So what should vendors do? (link, pdf)
- How Managers Should Prepare for Deep Learning — Initial article describing my ah-ha moment with next-gen analytics. Note latter half of the article. (link, pdf)
Following talks were presented by Dr. Hackathorn:
- DVEM 2018, Are You Prepared for Deep Learning, Genesee CO, 2018-10-03 (pdf)
- Teradata Analytics Universe, How is Deep Learning Valuable for Your Company, Las Vegas NV, 2018-10-17 (pdf)
- Teradata Universe, Managing Enterprise Analytic Systems: Practical Advice for Leveraging Business Value from Deep Learning Systems, Denver CO, 2019-10-22 (pdf)
BizSmartAnalytics is offering the following services:
- Mentoring session for peer groups of managers involved with DL-enabled systems, along with providing one-on-one advice. This service is performed via the Patreon BizSmartAnalytics. Richard organizes and mentors peer groups, which meet online for an hour, twice monthly, plus one hour of weekly preparation. Group size is limited to 5 to 7 persons to facilitate interaction. Group composition is spread across business functions and even industries to maximize a diversity of perspectives. Richard shares the latest concepts, research, and trends occurring in rapidly-evolving DL-enabled analytics. By stressing mentoring-the-mentors, group members are equipped to mentor colleagues within their organizations. More details are given in Guidelines for Peer Groups.
- Custom 1-3 day hands-on workshops for training IT managers about DL-enabled systems. Fees vary depending on duration, class size and travel. Customization to specific use cases relevant to your company is a suggested option. Client supplies the training facility. Ask for a free consultation and proposal.
BizSmartAnalytics conducts interviews with managers who are involved with enterprise analytical systems using neural network technology. The interviews focus the emerging managerial issues and challenges facing managers at all levels. Interviewees do not need in-depth technical knowledge. The interviews are informal and unstructured. Interviews can optionally be conduct as anonymous. These questions are to stimulate discussion:
- Describe your management involvement with analytical systems and deep learning.
- What is the motivation for using neural network technology? Tactical or strategic or mixture?
- What are the issues that you are encountering or expect to encounter? Any surprises?
- Are these issues unique to deep learning? Are the issues technical or managerial?
- Do you have suggestions for best practices or lessons learned for similar professionals?
If willing to participate, contact Dr. Hackathorn.
Past Studies and Articles
Here are links to previous studies and articles about Business Intelligence.