“You may have a patient surveillance system that requires really large datasets to monitor their vitals and maybe do some predictive analytics about how they’re trending, and that requires immediate, truly real-time insights for the patient while they are still in your care setting.” But population health management prioritizes different metrics and aims to achieve somewhat different results, he added. “Population health is about identifying groups of patients and figuring out a commonality around their needs. After you identify a common need, you redesign care around delivering that service or improving that outcome.” Population health programs also tend to generate large volumes of data that is often used to track improvements over time.
Continuum Analytics, the creator and driving force behind Anaconda — a leading open data science platform powered by Python — has allied with IBM to advance open-source analytics for the enterprise. Data scientists and data engineers in open-source communities can now embrace Python and R to develop analytic and machine learning models in the Spark environment through its integration with IBM’s DataWorks Project. ... This program empowers corporations to better understand, use and maximize the value of their data. The program will support IBM’s DataFirst Method, a methodology that IBM says provides the strategy, expertise and game plan to help ensure enterprise customers’ succeed on their journey to become a data-driven business.
The issue is that this mentality of the “big deal” still pervades for many senior bank decision-makers, yet today it’s no big deal. If a startup can get a full suite of banking software up and running like Ant Financial, Solaris, Thought Machine, PrivatBank and more, then you know the answer today is all about speed and agility at low-cost. There’s no big deal here. In fact, as alluded to in an earlier blog, if you can build a developer-driven bank where a micro-services architecture allows very small teams to change little parts of the architecture continually, then you have a bank built for today – a bank that can provide updates for its apps and APIs every day (or even intraday), rather than every year or even biannually.
Behind every successful fintech firm, there is an agile and well-diversified team of forward-thinkers. Since startup companies operate with limited resources, every employee counts. Therefore, it is imperative to have employees with a combination of experience and relevant skills for fintech companies. Even if you find skilled individuals, they will most likely ask higher wages because their opportunity cost is very high. ... Unless one is speaking to a financially and technologically savvy investor, it’s often difficult for startups companies to describe the value proposition and more explanation is needed than in other industries. Therefore, fintech companies are required to know their products and to have efficient ways to tell their story for anyone to understand.
The Yahoo breach has drawn particular attention not only for its size — 500 million accounts were exposed by hackers Yahoo says were nation state actors — but for the time the company took to notify victims. The breach occurred in 2014, with Yahoo only announcing it this month. But reports indicate that the company may have been aware of the hack in July or August of this year. The timing of the disclosure drew swift criticism from lawmakers who suggested that the company might have sat on the breach to avoid disrupting a purchase deal with Verizon. “As law enforcement and regulators examine this incident, they should investigate whether Yahoo may have concealed its knowledge of this breach in order to artificially bolster its valuation in its pending acquisition by Verizon,” Sen. Richard Blumenthal
Systems programmers and database administrators in large shops earn six-figure incomes. They earned these incomes by polishing their skills in a particular technical specialty, and by mastering tools that have proven their worth over time and that they trust. Their career calling cards are their expertise and their ability to use these tools to solve difficult problems, so they are not always open to new tools and technologies that challenge the tools and approaches that they cut their teeth on. If you are considering a new approach or vendor toolset, it is really important to obtain staff buy-in before moving forward. If you can't get buy-in, and you and the company have determined that it's absolutely necessary to move forward, you should be prepared to lose people.
"At one extreme, forking is one of the fundamental rights you have with open source code and we talk about how great it is to have the freedom to fork — it can be a good way to revive a dying project," says Allison Randal, president of the Open Source Initiative. As an example, Randal points out that before the LibreOffice fork, OpenOffice.org was suffering from "human problems" that prevented the code from moving forward. The LibreOffice fork was successful and now has overshadowed OpenOffice.org. Unfortunately, forking doesn't always produce such a positive outcome. "I have seen cases when forking a project divides the community, introduces tensions, cuts resources and ultimately kills both projects," Randal says.
Many organizations rely on traditional SIEMs to store data and run simple, real-time, rules-based analytics. This works for providing insights into activities at a point in time, but most attacks are more subtle and may unfold over weeks or even months. The ability to consider more and varied data types over a longer period of time offers richer insight as to who the attacker was, what malicious activities were performed, and how to remediate the threat. Newer big data platforms overcome the limitations of traditional SIEMs and provide the ability to keep up with the volume, velocity, and variety of data while conducting more sophisticated statistical and machine learning analytics.
It is an approach to modularity that functionally decomposes an application into a set of services. It enables teams developing large, complex applications to deliver better software faster. They can adopt new technology more easily since they can implement each service with the latest and most appropriate technology stack. The microservices architecture also improves an application’s scalability by enabling each service to be deployed on the optimal hardware. Microservices are not, however, a silver bullet. In particular, domain models, transactions and queries are surprisingly resistant to functional decomposition. As a result, developing transactional business applications using the microservice architecture is challenging.
Mobile devices are at the heart of merged channel because those handheld computers — and, yes, mobile phones are computers — make any other compensation approach ridiculous. How, for example, is a Macy's in-store-versus-online mentality supposed to deal with someone scanning a barcode in-store with a mobile device and then purchasing it from Macys.com? No need to worry about which division gets what percentage of the sale. It's a Macy's purchase and that's that. The point is to look at purchases from the shopper's perspective. That is what retailers tell their shareholders, right? That they are so customer-centric? Shoppers see it as a Kohl's transaction or a Walmart purchase.
Quote for the day:
"Even if you are doing robust risk assessments, between that and human error, breaches will happen."
-- Pam Hepp