Well, you would ideally want to know what you’re getting yourself into when you apply to that dream position or need to make that crucial hire. But besides that, data science plays a huge role in machine learning and artificial intelligence. Being able to sift through and connect huge quantities of data, followed by forming algorithms and functions that allows virtual entities to learn from that data is hugely in demand in today’s marketplace. Machine learning is one of the most exciting developments in the tech world as the innovation continually impress. Take IBM’s Watson and its victory on Jeopardy!, or Google’s DeepMind beating the best human players in the world at the board game, Go. Both examples of our future mechanical overlords bringing us to heel under their cold metal boots . . . I mean, of the advances in machine learning.
A good IT project proposal isn't a technical inventory. Business executives don't care that the stack will use hyper-converged systems with NVMe memory connected to the public cloud via pixie dust. Couch all messages in terms that make sense for the company (see Figure 2): What will the project do to better manage costs and risks within the business's operations? Does the change enable greater overall business value without changing the functionality of the company's existing products or services? Is output or margin increased, or both? Does the change enable a new product or service at a suitable margin? ... Consider what's important to your company when developing the IT project proposal. The proposed change doesn't have to better manage risk and cost, improve existing business and also bring a new offering to customers. Some organizations take on more risky initiatives if they can lower costs appreciably.
IRS anti-fraud measures, such as the recent introduction of a new 16-digit alphanumeric authentication code on W-2 forms, have made it harder for scammers to file fraudulent tax returns using only stolen W-2 data, says Adam Meyer, chief security strategist at SurfWatch Labs. So information such as the Adjusted Gross Income (AGI) number from previous year tax returns, for instance, has become a valuable commodity to criminals, Meyer says. Many tax-related forms have begun asking for that information and other data such as birth dates and driver’s license numbers as secondary authentication measures. “I think you are going to see a shift in cybercriminal tactics,” as a result of these changes, Meyer predicts.
Underpinning the Waze platform is more than 100 microservices, and each one is hosted across multiple availability zones and datacentre regions for resiliency purposes. “The most mission-critical ones are spread across multiple providers, Amazon and Google, so we can provide the best redundancy possible for our users,” he said. Waze’s desire to source cloud services from more than one provider was hastened by an eight-hour outage AWS suffered in 2015. “Our engineers made sure Waze did not crash on that day, and I’m happy to say it didn’t, but it came very close,” he said. “It was one of the triggers for us to realise we actually needed a multi-cloud solution, and can’t just rely on one provider. “This was before our GCP migration. We wanted to spin up our GCP cluster sooner, but we couldn’t do it because weren’t ready.”
One of the biggest challenges in banking is meeting the needs of compliance, best exemplified by the arduous task of filling out forms and applications when applying for anything from a new account to a loan. These tedious processes often result in customers frequently returning to the bank due to missing information. Certain fintech start-ups such as QumRam make it possible to meet the extensive regulatory needs of the banking industry, while helping reduce fraud and streamlining the entire process for customers. Bank branch networks could leverage similar types of technology by providing customers the option to complete their forms in the branch within the waiting area or allow them to start the process at home and then complete the final stages at the branch level.
The goals of the function need to be prioritized once cascaded from the organization. It is better to include the board and executive leadership to endorse them and it is suggested to take them along the journey. The function provides risk governance services that can be considered horizontal in the organization. The same will be pushed to business units, they like it or not. But, early collaboration across the organizational units in strategy analysis provides future buy-in to risk management activities. This would enable the units to participate in eliciting risks and decisioning on solutions related to data, in a council discussion, once the services are pushed to a division. The next step would be to come up with capabilities that would achieve the objectives of the data risk management function.
Forward-thinking companies are beginning to apply concepts like active defense and corporate social responsibility to cyberspace. As cybersecurity regulations take shape, companies can choose to stay in the vanguard of progress – or simply react, following the rules as they develop. Managers must think in new ways about data, communications, business law and even the ethics of trading off potential corporate benefits against risks to consumers’ privacy. At stake is not only a firm’s reputation but also, potentially, legal liability for failing to follow emerging industry standards. For example, Consumer Reports recently announced that it will be rating companies’ cybersecurity and privacy practices. Businesses of all types, not just tech-centered ones, can help keep themselves in the clear by putting cybersecurity at the forefront of their risk management efforts.
In the past, the complexity and size of an operation generally provided safeguards against data theft or leakage. But with commonly used data mining tools, it’s now possible to separate out meaningless shop floor data and hone in on the important events, which roughly adhere the 80/20 rule. Add in multiple companies and begin correlating bottlenecks and other noteworthy industrial events, and that data suddenly becomes much more valuable to a lot of people—makers of equipment, government or industry policies, marketing groups, as well as the highest bidders within a particular industry or those looking to invest in an industry. “It used to be that an employee would take out data they downloaded onto a USB,” said Ford.
Harsh environments raise the odds that a sensor will generate bad information: Weather, vandalism and pests are among the many dangers. For better results, enterprise IoT users may need to calibrate their sensors, install redundant nodes or use one type of sensing device, like a camera, to monitor another. Artificial intelligence can help solve the problem by weighing inputs from multiple sensors to reach accurate conclusions. For example, doctors can monitor a patient with wearables that measure different vital signs and can be checked against each other. Also, filtering out readings that aren't needed -- like 1,000 consecutive reports that a pipeline hasn't cracked in the last five minutes -- is a big part of what edge computing is designed to do.
The group said via email that it has had a database of about 519 million iCloud credentials for some time, but did not attempt to sell it until now. The interest for such accounts on the black market has been low due to security measures Apple has put in place in recent years, it said. Since announcing its plan to wipe devices associated with iCloud accounts, the group claimed that other hackers have stepped forward and shared additional account credentials with them, putting the current number it holds at over 627 million. According to the hackers, over 220 million of these credentials have been verified to work and provide access to iCloud accounts that don't have security measures like two-factor authentication turned on.
Quote for the day:
"In order to be irreplaceable one must always be different." -- Coco Chanel