Profile of Lisa MorganFreelance Writer
News & Commentary Posts: 166
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
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.
In an era when organizations have to move forward quickly with innovative -- often expensive -- tech initiatives, CIOs and CFOs may have to form a partnership.
Analytics is spreading out to more departments that want to optimize their operations, but that may give users a false sense of freedom from IT. Here are some dynamics currently affecting IT.
HR analytics aren't mainstream yet, but they're gaining traction because human capital management is a competitive issue. From recruiting to employee performance and overall HR operations, analytics will have an increasing impact on companies and individuals.
Organizations are collecting more data from devices, whether in industrial settings, retail operations, or other installations. Here's a closer look at what they are doing with all that data.
Businesses are updating their approaches to data analytics as the competitive landscape changes. We explore the trends, technologies, and vendors leading the way.
Digital transformation requires fundamental changes to the business. Are you ready yet? If you're not thinking about how the following 5 trends affect your business you need to start doing so now.
As GDPR and its hefty fines loom, it is time for organizations to really look at their privacy policies. You can't just cut and paste the language from a template anymore.
Faster, better, potentially dangerous. Quantum computers will push way past the boundaries of traditional computers, but to what ends? We explore some of the possibilities.
Cross-functional analytics can benefit businesses by replicating successful programs. Here are some common challenges you should know as you formulate a winning strategy.
Biased data can lead to bad decisions. Most business leaders aren't aware of the problem just yet, but they need to be because they're ultimately responsible.
InformationWeek readers know a lot about technology. Many studied computer history as part of their majors and yet, even PhDs would likely flunk a test about African-American contributions to the computer industry. Here's why.
If your data is failing to persuade executives, maybe it's not the data that is the problem. Here's how to change your approach to fit the audience.
Businesses in virtually all industries are using or experimenting with AI, but do they really understand the ultimate impact AI will have on their businesses? Not completely, according to a new survey by Genpact and FORTUNE Knowledge Group.
Looking to get started in analytics or data science? Are you better off pursuing a degree or getting a certificate? Here's a closer look at the different paths available to aspiring data professionals.
Equifax blamed its recent high-profile breach on the Apache Struts Web Framework. As software delivery cycles shrink, developers have to rely on more third-party components, libraries and frameworks. When they do, what are their liabilities and responsibilities?
Drone mapping data can dramatically impact the profitability of certain businesses. Should you include it in your business app? Consider these points.
Analytics ROI often falls short because businesses overlook important parts of the process.
Are you looking to add more self-service options for business users? Here's how one company is updating its business intelligence program with Agile methodologies to open the doors to better user insights.
AI and automation are being combined in different ways to complete tasks more efficiently than humans. Every business will be impacted by intelligent automation sooner than may be apparent, so the time to think about it is now.
Insurance agencies struggle to reach new prospects. To adapt to changing markets, they must overcome challenges with data integration, data quality, and systems fragmentation.
Most organizations that sell to consumers aspire to gaining a 360-degree view of customers. But is that really attainable?
If you're having trouble finding and keeping IT personnel, you're not alone. One problem might be that you don't understand what they want, as a new Manpower study suggests.
As summer vacation season is in full swing, we take a look at the state of analytics in the hotel and hospitality industry.
Frequent flyer programs have evolved over the years. So has the amount of data available. Here's a look at where we stand today.
More hiring managers and HR pros are using social media to make decisions about candidates, but how wise is it? Could the use of social media for hiring be dangerous in its own way?
For PG&E a utility pole inspection app offers much more than a chance to replace paper.
Some organizations race into data-driven transformation. Others want to get everything "right" first. There's an optimal balance between the two.
Companies doing analytics 20 years ago enjoyed a competitive advantage. Today, if you are not doing analytics, you are falling behind.
Modeling artificial intelligence on the human brain is modeling it on a flawed model.
If you're just getting started with analytics, you can avoid a lot of headaches by learning from the experts. We've tapped a few who have great practical advice.
Here's a tale of how two cities are managing vast quantities of data and using data analytics to improve citizens' lives.
Enterprises and jobs are changing fast as more tasks are automated with increasing levels of machine intelligence. Automation displaced manufacturing jobs, but it also enabled the creation of new businesses and career opportunities. Will knowledge workers and their employers adapt fast enough?
DevOps has been hyped for a decade, but many still don't understand what it is, let alone what it does. There are many potholes on the road to DevOps. We explain how to avoid some of them.
Artificial intelligence and machine learning are gaining enterprise attention. Here's an overview of some essential terms you can share with your team and executives.
Change is the only constant, which IT professionals know all too well. However, as technology changes, their departments must too. Some IT departments are in trouble, big trouble if they don't do something fast. We explain a few reasons why.
Are you ready for AI and machine learning? Here's an overview of three use cases to give you a flavor of just what is possible.
More organizations have embraced DevOps to deliver higher quality software faster. Meanwhile, DevOps itself has evolved. We explain where DevOps is today and where it's is headed.
Professional sports leagues the NFL, NHL, NBA, and MLB are all leveraging analytics and IoT in their efforts to improve the games. Here's an overview.
A lot of firms start out as virtual companies, but as they grow, they move into office space. It turns out there are advantages to staying virtual, however. We explain some of them.
How the National Hockey League is using sensors and predictive analytics to learn more about fans and game play.
Data governance policies are full of holes that can become expensive pitfalls. We explain some of the stumbling blocks.
Everybody knows how important analytics is to remaining competitive. Where does your company and industry stand in terms of advanced analytics maturity?
Cybersecurity analytics must balance the lessons of user behavior with the need to maintain service levels for workers while always assuming that the intruder is already inside the network.
New technologies and solutions are compelling, so compelling that little thought may go into what will make them successful. Solutions architects can help, but they need help from IT and the business. Thought leaders, including an Interop ITX speaker, share advice.
Agility is the name of the game for today's IT organizations, but keeping up with the rapid pace of change is difficult. We explain what's holding IT back.
Marketing analytics has evolved with the increase in volumes of customer data. But can this increase in data really help us get a full view of the consumers?
Cyber security continues to be an arms race as organizations race to protect against new kinds of attacks. Here's how analytics IS making a difference.
There has been plenty of talk about the need for a chief analytics officer or chief data officer. But do you ever wonder what they do for a living?
Users want answers to burning questions, but IT and the data team can't tackle them all at once. Self-service analytics help organizations triage problem-solving by providing many of the insights business users need.
Smart people and the best technology aren't enough to drive a data-driven culture. It's all about people and collaboration, which is easier said than done. If you're serious about affecting change, consider these best practices.
For a company, product, or service to be disruptive, it takes more than technology. Analytics can point you to your opportunities.
GPU-accelerated databases aren't new, and they're not all that popular, but that will likely change over time. Here are some of Kinetica's latest improvements and why that matters to big pharma company GSK.
People in business and tech love to use the latest, popular buzzwords. "Disrupter" is one of them.†But IS your company really leveraging analytics disruptive capabilities?
Analytics is popping up in more functional areas of businesses, outside of IT's control. Like BYOB, the trend is inevitable. How will your organization manage it?
Data is the new oil. Those that figure out how to use it more effectively than their competitors are realizing significant, strategic benefits. But what's so unique about data-first companies? Technology? People? Culture? It turns out, there's more than meets the eye.
Those website recommendations engines sometimes can be just what the consumer needs to make a decision. Then again, sometimes those recommendations are way off base.
Ever noticed that some recommendations from consumer websites tend to be a bit off base? Lisa Morgan takes a look at why those engines get confused.
Analytics is being embedded in all kinds of software which suggests a major shift is on the horizon. How we think about analytics will change and so will our use of analytics. We explain why.
Analytics are taking on a lead role in all phases of the healthcare system. Those personal fitness devices? Their value is in what they say about us, not the data itself.
Analytics are taking on a lead role in all phases of the healthcare system. Those personal fitness devices? Their value is in what they say about us, not the data itself.
Applications and devices that sense human emotions are hitting the tech market, focused on what customers and other users are feeling, and how the device or a person should respond.
Visualization or storytelling for delivering data results to business users? Well, maybe you need to let both methods work together to do the job.
Looking for a unicorn? Get in line. Actual data scientists are in high demand, and there's not enough of them to go around. If you want to identify the right talent, consider these tips.
It's time to accept the fact that so much of the data we see is biased, whether intentionally OR not. so what can you do about it?
It's a new world out there when it comes to analytics, and the old IF/THEN model is no longer a sure thing.
IoT devices are entering the workplace in all shapes and sizes, from workers wearing smartwatches to industrial sensors such as soil monitors. The data pouring in may be so overwhelming it's unclear what should be done with it, why, and what the risks might be. Here are a few ways to navigate the maze.
Part of any analysis has to be a sanity check to understand where the data may reflect any number of different types of bias.
Applying machine learning and artificial intelligence to your decision-making can help your business stay competitive. But a lot can go wrong along the way. Without the proper checks and balances, machine learning efforts can spiral out of control, exposing your organization to risks. Here are 13 pitfalls to avoid.
Businesses use bots to engage with customers, online and via social media, because they're a cost-effective way to respond instantly to simple queries. As the technology improves, bots are finding their way into more use-cases where human judgment and effort were traditionally required. Are bots right for your business? Here are 10 examples to help you decide.
Even as they aspire to be data driven, organizations are failing to align their vision with execution. Pitfalls lurk everywhere. We've uncovered 10 of the most common culprits.
A PwC survey highlights the confusion and resistance that surround analytics initiatives in the executive offices.
Regardless of how much data your company has -- and how much your business leaders are asking for -- you're likely missing some hidden gems. Here are 12 examples of what you might be overlooking, and why it matters to IT professionals, and to your business at large.
Companies competing on data need the right skill sets and mindsets in place to succeed over the long term. While more individuals are analyzing data as part of their jobs, their ability to do so varies greatly, even among peers. We've identified 10 key traits of an analytical mind, and explain what to look for in your next hire and what skills to cultivate in your own career.
The key to implementing real-time analytics is understanding what "real-time" means for your organization and your application.
As organizations look to stay competitive by expanding their use of real-time analytics, implementation becomes a challenge. Finding options to effectively serve your company over the long term is often more difficult than it appears. We've identified 12 common obstacles you'll want to avoid as your company pursues real-time analytics.
Organizations aspiring to become data-driven need to take a close look at their HR practices. If your company's hiring and retention standards aren't keeping up with the times, you may be losing valuable job candidates and employees. To minimize the pitfalls of building a data-savvy workforce, consider these tips.
A CompTIA survey shows how organizations would like to expand their analytics initiative, but there are some areas where they might want to simply do analytics better in the right spots.
Somewhere between blind faith and skepticism is the world of prescriptive analytics. Here, machine-generated action items and potential outcomes meet human decision-making. Finding the right balance between algorithms and common sense can be tricky, so consider these tips.