Banks need help, and they have recognized that some of that help will come from Fintech firms. That is why so many banks have created incubators and accelerators. Banks and Fintech firms need each another. It took a while to sink in, but most players now agree. But Fintechs struggle with how to partner with banks, and vice versa. What will a good Fintech partner look like? Without a doubt, banks are looking for partners. They want companies that will share their business goals and understand their vision. They want partners who will measure success the way they do. But what partnering model are we talking about? There are several existing or emerging models.
Within IT, there are places where we want to move in a more agile way -- where we want to move faster. There are also certain activities where waterfall is still an excellent methodology to drive the consistency and predictability that we need. A good example of that comes with large releases. We may develop changes or features in a very agile way, but as we move towards making large changes to the business that impact large business functions, we need to roll those changes out in a very controlled, scripted way. So, we take a little bit different look at Bimodal than some companies do. Your other question was on Shadow IT. One of the things that we have challenged a lot over the last year or so is this concept the role of the IT organization relative to the rest of the enterprise.
Services and APIs are only loosely-coupled in conceptual architecture, but not in the real-world where people still have to manually discover and integrate them at the Application and Process layers. This is the reason why Service Orientation has yet to have delivered “Business Agility”. From that high-level Enterprise Architecture perspective (as opposed to the bottom up IT view) it’s not useful or scalable to be stuck manually considering individual APIs. It would be better to have an abstraction, a model for looking at all of these endpoints as objects that expose functionality, but hide their complexity and automate management of the end-to-end API contract lifecycle in order to advance the Service Orientation architectures.
Extract, Transform and Load (ETL) systems commonly integrate data from multiple applications and systems and are typically developed and supported by different vendors or hosted on separate computer hardware. The disparate systems containing the original data are frequently managed and operated by different employees as well. It is likely you have found some point-to-point tools in your tool kit to help with this enormous data corralling challenge, but what about maintaining the integrity of the data as it moves away from your original system downstream? An even more elusive question to answer is do you need enterprise visibility into the overall integrity of your key business data?
The industry's interest in AI, Rajan says, has been driven both by rising costs and increasing volumes of data. "There isn't necessarily the capacity to capture and process and understand all of it. I think AI, particularly a lot of early solutions, are targeting those issues -- being able to take large volumes of data, put it through levels of processing that can allow some level of relevancy to crop up to support decision making and influence the course of care." The aim is for AI systems to do what doctors can't always: keep up on every detail of every patient's visit to every specialist or hospital, as well as each pertinent new piece of research, disease outbreak, and public health recommendation. The system must not only digest all that information, but also factor in the patient's symptoms and then recommend a diagnosis or course of treatment that takes all those elements into account.
“Hey ‘Big Data’ is just a big fuzzy word for me” quoted a Vice President of an Innovation Center at a big logistic company back in early 2015. Just one year later, he not only has to admit that ‘Big Data’ is the next big revolution, but has already applied big data technology to dramatic effect significantly growing the business and reducing costs. In fact, he’s been so successful that he’s been given the funding for a new Machine Learning department! UPS’ 1 billion investment in big data more broadly blows the whistle for all logistics companies all around the globe to get very serious about becoming data-driven or otherwise be in fear of being wiped out. The delta being created by those who have been quick to embrace big data is growing rapidly.
Talking of Snowden, Zimmermann notes with a certain amount of pride: "Snowden got his hands on some documents that showed some products that [the NSA] had broken the crypto [on]—and none of my stuff was on the list." Silent Circle's Blackphone device runs a security-toughened version of Android it calls PrivatOS. Calls are encrypted end-to-end which means even the company itself can't hand over the details to anyone. "We have no access to it. None. We can't disclose what we don't have access to," the company says. Since the V&A exhibition opened, the Blackphone has been added to the collection of a second museum—the International Spy Museum in Washington DC. Its 'Weapons of Mass Disruption' gallery explores the challenges facing the intelligence community in the twenty first century.
While the disconnect between the conception of "business processes" as being "business process flows" and event architecture -- or microservices architecture -- seems obvious, it's not being adequately reflected in most enterprise architecture methodologies. The business process output of EA is often prestructured into business process flows and leans toward workflow thinking when translating EA requirements to IT requirements. It is possible to "retroject" an understanding of modern software architecture evolution and design approaches based on the cloud and microservices into today's EA methodologies, but this is difficult to do in a consistent and organized way.
“There are challenges ahead. A lot of companies will have their work cut out for them to be compliant in time,” said Bridget Treacy, partner at Hunton & Williams. “All organisations that have not done so already, really have to start thinking in very pragmatic terms about what the GDPR means for the business and how they are going to handle their data assets, because two years is not much time,” she said. The final alarm bell has been sounded, said Stewart Room, cyber security and data protection partner at PricewaterhouseCoopers (PwC). “There are no more alarm bells after this. There is no more pretending. All organisations that have not started preparing now need to start taking this seriously,” he said.
There's nothing in value-sensitive design that's about a specific technology. It's about how do we foreground what's important to people in the tools and technologies and infrastructure we build. Most of my work has focused on information technology, but other people have applied it to wind turbines, to designing processes for customs in major ports, for transportation systems. ... When you're designing a system, who do you focus on? The language in the field is to talk about users and user-sensitive design. So when people design, they think about who is going to use the technology. We have methodologies for doing usertesting, but we know that others are stakeholders, too. So one of the key changes is to bring other stakeholders in to make sure they're considered along with the users.
Quote for the day:
"Just because something doesn't do what you planned it to do doesn't mean it's useless." -- Thomas A. Edison