Profile of Lisa MorganFreelance Writer
News & Commentary Posts: 244
Lisa Morgan is a freelance writer who covers big data and BI for InformationWeek. She has contributed articles, reports, and other types of content to various publications and sites ranging from SD Times to the Economist Intelligent Unit. Frequent areas of coverage include big data, mobility, enterprise software, the cloud, software development, and emerging cultural issues affecting the C-suite.
Articles by Lisa Morgan
Corporate memories are at risk because the growth in data is outpacing companies' ability to govern and manage it.
Pattern recognition and anomaly detection provide insight into unwanted behavior, but mainstream techniques may be missing subtle clues.
Enterprises are running into challenges with robotic process automation because lines of business or IT are missing the bigger picture. Thinking strategically and cross-functionally helps.
Understanding the details of customer behavior can increase sales and marketing ROI, but misusing that data can be expensive and unnecessary.
There are a lot of misconceptions about ML that can have a negative impact on one's career and reputation. Forrester and ABI Research weigh in.
Today's managers and executives need to oversee humans and machines in this age of AI and RPA, but should machines be managed as humans in a way that some suggest?
"Applications" have evolved from large monolithic structures to their decomposed equivalents. The trend will continue with some interesting twists.
Bias can result in undesirable AI outcomes. A recent DataRobot survey says organizations are most concerned about its impact on trust and their reputations.
As software delivery cycles continue to shrink, software teams have to minimize the remaining inefficiencies, regardless of where they are in the SDLC.
Keeping the lights on isn't enough anymore. In this century, the IT departmentís goals must align with those of the business.
Text analytics has been the biggest use case for NLP, but now BI and analytics vendors are adding it to their products to make them easier to use.
Companies are moving further into the cloud and undergoing data modernization. What some don't realize yet is that one strategy is better than two.
The CDO role continues to change with competitive pressures. Where are you on your journey and what do you need to do to get to the next level?
Automation isnít new to IT, but autonomous systems are, which is why IT leaders and professionals have to think about the value they're delivering, again.
AI and machine learning are becoming more commonplace, but the people using such systems may not be qualified to operate them.
Self-service may help reduce shadow IT, but it wonít eliminate it. Business-IT relationships help.
More enterprise organizations are experimenting with AI-based voice assistants to boost internal efficiencies, but it will be a while before they realize the ROI they seek.
Affective computing systems impact human emotions. They arenít necessarily able to recognize or respond to emotions well yet, but that will change.
AI is being embedded in human capital management applications, but there are many reasons they're not necessarily ripe for prime time, according to Gartner.
If you really want to understand the capabilities and limitations of machine learning, you have to get hands-on. Here's a short list of options for beginners.
Technology and business are evolving rapidly. You can contribute to your career and your organization more effectively by keeping one thing in mind.
According to industry hype, the latest emerging technology will change everything. No technology is an island, however, which is where things get interesting.
AI and machine learning are powered by lots of data, so much so that one futurist thinks today's cloud architectures aren't enough.
Many things in our modern world involve behavior modification. In fact, some organizations are setting up "nudge units," but why?
Organizations across industries are extending their infrastructures outward to enable IoT, but not all of them are able to use data as well as they'd hoped.
Not all organizations are succeeding with their digital transformation efforts. For one thing, the focus of their success metrics may be too narrow.
Most companies have IT-related risk management programs, but they need to be updated to include the nuances of AI.
Enterprise approaches to data privacy and governance need a refresh when it comes to AI because things can go wrong at scale, fast.
Continuing education is critical for IT professionals, but where should they go to get it? There are so many choices and so little time.
The roles of chief information officers (CIOs) can vary significantly. Some are strategic business leaders, others are tactical implementers, some fall somewhere in between. What they do says a lot about your company.
Non-traditional IT roles continue to emerge with new business models and technology. Is your career on track?
Headline news just hit, customers are livid, lawsuits are imminent. Whom should be held responsible when an IT error disrupts business?
Nine big tech firms are deciding your company's fate and even the fate of humanity simply because they have the most control over AI.
Fullstack Academy and Cal Poly University Extended Education recently partnered on a coding bootcamp that helps students find employment as programmers.
Municipal IT leaders manage a lot of complexity; improving government efficiency, protecting citizens, and making cities attractive places to work, live and visit.
Organizations tend to get different results with digital transformation. To realize business value, first realize that transformation isnít just about tech.
An Illinois court ruling underscores the importance of providing notice of biometric data collection and use. Violate the law and your company could be sued.
As enterprises travel on a digital transformation path, they need to stay current with analytics, but itís not a linear journey.
CES exhibitors continue their tradition of zany tech announcements, almost all of which are cool. However, some of the innovations signal trends IT should consider.
Enterprises often make the same mistakes when adopting technology, generation after generation. A PwC tech leader outlines seven considerations to keep in mind.
Organizations continue to become more metrics-driven, but when business outcomes donít turn out as expected, the lament is sometimes ďwe were measuring the wrong things.Ē If you want to measure the right things, consider these tips from Gartner's Doug Laney.
More organizations are using machine learning for competitive reasons, but their results are mixed. It turns out there are better -- and worse -- ways of approaching it. If you want to improve the outcome of your efforts in 2019, consider these points.
When building and using autonomous and intelligent systems, itís important to know theyíre behaving reliably, because if things go wrong, they can do so at scale, fast.
Robotics use cases are endless, but the overhead of developing them is stymying progress. AWS Robomaker, announced at AWS re:Invent, with lowers the barriers so developers can spend more time innovating.
Customers are constantly asking Amazon to help them accomplish more in less time at lower costs. Amazon CEO Andy Jassy said the company is listening. Hereís what AWS presented as proof.
IT continues to lose control of technologies used in the enterprise. A recent report explains just how empowered end users have become, especially when it comes to communications and collaboration technologies.
Augmented reality (AR) and virtual reality (VR) were supposed to transform user experiences, but technologies have had false and soft starts in various industries. Here's why.
Boards of directors should know that the value of their company's intangible assets probably outweighs the value of their tangible assets. However, their lack of specific knowledge about the details is resulting in lawsuits.
Organizations are using data to facilitate digital transformation, making data analytics a booming market. We highlight vendors that are addressing enterprise challenges with products for advanced analytics, machine learning, and data governance.
Agile, DevOps, Continuous Delivery and Continuous Development all help improve software delivery speed. However, as more applications and software development tools include AI, might software developers be trading trust and safety for speed?
Organizations have had a tough time trying to comply with the European Union's GDPR and now they have to consider the potential effect of the California Consumer Privacy Act (CCPA).
Amazon recently proved it isn't infallible when it shut down a human resources system that was systematically biased against women. However, there's more to the story that today's enterprise leaders should know.
Software designers and IT know the importance of a good user experience. However, accessibility by design isn't as pervasive as it should be. That will change as accessibility is integrated into more university programs.
New technologies keep on coming, but which are better to invest in now versus later? CompTIA's recently released a prioritized list of top 10 emerging technologies. We compared it with CompTIA's latest State of the Channel Report.
As more business processes move toward real-time and near-real-time, companies are finding themselves with skill shortages. One good way to fill the gaps is with "gig workers" who can be scaled up or down as required.
IT risk management is a mature topic, but it continues to evolve with technology. As rules-based systems are supplemented with self-learning systems, IT departments, risks managers and business leaders need to update their thinking.
Boards and CEOs are more tech-savvy than they once were, but they still don't always know the best questions to ask CIOs. With the push for digital transformation they need to be armed with the right questions at the right time.
2018's bullish economy is reflected in venture capital and private equity investments. Software drives the majority of deals since software powers just about everything now. Here's where the money is flowing and why.
Customer-centricity, customer journeys, data as an asset. They're easy to say, much tougher to do.
Cybersecurity is more painful to manage as technology architectures become more complex. Simplify your approach by avoiding these major security mistakes.
Organizations feel pressured to appoint chief analytics officers and chief data officers, but they may not be using those roles as effectively as they could.
AI and intelligent forms of automation are changing the ways companies operate. HR is no exception. In fact, HR leaders are spearheading automation efforts for their employers.
Companies in all industries are talking about digital transformation, but success may depend on whether the firms have world-class or ordinary IT organizations.
AI and intelligent automation are changing the ways companies compete. Members of the C-suite need to contemplate a broader spectrum of issues than technology alone.
Online catalog approaches to ecommerce are fine, but today's customers want more than the digital equivalent of a brick-and-mortar shopping experience.
Innovation is entering a new stage of maturity as a range of academic and industry organizations ponder the impacts of autonomous and intelligent systems.
Cloud natives differ from traditional companies in more ways than just their lack of legacy infrastructure: They think and operate differently.
The 2018 Interop ITX State of AI report includes some sobering statistics that will sound familiar to many business and IT leaders.
The hospitality industry wants to make travel experiences as "friction-free" as possible. Amazon and Marriott are advancing that concept by placing Amazon Echo speakers in hotel rooms so guests' desires can be fulfilled with mere utterances.
More enterprises are moving to the cloud and implementing DevOps, containers and microservices, but their efforts are falling short of expectations. A recent study from the Ponemon Institute identifies some of the core challenges they face.
While an across-the-board migration from virtual machines to containers isn't likely, there are issues developers and operations personnel should consider to ensure the best solution for the enterprise.
For all of the promise that artificial intelligence represents, a successful AI initiative still requires all of the right pieces to come together.
Boston Consulting Group and Forrester are advising clients to get smart about quantum computing and start experimenting now so they can separate hype from reality.
Disruption causes quantum shifts in industries and societal behavior by digitizing the analog, upending economic models and otherwise challenging the status quo. The disruptors differently and act differently than the incumbents. Let's look at how.
More business processes and highly-specialized tasks are being targeted for automation with the goal of making people and companies more efficient. If you haven't considered how intelligent automation will affect your career and your company, and even if you have, following are some points to consider that may help you navigate the issue.
Workforce analytics have traditionally focused on HR's use of them when their value can actually have significant overall business impacts. Realizing this, more business leaders are demanding insights into workforce dynamics to unearth insights that weren't apparent before.
The Computer Age fueled the ever-accelerating pace of innovation, but as the Digital Age matures, there are plenty of discussions about tech ethics, especially in light of AI. Emerging tech leaders are more likely to include ethics as an integral part of innovation, according to MIT's first humanist chaplain, Greg Epstein. Here's why.
As AI is woven deeper into different types of software and business processes, the success of it, particularly from customer experience and personalization standpoints, depends on its ability to recognize emotion and act accordingly. Will machines be able to achieve artificial empathy? Have they already? Following are some of the challenges and opportunities.
Las Vegas may well become the next high-tech hotbed as more IT talent and related investment flow into the city. On and off The Strip, there are all kinds of opportunities to cash in on digital transformation, from gaming to the maker movement and beyond. You may enjoy life more, too. Here's why.
Cognitive computing, AI, machine learning, and deep learning are often used to describe the same thing, when they actually differ. We explain what the differences are so you can better understand how the pieces fit together.
Alexa, Waze, apps. Citizens are getting more tech savvy and city governments are struggling to keep up. North Carolina's Town of Cary has an award-winning strategy, though. We reveal what that is.
Technology innovation is accelerating and so are the impacts of technology on society. As machine intelligence gets baked into more products and services, as more human tasks become automated, and as more industries are disrupted, the tech industry needs to think differently. Here's why.
Digital transformation is taking off across industries, although not all sectors are maturing at the same pace. A new Infosys report reveals the details of the key technology investments, goals and outcomes.
Organizations consider data one of their most valuable assets, but exactly, how much is that data worth? Most business leaders can't answer the question yet. But venture capitalists, financial analysts and board members increasingly want to know.
Plenty of companies have plenty of data and plenty of analytics tools, but they fall short when it comes to converting analytics results into action.
Consider these four barriers to success when moving forward with your data analytics initiative.
Enterprise software development teams have historically had trouble ensuring the code that runs well on a developer's machine also runs well in production. DevOps has promoted more collaboration between developers and IT operations. Data scientists and data science teams face similar challenges, which DevOps concepts can help address.
Alternative and virtual realities provide organizations with new opportunities to reimagine product demos, employee training and more. As the systems collect and generate data, there are opportunities to use the new streams in innovative ways.
Alexa's popularity among consumers serves as a wake-up call for businesses. Eventually, voice interfaces will replace keyboards, taps and swipes, but organizations must be wary of approaching voice interface design the same way they've approached web and mobile design. Before you begin, consider these points.
Some enterprises struggle to drive business value from data science efforts because the business and data scientists are not communicating or collaborating well. Here are five things you can do to improve the cross-functional relationships and ROI.
There are best practices for approaching chatbots and virtual assistants as organizations move to a scenario where tasks happen transparently behind natural language interfaces. We explain some of the opportunities and pitfalls.
Data storytelling can help organizations convey the message of data to customers, employees, shareholders, and other audiences. Here are a few ways to do it more effectively.
Demand for SaaS software continues to grow, but procurement is often short-sighted. Think past today because integration and governance are more important than pricing.
When most people think about innovation, they think of companies like Amazon, Facebook, Apple, and Google because those companies appear to have some kind of magic that other organizations lack. If your company wants to make lightning strike repeatedly, consider these points.
Your behavior online and in stores gives retailers a glimpse into what you want and how to sell it to you. Here's what's coming in retail data and analytics.
Everyone's talking about AI, but many companies have trouble getting their efforts off the ground. In a recent survey and brief, EY pinpoints the challenges and opportunities.
As you look back on 2017, we're sure there are improvements you would want to make. Now, as we head into 2018, what changes are you planning?
It's not surprising that men and women value different things in the workplace, but employers aren't necessarily paying attention to the details. Going into 2018, here are a few things you should know.
Machine learning isn't as widely adopted as some may think, mainly because there are serious barriers to adoption. Researchers are making progress in reducing those barriers.
Is the enterprise itself getting in the way of achieving results from analytics insights? Here's a closer look at what organizations can do to get out of the way of analysts.