Scrum, DevOps, SAFe, Kanban, Continuous Delivery. With so many different buzz words floating around the Agile sphere, it can be easy for companies to get excited and bite off more than they can chew. Every organization is different in its readiness to adopt Agile and needs to carefully consider many factors when deciding how to start the journey. Smaller organizations or teams such as start-ups or IT departmenst of larger companies may be able to immediately start practicing Scrum. On the other hand, larger organizations that have traditionally worked in a waterfall fashion or are in heavily regulated industries, may find it difficult to make the big changes that accompany a framework such as Scrum. As a result they may get discouraged or quit altogether if they run into problems, early on.
Modern software delivery is a constant struggle to abstract, simplify and model some part of the real world into a useful automated process. However, lack of domain knowledge, time pressure and imperfect information often lead us to oversimplify the real-world, so edge cases fall through the cracks. For example, complex distributed systems built around microservices often require some kind of production monitoring that tries to process transactions end-to-end with test data, and remove those test cases at the end of a successful check. It's difficult to imagine how something like that can cause serious damage, until you know that someone called Jeff Sample ended up stranded in Buenos Aires when the airline operating the connecting flight deleted his ticket without any trace.
“A European data subject can make requests on what data the bank has on it, and can make changes and request deletion of the data,” said Roth, who is a former chief privacy officer at American Express. “These require business practices that banks don’t have in the U.S.” Companies with multiple legacy systems will face one of the toughest challenges, Dingle said. “The first problem you will have when you deal with GDPR is that you have to somehow be able to reconcile how the data flows between all these different databases, even though they were made in different times, they may have different formats [and] the data might be called something different,” she said. “That’s why a lot of these beautiful ideas of GDPR are very difficult in reality for people to execute on.”
While it was once thought that computers would never be able to demonstrate true emotional intelligence, examples are starting to blur those lines. In one study, computers were able to detect criminals with a high degree of accuracy just by looking at their facial features and movements. This means they’re getting good at reading people, a key social attribute that aligns with some degree of EQ. Closer examination shows that while the computers may be able to read people, that doesn’t necessarily mean they can understand people. They were able to pick out the criminals by analyzing incredible amounts of data about facial features. The decisions the computers made were based not on insight, but on algorithms. There are plenty of similar examples in which a machine can demonstrate the appearance of empathy when they’re actually just running the numbers.
There are several broad themes to this year’s hype cycle, with a particular focus on disruption and disruptive opportunities. In the context of disruption, some of these are still at the innovation trigger stage–being used by some brave souls willing to take a change and deal with challenges of new technologies (or applications of technology). Broadly, Gartner sees AI and human-centered design in this stage. Further along the curve is customer experience and intimacy. Some grouping are moving toward the trough of disillusionment, as the hype grows without being replaced by enough tangible examples and paths to success. Finally the core areas of the Nexus of Forces (cloud, mobile, social, and information) are rapidly moving toward the plateau of productivity. Exploring the details will help you have appropriate expectations as you embark on your change initiatives.
Edge computing is a “mesh network of micro data centers that process or store critical data locally and push all received data to a central data center or cloud storage repository, in a footprint of less than 100 square feet,” according to research firm IDC. It is typically referred to in IoT use cases, where edge devices would collect data – sometimes massive amounts of it – and send it all to a data center or cloud for processing. Edge computing triages the data locally so some of it is processed locally, reducing the backhaul traffic to the central repository. Typically, this is done by the IoT devices transferring the data to a local device that includes compute, storage and network connectivity in a small form factor.
With the IoT, the impact could potentially be even more threatening. Instead of “just” stealing data, an IoT hack could potentially take over the functionality of the device being hacked. For example, a IoT-hacked car could be driven off the road, or the systems and controls of a home could be manipulated. Another issue is the potential loopholes in firewalls – giving access to networks – that a poorly-designed IoT device could provide ... The GDPR explicitly introduces a general mandatory notification regime. When there is a personal data breach, a supervisory authority needs to be notified within 72 hours once an organization becomes aware of a breach, and impacted individuals must also be notified if a certain threshold is met.
Continuous deployment involves automatically testing incremental software changes and frequently deploying them to production environments. With it, developers' changes can reach customers in days or even hours. Such ultrafast changes have fundamentally shifted much of the software engineering landscape, with a wide-ranging impact on organizations' culture, skills, and practices. To study this fundamental shift, researchers facilitated a one-day Continuous Deployment Summit on the Facebook campus in July 2015. The summit aimed to share best practices and challenges in transitioning to continuous deployment. It was attended by one representative each from Cisco, Facebook, Google, IBM, LexisNexis, Microsoft, Mozilla, Netflix, Red Hat, and SAS.
"Introducing a module system into a language and platform like Java SE, 20 years after its creation, when a large portion of the world's systems are running on it, is a very serious change," said George Saab, ... Once developers get used to it, modularity has the potential to make their lives easier by allowing them to, as Oracle puts it, "reliably assemble and maintain sophisticated applications." The module system reduces the size and complexity of both Java applications and the core Java runtime itself. It also makes the JDK more flexible, allowing developers to bundle just those parts of the JDK that are needed to run an application when deploying to the cloud. "This version of Java SE will provide millions of developers [with] the updated tools they need to continue building next-generation applications with ease, performance and agility," Saab said today in a statement.
While banks in the past have taken something of a one-size-fits-all approach, expect services to become much more tailored to your individual needs in the future. Behind this development will be data - or, rather, the more intelligent use of data - by banks. From the way we spend our money to the things we actually buy and the devices we use to log in to our account, banks can use data to build unique profiles of their customers. There are also external data points that can be used, from social media profiles for example. Of course, no bank should be using any of this data without the customer’s explicit consent, but the potential for highly personalised banking services should be a strong draw for many people. For instance, who wouldn’t appreciate discount offers on items you buy regularly sent directly to - and redeemable through - their smartphone?
Quote for the day:
"Anyone who lives within their means suffers from a lack of imagination." -- Oscar Wilde