It is crucial that data scientists and analysts take into account the existing biases and formulate remedial solutions for these. As hidden biases in big data are an impediment to accurate decision-making and can affect outcomes, it is paramount that business leaders and lead management members remain alert.
What will bring 2018 for blockchain and distributed ledger technology? How will Bitcoin and other cryptocurrencies develop? And how the acceptance of blockchain technology will evolve in 2018? In this blog, I like to share my ideas and opinions on what trends and developments to look for in 2018. Let’s go!
For a myriad of data scientists, linear regression is the starting point of many statistical modeling and predictive analysis projects. The importance of fitting (accurately and quickly) a linear model to a large data set cannot be overstated. The goal of this article is primarily to discuss the relative speed/computational complexity of these methods.
Better cybersecurity protections for IoT requires improvements in people, process and technology. So let’s not pit people issues against technology protections in a fight for dollars — nor pretend that a perfect black box is coming that will enable IoT nirvana while removing people and process from the security equation.
Digital champions utilize analytics strategically to better understand customer trends and preferences, and instantly respond to changing market conditions. Research shows that excelling in analytics cannot just accelerate time-to-market, but it can also be financially rewarding. To overcome the hurdles, organizations should focus upon organizational readiness, open data and interoperability, and well-honed orchestration of people and processes.
Far more tactical implementations of Robotic Process Automation (RPA) are more promising. RPA is not machine learning, it uses software bots to mimic human activity. Tone down your AI expectations. And get ready for the next generation of AI big words.
Apart from big data, businesses are making optimum use of open data - data that is inexpensive, easily accessible, and a profitable resource goldmine. Businesses are now starting to feel the benefits of open data in synchronization with their private data and are collaborating on a whole new level to acquire state of the art business models, improved revenue streams, innovative products and services, and a competitive advantage over their business rivals.
Organizations need to take an inside-out approach to cybersecurity assessments, looking for areas of weakness and making it a priority to safeguard systems that must be impervious to attacks to protect human life and safety. Companies should undertake scenario planning to “think the unthinkable” and run simulations to ensure that their firm is ready to withstand such attacks.
We wanted to follow up our previous piece about how to grow as a data scientist with some other skills senior data scientists should have. Our hope is to bridge the gap between business managers and technical data scientists by creating clear goals senior data scientists can aim for. Both entities have to take on very different problems. Both benefit when they are on the same page. This is why the previous post focused so highly on communication. It seems simple, but the gap between technical and business continues to grow as new technologies keep getting piled on every year. Thus, we find it important that managers and data scientists have a clear path of expectations.
Along with a few near-term predictions - so hard to resist - I'd also like to make some predictions not just about technology per se, but about related changes to organizations, processes, and the cultures around them. Here's my main prediction: By 2030 what we've come to know as "IT" today will be virtually unrecognizable.
It’s high time that organizations realize that while the long-term information security environment is likely to become better in obvious ways, it is likely to worsen in subtle ways due to technology and vested interests. The key to understanding this phenomenon lies with, how tomorrow's information systems are going to be used. This calls for an active participation in Information Security Management System activities right from the top to the very bottom of an organization.
Consumers with access to technology at their fingertips expect a digital experience taking the need for automation to newer levels positioning 2018 to be an exciting year for realizing tangible outcomes from automation. Why, you ask? Well, think about it -- this may very well be that single overarching term that brings the business and the technology mindset under the same umbrella with the common goal of enriching the experience of the end customer -- both external and internal. Let us join Business and IT in wishing Automation a Happy New Innovative 2018!
There are real-life AI applications being deployed that automate business processes to improve the customer experience. We are also hearing progressively more myths when it comes to business applications. Following are common myths, assumptions, and truths to know as you consider your AI strategy in 2018.
Creating an IoT Monetization roadmap should be the top priority for any IoT initiative. Take the time to identify, validate and prioritize those use cases with the key business stakeholders and constituents to ensure that you are focused on the right use cases in the right order. There is no value in generating and collecting the data if you don’t have a plan for how to monetize that data.
Decentralization has its flaws; the complete security and privacy are yet to be achieved. It doesn’t mean, however, that blockchains are unsafe: substantial progress has been made already in the security area and clever developers keep on improving the technology on a regular basis.
In order for a data scientist to grow, they need to be challenged beyond the technical aspects of their jobs. Data scientists have the opportunity to sway company decisions. They have a lot of responsibility on their shoulders. That means they need to take ownership of the work they do. They need to question their data sources, be concise in their insights, know their business and help guide their leaders.
Markets move too fast and customer expectations elevate too precipitously for businesses to rest on their laurels. Here's a DevOps "to-do list" for 2018 that should be priorities for anyone who wants to make sure their organization is running at the front of the digital pack through next year - and beyond.
The financial sector received a big boost due to technological integration. Banks revealed during this amalgamation and now, the insurance sector has got a taste of the nectar generated by churning Finance and Technology (FinTech). Listed in this article are seven ways in which FinTech is impacting the insurance industry.
Maybe you have an AP automation solution in place that provides automated workflows, but requires customization to address your unique processing requirements. Or your automation solution works, but you lack full end-to-end invoice processing visibility and are unable to further optimize processes based on a drill-down of key performance indicators.
It will be that smart products connected to the internet, where standards may or may not exist for them, pose a new challenge for experts who may have the requisite skills to offer opinions on the dumb version of a product but lack the new skill sets to avoid exclusion when offering opinions on the smart version … or will new experts need to step forward to complement and supplement traditional experts?
What will happen in cyberspace in 2018? How will technology impact the real world over the next year? Once again, the cybersecurity industry is full of security predictions, trend reports, cyber forecasts, IT security analysis and red-hot security examples to allow everyone to try to connect the dots to the future. Here’s your annual security industry prediction roundup from the top cybersecurity experts, magazines, companies, analysts and more.
The terminology of financial services technology morphs as fast as the technology itself. Already, terms like big data, cloud services, biometric authentication, and more are so yesterday. Yet bankers must keep up as new tech terms get invented and adopted. As fast as technology accelerates, people still have to master the language in order to attempt not only to understand what’s going on, but to figure out whether the new things are worthwhile.
2017 has undoubtedly been the break-out year for enterprise robotics software. The global market for RPA Software and Services will reach $898 million in 2018 and is expected to grow to $2.2 billion by 2021 at a compound annual growth rate of 54%.
Intelligent disobedience stems from the concept of teaching a guide dog to go directly against the owner’s instructions if the commands given risk the owner’s safety.