The Doppler Quarterly Winter 2018 | Page 61

minds wrapped around. Techniques to visualize data sets help us to clearly see errors, patterns and anomalies that our eyes would otherwise be unable to dis- cern from the raw data itself. Second, data visualization is sometimes thought of only in terms of outputs for humans. More and more, we see our applications comprised of chains of pro- cesses connected via APIs. The output of one stage needs to be presented in a manner that can be understood as input to the next stage. Thinking of data visualization from this perspective allows us to go beyond what our human eyes can perceive, and address the superhuman capacity of what machines can see. Enterprise Considerations When we look at all the moving parts, it becomes easier to understand why large enterprises often struggle to apply AI to their business processes. The three areas below outline some of the biggest challenges. Organizational Structure Organizational structure tends to be the single biggest impedimen t to prog- ress for enterprises. As organizations grow into the thousands, tens of thou- sands or even hundreds of thousands of employees, they naturally form orga- nizational structures and processes to maintain some semblance of order. These structures and processes often create inertia, with silos and bureau- cracy becoming impediments to innovation. This inertia can easily quash efforts to apply AI to business processes, simply because of the number of data inputs, the overall amount of data and the additional data manipulations AI requires. Incidentally, concepts such as the Cloud Business Office (CBO), which CTP advocates, can help bridge silos by providing representation to every business function. We have seen this facilitate agility, innovation and appropriate orga- nizational change. Public Cloud Capabilities As we mentioned earlier, AI can be significantly facilitated by services in the public cloud that provide speed, scale and cost advantages. However, since the shift to the public cloud is relatively new to many large enterprises, we find that they often do not have the skills and experience to move their workloads while still managing critical considerations, such as security, compliance and costs. Without the guidance of people who have repeatedly assisted large enterprises to set themselves up properly in the cloud, we have seen countless corporate efforts delayed or outright failed. This definitely lies in the realm of “you don’t know what you don’t know,” so do not shy away from getting guidance from those who have done this before — a lot! WINTER 2018 | THE DOPPLER | 59