Archive for the ‘Business Intelligence’ Category
Unexpected election results around the world have given the media the chance to talk about their favourite topic: themselves! With their experience running polls, the media are very good at predicting the winner out of two established parties or candidates but are periodically blindsided by outsiders or choices that break with convention. In most cases, there were plenty of warnings but it takes hindsight to make experts of us all.
Surprises are coming as thick and fast in business as they are in politics and similarly there are just as many who get them right with perfect hindsight! The same polling and data issues apply to navigating the economy as they do to predicting electoral trends.
The Oxford Dictionary picked “post-truth” as their 2016 word of the year. The term refers to the selective use of facts to support a particular view of the world or narrative. Many are arguing that the surprises we are seeing today are unique to the era we live in. The reality is that the selective use of data has long been a problem, but the information age makes it more common than ever before.
For evidence that poor use of data has led to past surprises, it worth going way back to 1936 when a prominent US publication called The Literary Digest invested in arguably the largest poll of the time. The Literary Digest used their huge sample of more than two million voters to predict the Republican challenger would easily beat the incumbent, President Roosevelt. After Roosevelt won convincingly, The Literary Digest’s demise came shortly thereafter.
As humans, we look for patterns, but are guilty of spotting patterns first in data that validates what we already know. This is “confirmation bias” where we overemphasise a select few facts. In the case of political polls, the individuals or questions picked often reinforces a set of assumptions by those who are doing the polling.
This is as true within organisations as it is in the public arena. Information overload means that we have to filter much more than ever before. With Big Data, we are filtering using algorithms that increasingly depend on Artificial Intelligence (AI).
AI needs to be trained (another word for programming without programmers) on datasets that are chosen by us, leaving open exactly the same confirmation bias issues that have led the media astray. AI can’t make a “cognitive leap” to look beyond the world that the data it was trained on describes (see Your insight might protect your job).
This is a huge business opportunity. Far from seeing an explosion of “earn while you sleep” business models, there is more demand than ever for services that include more human intervention. Amazon Mechanical Turk is one such example where tasks such as categorising photos are farmed out to an army of contractors. Of course, working for the machines in this sort of model is also a path to low paid work, hardly the future that we would hope for the next generation.
The real opportunity in Big Data, even with its automated filtering, is the training and development of a new breed of professionals who will curate the data used to train the AI. Only humans can identify the surprises as they emerge and challenge the choice of data used for analysis.
Information overload is tempting organisations to filter available data, only to be blindsided by sudden moves in sales, inventory or costs. With hindsight, most of these surprises should have been predicted. More and more organisations are challenging the post-truth habits that many professionals have fallen into, broadening the data they look at, changing the business narratives and creating new opportunities as a result.
At the time of writing, automated search engines are under threat of a ban by advertisers sick of their promotions sitting alongside objectionable content. At the turn of the century human curated search lost out in the battle with automation, but the war may not be over yet. As the might of advertising revenue finds voice, demanding something better than automated algorithms can provide, it may be that earlier models may emerge again.
It is possible that the future is more human curation and less automation.
South of Iran, east of Saudi Arabia, and north of Oman is Dubai, an emirate (political territory) of the U.A.E. (the United Arab Emirates). In addition to being the location of Burj Khalifa (“Khalifa Tower” in English), the current tallest building in the world, Dubai also hosts an international airport unlike any other. The Dubai International Airport (DXB) holds the record for the world’s busiest airport. This “mega-airport” expects to serve a staggering 120 million customers this year. Compare that to the measly 94 million passengers that the Hartsfield-Jackson Atlanta International Airport in Georgia handled in 2013, and the 72 million that passed through London-Heathrow Airport in the United Kingdom in 2014.
Any traveler who has missed a connecting flight because the gates were too far apart, or ended up standing in the wrong line because either the writing on the boarding pass or the announcements over the intercom were in a different language has to wonder how an airport of any size could handle 120 million people — successfully.
When asked about the likelihood of issues such as people getting lost and luggage being left behind, Dubai Airports CEO Paul Griffiths explained at the ATIS (Air Transport Industry Summit) that the efficient and intelligent analysis of real-time big data will keep the airport running as secure as a Boeing 717. “We keep increasing the size of the pipe but actually what our passengers want is to spend less time going through (the) process,” Griffiths said in an interview with Gulf Business. “This is where technology comes to the fore with more efficient operations. It’s about the quality of the personalized customer experience where people don’t have to walk more than 500 meters. That is the design goal and technology is central to that.”
The big data that Griffiths referred to is a massive collection of information about distances between airport gates, baggage handling efficiency, and flight durations among other statistics. All of this information interpreted by “intelligent systems” will transform DBX and airports like it in three ways:
1. Increased Efficiency. The Dubai International Airport is an exception to the rule that larger airports are more difficult to traverse. Real-time calculations will allow the air traffic control tower to guide airplanes to terminals close to the connecting flights each passenger requires.
2. Improved Customer Experience. Everything’s getting smarter, including the boarding passes. Instead of printing everything only in Arabic and English, the analysis of big data information such as a person’s native language will result in better, readable, personalized boarding passes tailored to each individual.
3. Cost Reduction. An increase in customers, plus increased efficiency, plus an improved customer experience means that Dubai’s profits will soar. When the statistics are examined a year from now undoubtedly the money saved by not having to reroute passengers and pay for missed flights and hotel stays will be the final proof that big data analytics tools are transformative.
“I believe that technology will take center stage in the future of aviation,” Griffiths said. “Airports, for too long, have been considered just infrastructure businesses. Actually, we have a vital role to play in enabling a level of customer service that certain airlines have already got right in the air but some airports have let them down with on the ground.”
Most companies by now understand the inherent value found in big data. With more information at their fingertips, they can make better decisions regarding their businesses. That’s what makes the collection and analysis of big data so important today. Any company that doesn’t see the advantages that big data brings may quickly find themselves falling behind their competitors. To benefit even more from big data, many companies are employing big data strategies. They see that it is not enough to simply have the data at hand; it must be utilized in the most effective manner to maximize its potential. Coming up with the best big data strategy, however, can be difficult, especially since every organization has different needs, goals, and resources. When creating a big data strategy, it’s important for companies to consider several main issues that can greatly affect its implementation.
When first developing a big data strategy, businesses will need to look at the current company culture and change it if necessary. This essentially means to encourage employees throughout the whole organization to get into the spirit of embracing big data. That includes people on the business side of things along with those in the IT department. Big data can change the way things are done, and those who are resistant to those changes could be holding the company back. For that reason, they should be encouraged to be more open about the effect of big data and ready to accept any changes that come about. Organizations should also encourage their employees to be creative with their big data solutions, basically fostering an atmosphere of experimentation while being willing to take more risks.
As valuable as big data can be, simply collecting it for the sake of collecting big data will often result in failure. Every big data strategy needs to account for specific business objectives and goals. By identifying precisely what they want to do with their data, companies can enact a strategy that drives toward that single objective. This makes the strategy more effective, allowing organizations to avoid wasting money and resources on efforts that won’t benefit the company. Knowing the business objectives of a big data strategy also helps companies identify what data sources to focus on and what sources to steer clear from.
It’s the value that big data brings to an organization that makes it so crucial to properly use it. When creating a big data strategy, businesses need to make sure they view big data as a company-wide asset, one which everyone can use and take advantage of. Too often big data is seen as something meant solely for the IT department, but it can, in fact, benefit the organization as a whole. Big data shouldn’t be exclusive to only one group within a company. On the contrary, the more departments and groups can use it, the more valuable it becomes. That’s why big data strategies need a bigger vision for how data can be used, looking ahead to the long-term and avoiding narrowly-defined plans. This allows companies to dedicate more money and resources toward using big data, which helps them to innovate and use it to create new opportunities.
Another point all organizations need to consider is the kind of talent present in their companies. Data scientists are sought by businesses the world over because they can provide a significant boost to accomplishing established big data business goals. Data scientists are different from data analysts since they can actually build new data models, whereas analysts can only use models that have been pre-made. As part of a big data strategy, the roles and responsibilities of data scientists need to be properly defined, giving them the opportunity to help the organization achieve the stated business objectives. Finding a good data scientist with skills involving big data platforms and ad hoc analysis that are appropriate for the industry can be difficult with demand so high, but the value they can add is well worth it.
An organized and thoughtful big data strategy can often mean the difference between successful use of big data and a lot of wasted time, effort, and resources. Companies have a number of key considerations to account for when crafting their own strategies, but with the right mindset, they’ll know they have the right plans in place. Only then can they truly gain value from big data and propel their businesses forward.
Big data is where it’s at. At least, that’s what we’ve been told. So it should come as no surprise that businesses are busy imagining ways they can take advantage of big data analytics to grow their companies. Many of these uses are fairly well documented, like improving marketing efforts, or gaining a better understanding of their customers, or even figuring out better ways to detect and prevent fraud. The most common big data use cases have become an important part of industries the world over, but big data can be used for much more than that. In fact, many companies out there have come up with creative and unusual uses for big data analytics, showing just how versatile and helpful big data can be.
1. Parking Lot Analytics
Every business is trying to gauge how well they are doing, and big data is an important part of that. Perhaps some study the data that comes from their websites, or others look at how effective their marketing campaigns are. But can businesses measure their success by studying their parking lots? One startup is doing that very thing. Using satellite imagery and machine learning techniques, Orbital Insight is working with dozens of retail chains to analyze parking lots. From this data, the startup says it can assess the performance of each company without needing further information. Their algorithm uses deep learning to delve into the numbers and find unique insights.
2. Dating Driven By Data
Big data is changing the way people date. Many dating websites, like eHarmony, use the data they compile on their users to come up with better matches, increasing the odds they’ll find someone they’re compatible with. With open source tools like Hadoop, dating sites can gain detailed data on users through answers to personal questions as well as through behaviors and actions taken on the site. As dating sites collect more data on their customers, they’ll be able to more accurately predict who matches well with whom.
3. Data at the Australian Open
Many sports have adopted big data to get a better understanding of their respective games, but big data is also being used in a business sense in the sports world. The Australian Open relies heavily on big data during the tournament in response to the demands of tennis fans around the world. With big data, they can optimize tournament schedules and analyze information like social media conversations and player popularity. From there, the data is used to predict viewing demands on the tournament’s website, helping organizers determine how much computing power they need at any given time.
4. Dynamic Ticket Pricing
The NFL is also using big data analytics to boost their business. While it might seem like the NFL doesn’t need help in this regard, they still want to use big data to increase ticket sales. The goal is to institute variable ticket pricing, which has already been implemented by some teams. Using big data, NFL teams can determine the level of demand for specific games based on factors like where it falls in the season, who the opponent is, and how well the home team is playing. If it’s determined demand is high, ticket prices will go up. If demand is predicted to be low, prices will go down, hopefully increasing sales. With dynamic ticket pricing, fans wouldn’t have to pay high prices for games that are in low demand, creating more interest in the product, especially if a team is struggling.
5. Ski Resorts and Big Data
Many ski resorts are truly embracing the possibilities of big data. This is done through basic ideas, like saving rental information, but it can also be used to prevent ticket fraud, which can take out a good chunk of revenue. Most impressively is how big data is used to increase customer engagement through the use of gamification. With Radio Frequency Identification (RFID) systems, resorts can actually track skiers, compiling stats like number of runs made, number of feet skied, and how often they get to the slopes. This data can be accessed on a resort’s website where skiers can compete with their friends, earning better rankings and rewards which encourage them to spend more time on the slopes.
These cases show that with a bit of creative thinking, big data can help businesses in more ways than one. As companies become more familiar working with big data, it’s easy to see how unique and innovative solutions will likely become the norm. As unusual as some of these uses may be, they may represent only the beginning of many unique ventures in the future.
There’s nothing more punk-rock than the sort of DIY ethics currently fueling open-source communities. The general subversiveness combined with an apparent twice-a-week minimum black t-shirt rule among developers may make the open source scene look kind of like a cool-guy/girl clique, at least from an outsider’s perspective.
Everybody is rebelling against something, right?
In the cloud computing ecosystem the basic theme is rebellion against failure, according to whatever that means to whomever is considering the question. And within that question is the other major decision; whether the given needs call for an open-source, or proprietary architecture. So let’s take a closer look at what the major differences between those two models mean for businesses.
Charging for Software
Generally, open source models are free and won’t charge for the use of software. Proprietary models may offer free packages at first, but ultimately always end up costing the customer. Many updates to proprietary software are free, but significant upgrades and the ability to add new packages often comes with a fee. Charges can also come in the form of a per-user fee. Open source options are based more on the development of a community. They take direction from the demands of the market and tend to start with a small collection of developers and users. Successful projects are quickly picked up, while others are left to languish in obscurity.
Vendor lock-ins occur with proprietary software. This means that the website and software used with a proprietary vendor can’t be taken to another provider. It also limits the ability to use other providers with the knowledge to use a particular product. In contrast, open source products are more flexible and allow users to move between different systems freely. Open source cloud computing offers a greater range of compatibility between several different products. Typically, if a proprietary solution goes out of business the end-user is left with an unusable product. With open source projects, there is usually another project or fork that can take off where the old one left off.
Modifying System Code
Proprietary software doesn’t allow the manipulation of the source code. Even simple modifications to change styling or add features are not permitted with proprietary software. This can be beneficial for users who are happy with a set of features that is completely managed by one company. For those who like to tinker and adjust software to their needs, it may not be an ideal solution. Open source options allow for modifications and a company can even create an entire fork based off the existing software. When a feature doesn’t exist within an open source application, a developer can be hired to incorporate the feature into the product.
Licensing and Hosting Costs
Using proprietary software isn’t for the faint of heart or light of wallet. Licensing and hosting fees are often higher with proprietary software. By using open source options, users can avoid having to pay operating system costs, and per-product fees to use the software. This provides more flexibility to those who run open source platforms. A new software package or feature can be quickly added on to an existing installation without the need to purchase a license. Additionally, proprietary software requires the use of commercial databases, which further add to the total cost of operation.
Product documentation is often more involved and useful with open source software. The reason for this is the large communities that often follow and support open source projects. Help documentation for proprietary software is often only surface level. This is partially due to the service-based nature of proprietary software. It’s more profitable when consumers have to rely on the company for support and technical services. However, this can negatively impact business if an update goes wrong and technical support can’t immediately correct the issue. Open source applications come with substantial documentation that is typically updated with each product release and freely available online.
Security and Performance Considerations
When you have an entire community of developers poking and prodding at an application, you tend to have better security. Many of the features that are put into proprietary software are designed to keep the software from being modified. This adds bloat to the code and prevents the option for a light and lean product. Additionally, excess code leaves more room for security and stability flaws. With open source software, there are many more eyes looking at the code and fixes tend to come in much more quickly than with proprietary software. Stability and advanced threat defense tends to be tighter with open source applications, as long as users keep their software updated. Out of date applications are just as vulnerable to hacking and infiltration as proprietary systems.
Open source and proprietary cloud services both aim to provide end-users with reliable software. Some users prefer the backing of a large company like Amazon or Microsoft, with a tailored list of compatible programs and services. Others prefer the interoperability and flexibility of open source alternatives like OpenStack or Eucalyptus. It’s not necessarily an issue of right or wrong per se. It just depends what the user’s specific needs are. For some open source software is the obvious choice, while those who want more predictably managed solutions may find proprietary solutions the ideal choice.
Back in the analog days, designers used hands-on tools to bring their creations to light. But in this day and age of information and advanced technology big data and analytics tools are transforming the world of design as never before.
In a November 2014 article on wired.com Paul Papas, “the Global Leader for the IBM’s Interactive Experience practice, a next-generation digital agency, consultancy, and systems integrator,” discusses the revolutionizing power of big data in all facets and fields of design. Compiled from the author’s views and insights is this list of 5 ways big data is transforming the world of design.
1. Creativity – To illustrate how far design has come in the digital age, Papas has us first picture an architect at a drafting table laboring over a blueprint, or an auto designer modeling next year’s car out of clay. “With some variation,” says Papas, “those were creative tools that designers, architects and artists relied on to render their inspirations, refine their concepts, and finalize them into market-ready products.” While those tools may have some application today, Papas points out how high-performance computing, “has radically transformed the creative process in pharma, automotive, and government R&D.” Thanks to computer modeling and simulation capabilities, designers can render, test, refine and prove products in a virtual world before they go into production.
2. Innovation – “Today, data continues to affect the design of products in new and innovative ways,” says Papas. While no specific examples are mentioned in the article, Google’s autonomous cars controlled by real-time big data analytics comes to mind as an example of innovation in the automobile industry. Smartphones, which in actuality are powerful portable computers that in many ways have transformed our lives, are another example of innovation made possible by big data. According to Papas, “What’s truly revolutionary is how marketers and other business leaders are using data in the design of something much more intimate and essential — the personalized experiences that millions of individuals will have with their products, services or brands.” Which brings us to…
3. Experience Design – In the analog days the goal of designers was to create products that seamlessly combined form and function. In the era of big data, that model has been upgraded to what is being referred to as “experience design.” As Papas explains, when you pull “experience design” apart, “you have equal parts the design of beautiful, elegant interfaces and the creation of irresistible experiences that are smart, individualized, trusted and valuable — all 100 percent dependent on the astute use of data.” According to Papas, today’s businesses are defining their agendas by two forces—“massively available information and new models of individual engagement.” So powerful are these two forces for business that Papas says, “experience design is rapidly becoming a de facto element in contemporary business strategy.”
4. Behavioral Design – Not unlike the clay automobile designers use to mold and shape basic designs, big data is giving rise to a new medium, human behavior. Described by Papas as, “a harder trick to pull off than modeling metal,” designers are using human behavior to, “learn and modify designs before they’re implemented, as insight from data gives companies the ability to understand context, and learn and evolve with the consumer and create unique, reciprocal experiences.”
As evidence of the power of behavioral design, Papas cites Brown University’s dilemma of either upgrading its existing engineering school or moving the entire engineering department off campus to a larger, potentially better facility. “Through a deep analysis of a hodgepodge of data — from faculty collaboration patterns to course enrollments,” says Papas, “Brown discovered patterns showing an enormous amount of cross-fertilization between the school’s communities.” Based on the insights obtained from behavioral data that showed how the off- campus option would “negatively affect students, faculty collaboration and research dollars,” the university chose not to make the move.
5. The “Market of One” – Thanks to big data analytics, Papas says that, “the long-anticipated ability to really find, know and engage the proverbial “market of one” is finally at hand.” While not mentioned in the article, images of consumers being engaged on their mobile devices by companies in relevant and meaningful ways—in real-time and in context—serve as an example of how marketers are able to reach the once elusive “market of one.”
Big data is truly transforming the world of design.
Going forward, Papas predicts that the powerful, data-intensive tools that designers now have at their disposal will continue to “render the designs and create the experiences that will unlock the next great level of possibility and value for enterprise in every industry.”
You see them everywhere nowadays, whether you’re walking down the street, riding the bus, attending a sporting event, or eating at a restaurant. Smartphones have become a common sight, providing an easy and convenient way to communicate with family and friends through email, texting, and social media. The number of functions smartphones can possess is staggering, so it’s no wonder they’ve become such a major fixture in our lives. As mobile devices creep into everyday life, there’s one place where they might not be entirely welcome: the office. Smartphones have entered the workplace, and with workers performing their jobs on the road more frequently, they can often be the one connection they need to keep up with their workloads. But more and more businesses are looking at smartphones as more of a nuisance than an advantage. Now, some organizations are even considering banning smartphones and similar technology.
If company leaders want to look for reasons to ban personal smartphones and tablets in the office, they don’t have to look far. A recent study backs up many concerns and worries generated by the infiltration of smartphones in work environments. According to the study, a whopping 95 percent of employees say they’re distracted during the workday. While the first source of distraction is coworkers, 45 percent did say that they were distracted by technology like text messages and personal emails. People can become addicted to their smartphones, and it doesn’t take much for an employee to become sucked into their Facebook newsfeed.
In addition to the worries over distractions and missing productivity, business leaders also have significant fears over the security risks that might increase when people use their own devices in the workplace. Many businesses have actually encouraged people to bring personal mobile devices to work with bring your own device (BYOD) policies, but the result has been an increase in the volume and severity of security incidents. When workers are part of a BYOD policy, that means they’ll connect their devices to the business network. Should the device have malware or other damaging code on it, the network and other systems–along with other devices–may become infected as well, fully compromising IT security. Plus, there’s always the fear that an employee’s device will get lost or stolen, and if it has sensitive company data on it, the company may suffer damage.
So worries over distractions and security risks seem to show the need to ban smartphones and other mobile devices from the workplace, but that would ignore the benefits that come from bringing this technology. While they may cause distractions, smartphones have also been shown to increase productivity among employees. That’s one of the reasons workers like to use their own devices as well as a reason so many businesses have adopted BYOD in the first place. Employees can get more work done since they are already familiar with their devices and know how best to use them. BYOD policies can also save companies money since workers would be responsible for the costs of those devices.
There’s also the question of whether a ban on smartphones is even effective. While it’s true that some bans in Finland have been successful, tech bans in other parts of the world are more of a mixed bag. Research shows that around 70 percent of workers already bring their personal devices to work every day. Of those who do so, about 20 percent use personal smartphones that are restricted by their employers. As mentioned before, people grow attached to their smartphones, and many will likely bring them in even if told not to. Workers are also increasingly reliant on their devices for doing work-related tasks. Apps and other features have been developed with businesses in mind, making smartphones a valuable tool in the workplace. Many of the distractions found on smartphones (email, social media) can also be accessed through normal desktop computers as well. In short, tech bans might seem like a good idea at first, but they may prove ineffective in the long run.
Smartphones can be much more than a distraction or security risk. While businesses may be understandably cautious about mobile devices, their employees can get more done in less time. Ultimately, tech bans don’t accomplish what they set out to do, so a more active approach like monitoring mobile activity may be helpful in keeping workers on task and minimizing security threats. A few common sense rules and guidelines can go a long way to getting the most out of smartphones, which effectively avoids an outright ban.
Selecting a big data solution can be tricky at times with the different options available for enterprises. Deciding between a cloud big data analytics provider and an on-premise Hadoop solution comes down to recognizing the pros and cons of both options and how they will affect the bottom line.
Pros of On-premise Hadoop Solutions
As with any on-premise solution, on-premise Hadoop allows businesses to have complete control over their Hadoop cluster and perhaps more importantly their data. While the cloud is getting more accessible to industries facing heavy security and compliance regulations, some companies may prefer to keep everything in-house. On-premise Hadoop also avoids the complexity or potential log-in of vendor SLA agreements.
Cons of On-premise Hadoop solutions
Investing in Hadoop hardware can prove to be expensive depending on how it’s being used. Despite using low-cost commodity servers, extending to thousands of nodes can result in significant costs requiring attention to problems typically uncommon but become increase in frequency with a large number of servers.
Hadoop is also complex to maintain and manage. Companies will have to dedicate certain employees to deploying clusters every time a query is made. Once a cluster’s capacity is reached, it will also eat up resources adding additional nodes to th ecluster.
Pros of Cloud providers
One of the pros of using a cloud provider versus an on-premise Hadoop solution is the scalable nature of a cloud provider. Cloud platforms allow for total scalability allowing companies to access unlimited storage on demand. Enterprises can easily upscale or downscale depending on the IT requirements allowing business growth to be supported without expensive changes to your existing IT systems.
Another pro of using a cloud provider versus an on-premise Hadoop solution is the flexibility of solutions available both in and out of the workplace. Employees can more easily access files using devices like smartphones and laptops. Organizations can simultaneously share documents and other files over the cloud while supporting both internal and external collaboration.
Cons of Cloud Providers
Due to the massive growth of cloud computing, organizations are starting to rely on managed data centers run by cloud experts trained in maintaining and scaling shared, private and hybrid Clouds. Companies who do not have their own data scientists will have to make changes to their current cloud computing structure to meet their evolving data needs.
A risk organizations make with cloud providers is relying on the provider’s level of security and responsiveness to technical issues. Though rare, the cloud provider may have downtime that impacts a businesses’ ability to run queries or meet the customer’s demand for queries.
The path businesses take will depend on individual needs and circumstances as there are pros and cons to each type of solution. As big data moves mainstream, you will want to consider how you will take advantage of this resource.
With the holidays upon us, most businesses are dealing with what is usually their busiest time of the year. It’s a period of excitement and increased sales, but it’s also a time of worry and concern. In the wake of the recent data breaches at large retailers like Target and Home Depot, many businesses are approaching the holidays with a more cautious attitude, particularly toward security. Hackers have the potential to steal data and cause millions of dollars in damages, essentially crippling any business no matter their size. What’s even more alarming is that many companies haven’t responded effectively to the threat of security breaches. A recent study has shown that up to 58 percent of retailers are actually less secure compared to a year ago. While some may have added new network security features, cyber attackers have had added time to get inside a business system and take advantage of any weaknesses they have found. The lesson is that organizations need to work on their security for the holidays, and they need to do so immediately. Any delay could be costly.
When it comes to improving business security, one of the first steps is to identify where a company may be vulnerable. This can be accomplished primarily through vulnerability scans. These scans are basically an automated test that businesses can run to find weaknesses within their networks and systems. Any vulnerabilities may eventually be used by hackers to infiltrate the network and steal valuable and sensitive information. This is a particular concern during the holidays since the number of credit card purchases increases dramatically. With the weaknesses properly identified, companies will know where to focus their attention.
Finding vulnerabilities as soon as possible is especially important because current hacking techniques are different than those used years ago. While some hackers may still employ traditional hit-and-run tactics, many others have the long game in mind. Companies that experience attacks during the holidays may actually be suffering from an infiltration that occurred as long as six months ago. Surprisingly, recent research has also shown that attacks during the holiday shopping season don’t actually increase in number, but that doesn’t mean hackers aren’t busy. Many may infiltrate a network during that time but not launch an attack until many months have passed. The main point is that finding vulnerabilities quickly is the first step businesses need to take, and fixing those problems needs to follow immediately.
Companies also need to be on guard for other cyber attacks targeting their business. One of the most common during the holidays is spear phishing. Spear phishing isn’t necessarily targeted toward a company’s network but rather at the employees. The idea is to deceive people into believing an email or similar message is real and have them click on a link. That link usually leads to downloading malware or some other type of virus. During the holidays, spear phishing usually comes in the form of fake charity emails, false shipping confirmations, or a fraudulent bank notification. Since users are making more unusual purchases during this time of year, they are more susceptible to believing this type of scam. While it may seem like this is more of a problem for individuals than for an organization, employees are using personal mobile devices at work much more often through BYOD policies, and those devices often connect to the company’s network. If those devices have been infected with malware, the business could be in trouble.
Combating this type of cyber attack requires companies to inform and train their employees. Workers need to know about the security threats that are out there. That means spotting the warning signs and knowing how to respond to them. This is especially important during the holidays since many workers are only seasonal and may not receive adequate training. Even if the job is temporary, employees still need to be kept up to date about the risks and how to prevent them. Taking this proactive step immediately can help businesses avoid security breaches during the holidays and into the future.
The last thing any business wants is to deal with a security breach during the holidays. Though the threats may feel overwhelming, it’s never too late to start improving security, finding vulnerabilities, and educating employees about the dangers they may face. Fighting the threats is an ongoing battle that should receive extra attention at any time of year, not just the holiday shopping season. With better security, businesses can feel more confident about protecting customer information and preparing for another busy year ahead.
You’ve likely read all about them–the massive security breaches and cyber attacks hitting major corporations like Home Depot, Target, and even the New York Times. These damaging attacks have cost these companies millions of dollars in damages, and they’re just a portion of all the security risk stories out there. As a small business owner, you may be tempted to think your company doesn’t have to worry as much about cyber attackers inflicting damage on your operations. After all, compared to a big business, your company has relatively few resources and doesn’t leave nearly as big of a footprint on the market. That belief, however, could leave you and your business vulnerable. A study from the National Cyber Security Alliance shows that one out of every five businesses becomes a victim of cyber attacks every year, with an even larger portion targeted by hackers. Small businesses need to work to improve their network security, because it’s not a question of if a cyber attack happens but when.
Of course, many small business owners are aware of the security risks and would like nothing more than to invest in the features that would help them repel hackers. The problem is many of these features require money, time, and other resources, and since many small businesses can only barely make ends meet, security issues tend to fall by the wayside. Luckily, there are still several methods you can employ that will increase your network security and keep your small business safe at no extra cost. One of the first and foremost measures that will provide added protection for your network is having stronger passwords for all your accounts as well as your employees’ accounts. A strong password is long–usually around eight characters or more. The password should contain capital letters, numbers, and symbols, and should not have simple words or phrases, no matter how memorable they might be to you. In addition to stronger passwords, small business leaders should also keep tight control over who has administrative access, which can be made easier through existing tools already found on many desktops and laptops (the Local Group Policy Editor for Windows 8 is a good example of this).
Much of a small businesses network security will depend on the workers. While employees may do great work, they also represent a weakness in a security system. Employees can be susceptible to spearfishing attacks and social engineering, which may introduce malware into the network and infect other systems. The best way to combat this is to educate your employees. Teach them the common methods hackers use to gain access to a network and demonstrate the methods they can practice to prevent these attacks from happening. Small business owners should also make sure every employee’s mobile device is secure, since mobile technology is an increasingly popular target for cyber attacks.
All small business owners should also identify the points in their network that are the most vulnerable. While this can be done with purchased software, it’s well known that wireless routers are a favorite entry point for persistent hackers. In fact, recent research shows that around 80% of the 25 best-selling wireless routers for small and home offices on Amazon had notable security vulnerabilities. Hackers can easily exploit wireless routers, often to damaging effect. There are a number of ways you can make your wireless router more secure for your small business. First, you should never use the default IP ranges that come with the router since attackers can easily predict certain addresses and use them. Second, make sure you turn on your router’s encryption while turning off WPS. And third, as mentioned earlier, make sure your router’s password is particularly strong. Change it from the default password you’re given and turn it into one that’s near impossible to crack.
As always, there are security products out there available for purchase, each with varying degrees of features, quality, and price. While the options are plentiful, you should always take into consideration a number of different factors. You need to ensure you have the staff that is trained to fully utilize the software. You also should make sure the program can be configured quickly and easily to suit your needs. Also, try to get software that will have new capabilities added to it as your small business grows over the years. With these considerations in mind, you’ll be sure to pick a security product that’s right for your business.
Attacks happen, and unfortunately there’s no way to prevent them 100% of the time. The best you can do to protect your small business network is to have the security features that will give you a fighting chance. With improved network security, you’ll be able to grow your business with confidence and a safe outlook for the future.
TODAY: Fri, April 28, 2017April2017