Sectors – Big Data Made Simple https://bigdata-madesimple.com One source. Many perspectives. Wed, 17 Jul 2019 05:41:11 +0000 en-US hourly 1 https://wordpress.org/?v=4.9.7 https://bigdata-madesimple.com/wp-content/uploads/2018/10/bdms-favicon.jpg Sectors – Big Data Made Simple https://bigdata-madesimple.com 32 32 Cash flow and big data: the fintech opportunity ahead https://bigdata-madesimple.com/cash-flow-and-big-data-the-fintech-opportunity-ahead/ https://bigdata-madesimple.com/cash-flow-and-big-data-the-fintech-opportunity-ahead/#respond Wed, 17 Jul 2019 05:39:42 +0000 https://bigdata-madesimple.com/?p=35277 Maintaining stable finances is a core concern of almost every business, regardless of the size or type, because — unless you happen to be independently wealthy and willing to throw good money after bad — you can’t keep operating once your funds run dry. But it’s often a complicated matter. Payments big and small stack … Continue reading Cash flow and big data: the fintech opportunity ahead

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Maintaining stable finances is a core concern of almost every business, regardless of the size or type, because — unless you happen to be independently wealthy and willing to throw good money after bad — you can’t keep operating once your funds run dry. But it’s often a complicated matter. Payments big and small stack up, economic circumstances shift, and revenue varies. Even if you’re smart and careful, you can still have great difficulty.

In recent years, though, the field of big data has moved from an interesting consideration to an influential practical reality. Across industries, businesses are using rich data analysis to achieve remarkable things: yielding valuable insights and prompting operational improvements. It helps us work smarter, not harder. Can it be used to shore up financial security as well?

The simple answer is “yes”. If implemented correctly, algorithms can absolutely produce a seismic shift in how businesses handle their money. In fact, given time, they surely will. Let’s take a closer look at the fintech convenience that’s waiting over the horizon:

The practical demands of cash flow calculation

In essence, cash flow is the amount of money your business brings in during a particular period. Stacked up against the amount of money it spends during that same period. Companies typically look monthly, but it could also be weekly (depending on the circumstances — the regularity of the payments, etc.). If you bring in more than goes out, you have a positive cash flow.

Despite the immense importance of cash flow, it’s often overlooked and/or misunderstood. Companies think that profits is what they need to prioritize. Not necessarily— at least, not to the extent they believe. Profit matters in the long run, but cash flow matters all the time.

What’s the difference? Profit is based on completed transactions — when everything has concluded, did you make money on a deal? But cash flow doesn’t wait for completion. It cares about the money you’ve secured. If you spend heavily on launching deals that will yield major profits in six months, you can run out of money within two months, and be unable to continue.

What machine learning brings to the table

There are various ways to calculate cash flow. But so many elements go into it that it can be a logistical pain to deal with. Some companies hire CFOs (chief financial officers) and task them with getting it all figured out, but good CFOs are costly. There are cash flow formulas you can try, and they can be reasonably simple, but it still takes time to get everything lined up when you’re working at an enterprise level.

This is where machine learning has a lot to offer. Machine learning (or ML) is the simplest form of AI technology (tech that seeks to mimic human capabilities). It uses algorithms designed to be adaptive. That means that an ML algorithm does more than rigidly follow one set routine — it draws from available data to decide how best to proceed.

This makes ML exceptionally strong at carrying out repetitive tasks while iteratively yielding better results, which is exactly what you want from a fintech system. You don’t just want something to work in the background and tell you how much money you’re making you want it to help you do something with that information.

Convenient integration in modern APIs

Modern payments can get extremely fragmented. This is largely due to several factors. The popularity of SaaS solutions. The commonality of micro-transactions. And the range of digital payment gateways and wallets further complicating matters. It’s not simple as it used to be to keep track of everything. Doing everything manually has become a messy matter of leaping from system to system while hoping that you don’t miss anything.

The existence of modern APIs, however, means that automation is extremely accessible. Software solutions are designed for effective communication. Because developers know that users rely on complex ecosystems. And they will always prefer to invest in solutions that they know will slot neatly into those ecosystems.

And even when they won’t get along natively, the convenience of tools such as Zapier or IFTTT makes it fairly easy to link systems together. For a cash flow algorithm, this makes the data-acquisition step totally straightforward: hook it up to every software service you use, and it can rapidly hunt down every invoice and every scheduled payment. It can even look through client communications to find identified deadlines.

Forecasting and optimization

So, as noted, machine learning software is perfectly capable of digging through your data and giving you an accurate and up-to-date cash flow assessment. That’s useful in itself, certainly, because it’s only the beginning. What we’re going to see much more of in the near future is a rich combination of forecasting and optimization.

Solutions such as Fluidly and Dryrun already offer ML-driven cash flow forecasting (though it’s nowhere near as extensive as it will be in a few years), so it’s not like this is purely hypothetical. Businesses can use these tools to predict their future cash flow, and glean potential improvements — for instance, pushing one set of payments back and moving another set forward might yield much greater operational stability.

Eventually, there will be fintech suites that bring cash flow management as close to complete automation as you’re willing to get. Once you’ve established the basic parameters and restrictions, you’ll be able to give the suite total authority over a range of matters. Including the ability to rearrange your payments, chase missed invoices, and even negotiate rates (likely with other ML systems). This will radically change how businesses handle their finances. And make it hugely easier for the average start-up to achieve growth with limited resources.

Over the course of the coming years, we’re going to see the foundations of the business world completely overhauled. By the power of ML algorithms drawing from big data. And fintech is an arena that’s going to prove particularly influential. Anyone who wants their business to get more competitive would do well to take advantage as soon as possible.

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Ways budding professionals can prepare for the future of AI https://bigdata-madesimple.com/ways-budding-professionals-can-prepare-for-the-future-of-ai/ https://bigdata-madesimple.com/ways-budding-professionals-can-prepare-for-the-future-of-ai/#respond Tue, 16 Jul 2019 13:24:57 +0000 https://bigdata-madesimple.com/?p=35272 The world seems to be fueling a dystopian view of what artificial intelligence (AI) can do. However, no machine can ever be imbued with the intelligence of a human; they slavishly follow indefinite program conditions which have already been laid down by a smart programmer. With the increase in technology advancments, Gartner foresees a shift. … Continue reading Ways budding professionals can prepare for the future of AI

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The world seems to be fueling a dystopian view of what artificial intelligence (AI) can do. However, no machine can ever be imbued with the intelligence of a human; they slavishly follow indefinite program conditions which have already been laid down by a smart programmer. With the increase in technology advancments, Gartner foresees a shift. From stand-alone intelligent things to a collaborative swarm network of AI systems.

It shouldn’t come to any surprise that workspaces all across the globe are being reshaped. By disruptive technology day in day out. Moreover, they have the power to automate mundane job operations usually done by humans. Which is a piece of great news, isn’t it! As a result, such tech will carry out more complex tasks. And slowly but steadily decrease the number of jobs for humans. Some of you guys believe that AI is a threat taking our jobs. While there are people who know they need to focus on the other half of the picture.

Early adoption has already begun. Take a look around. You will find virtual assistants, fraud detection and driver-less cars. With the emergence of automation, speech recognition, machine learning, decision-making, and natural language processing, the world is poised to transform itself in the future.

It may quite interest you to know that certain universities have started preparing their pupils for the 360° change. The rosy future of AI is inevitable, and if you are interested, you must pursue career possibilities focused on data science, machine learning, or advanced statistics. It may also interest you to know that McKinsey predicts that AI will replace up to 800 million jobs by 2030.

But the question is, how?

Curriculum requirements

First and foremost, educational institutes need to be honest with their budding employees. They need to learn some jobs are going to have let go- there’s no way around. Apart from this, try to recommit to the skills that are most resilient against automation. I am talking about incorporating certain skills such as pattern recognition, enterprise planning, process optimization, information retrieval in their curriculum. Also incorporate Social and emotional skills, creativity, Problem-solving.

Drawing conclusions about people’s state of mind. If simply put, repetitive tasks such as data entry and some kinds of business planning can be automated. In fact, you will find certain roles depending on the employee’s leadership and interpersonal skills, solve problems using unorthodox methods and ability to judge emotions and states of mind, generate creative content, etc. Tech giants like Microsoft give education and job experience a back seat. They have recognize the value of soft skills in fast-moving industries.

At the college level, it’s time for organizations to revive their courses. In context to coding, computer engineering, data science, analytics and other fields. Ones that contribute to advancement in machine learning, AI, IT architecture, industrial control systems, and robotics. At the same time, do not forget to focus on resilient competencies. Such as critical thinking, teamwork, interpersonal skills, leadership, and entrepreneurship.

Now gone are the days when having a strong knowledge base, problem analytical skills, design, and use of a plethora of engineering tools made you succeed. Today, much like technical stuff; non–technical skills grow in demand in ways that may directly or indirectly affect the society and the environment. Also, make sure that your students take complementary studies. Including humanities, raising awareness of the role and impact of engineering on society and culture courses in other disciplines.

Projects with corporations

Unfortunately, I don’t see more and more universities offering classes driven by projects with a corporation. I believe every student should have the opportunity to take courses that enable them to see how their academic curriculum is setting them up for their careers in the new machine-driven world. Getting out of your classrooms will only make you understand the relevance of emerging job opportunities.

Mentorship programs

With the vast amount of opportunities available, it is pretty evident for students to become overwhelmed. Mentors can aid them in gaining insights into how to set up their careers, utilize technology, and select the best employer. Additionally, they can offer support throughout the ups and downs of choosing a career path in the new AI world. And this is very easy as you will come across many alumni’s who wish to stay connected with current students resulting in transforming the current job market.

For companies

If you own a company, especially the one which plans to automate specific roles, make sure you don’t create a living where uncertainty is everything.  For example, the CEO or any other decision-maker shouldn’t break the news about coming automation opportunities. And leave the workforce wondering who will be getting the ax. Remember, your employees deserve a chance too. And maybe that’s the reason why they begin to look for different ways to educate themselves into a higher-paying and more demanding role than they have now.

In addition to this, companies should uplift employees into higher-order roles. By doing this, one can surely achieve a productive synergy between humans and machines that limits job loss. At the same time, you will be able to prepare the entire workforce for a rising tide in new jobs in automation support, IT, data science, and robotics.

As a society, it brings everyone else’s role in this. Do you think is there something mainstream society can do to prepare for AI in the workforce? Of course, only when we start taking automation, AI, and the green energy transition as seriously as the rest.

For example, our changing times mean “radical” proposals are reaching the halls of government. Like the Green New Deal. Which would help re-train U.S. employees for the changing economy. As well as offers a national job guarantee. Which helps force the public and private sectors to invest in people as well as machines. It’s worth taking notice and seeing which kinds of programs could more than pay for the investment required.

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Why your brand needs a data-driven marketing strategy https://bigdata-madesimple.com/why-your-brand-needs-a-data-driven-marketing-strategy/ https://bigdata-madesimple.com/why-your-brand-needs-a-data-driven-marketing-strategy/#respond Tue, 16 Jul 2019 06:51:21 +0000 https://bigdata-madesimple.com/?p=35262 Gone are the times when marketers would rely on their instincts to launch ad campaigns. In this day and age, when the competition knows no bound, your marketing has to be right on the money. Otherwise, you stand no chance to get the better of your competitors. That’s exactly why data-driven marketing has become a … Continue reading Why your brand needs a data-driven marketing strategy

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Gone are the times when marketers would rely on their instincts to launch ad campaigns. In this day and age, when the competition knows no bound, your marketing has to be right on the money. Otherwise, you stand no chance to get the better of your competitors. That’s exactly why data-driven marketing has become a buzz word in the business world.

The way data-driven marketing has enhanced the accuracy of marketing campaigns, it has pretty much become a requirement today. With the increased accessibility of customer information and enhancement of big data, marketers perceive data-driven strategy as crucial to success.

According to Insights Report, 64% of the respondents to a survey ‘strongly agree’ that data-driven marketing is essential for growth in the current global hyper-competitive economy.

Let’s have a close look at the perks that come with this mode of marketing:

Helps you in personalized marketing

In the past, a one-size-fits-all marketing campaign was launched for all customers. There was no way marketers could pay attention to individual needs. However, this trend has changed with the introduction of a data-driven marketing strategy.

With the help of data, marketers today, can generate campaigns keeping a particular potential consumer in mind. Personalization gives the impression that brands care for their customers and the consumers pay off by showing their loyalty towards the brands.

Today, people are familiar with the turns and tricks used by marketers, so it makes personalizing even more important.

The above infographic shows some of the chief benefits of personalization.

You can take an informed decision

Having detailed market insight makes life easier for brands. It saves brands from throwing money blindly into marketing. With this much information serving you as a cushion, you always know where you are heading so it minimizes the risk of failure as well.

The data not only helps you to take an informed decision but you can even forecast results to some extent because you are already aware of how customers are likely to behave.

Leads to better product development

According to an article published in Harvard Business Review, poor understanding of the market is the biggest reason behind flawed product development.

Suppose your brand has launched a top-notch product without considering public demands. If you are lucky, the product might do well. If not, get ready for a huge setback. That’s how it used to be until recently. But data-driven marketing has completely changed the dynamics of product development.

Needless to say, the data spells out everything about your audience. When you know what people expect from you, then you proceed with the product accordingly. It is like heading to the destination with a map in your hand.

Basically, data-driven marketing keeps you connected with your customer base. It includes tracking their activities on social media and other platforms which give you “a more than a rough idea” about their changing needs. To sum up, the more you are connected with customers, the less likely it is to launch a defected product.

Optimizing customer experience

A study conducted by Temkin Group finds that companies that earn 1 billion dollars annually are likely to earn an additional 700 million dollars within three years by investing in customer experience. In the past, companies had to concentrate on product quality to make the mark. But times have changed.

It is perhaps more important to care about the customer experience today. Particularly, marketing to millennials is about customer experience. If it was not the case, 86 percent of the customers would not be willing to pay more for the sake of great customer experience. Customer satisfaction not only improves the retention rates but also leads to customer loyalty towards the brand.

A fair proportion of brands is applying data-driven marketing techniques just to enhance their customer experience. You need constant measures and analysis to improve customer experience which is the virtue of data-driven marketing.

These stats speak volume about the growing importance of customer experience.

Enhances customer engagement

With the help of data-driven marketing, you can create content which gets maximum social shares. Since you have identified customer needs through data and if your content relates to them, they will have no problem sharing it.

Following are the major takeaways of social sharing:

  • Circulation of your content on a larger scale will inject trust among customers regarding your brand
  • You will reach out to the larger audience hence, more opportunities for conversion
  • You will be overwhelmed with feedback which is akin to improve customer experience
  • Improves content marketing

The best thing about data-driven marketing strategy is that you are always learning something new. Same applies to the content. Imagine brands investing thousands of dollars in content marketing without being able to measure whether or not their content strategy is working.

How can you improve if you don’t know your mistakes in the first place? Content marketing is an important tool for promotion. You can’t take it casually for sure. That’s where data-driven marketing comes into action.

It helps you to know how people are responding to your content. Is your content strategy working or it has been outdated? When you can find answers to suchlike burning questions, your content becomes more relevant and performs better.


The above chart shows the gradual growth of budget in content marketing of the last 10 years. The popularity of content marketing is quite evident.

Yields you maximum ROI

There are so many platforms of marketing, but the audience of one platform behaves differently than the other. For example, your Facebook followers might not be as receptive to your campaigns which did wonderfully well on Twitter or LinkedIn because the audience of these channels has a different approach.

The data will help you to map out what kind of campaign should be launched for a particular medium to ensure maximum Return on Investment (ROI).    

Keeping an eye on the competitors

To stay in the competition, it is important to know what your competitors are up to. By doing so, not only you outsmart them in business but you can also learn from them. Maybe they are using better keywords or making better use of hashtags than you?

You can also get an idea where you stand in the competition by keeping an eagle’s eye on your business rival. Make no mistake – it takes more than just following other brands on social media or reading their blogs on a daily basis. Analytic tools can get the job done for you without much fuss.

Automation process becomes more lethal

Automation tools have been a great assistance for marketers especially, in the big businesses where the workload is overwhelming. There is no question about the utility of these tools but they are mostly used to save time and energy. Imagine, how lethal automation tools can become if they are supplemented by implacable data.

Through data, brands can learn when their customers are active on social media. Brands can simply automate their posts at those timings for higher conversion.

Same stands true for email marketing. Once businesses have access to data, they can schedule their emails when they are likely to be read. Regardless of how personalized your content may be in the email, it is useless if people don’t bother reading it. It is like striking when the iron is red-hot.

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The age of personalization: why industries should offer services based on taste https://bigdata-madesimple.com/the-age-of-personalization-why-industries-should-offer-services-based-on-taste/ https://bigdata-madesimple.com/the-age-of-personalization-why-industries-should-offer-services-based-on-taste/#respond Fri, 12 Jul 2019 07:02:53 +0000 https://bigdata-madesimple.com/?p=35245 As a college student, I have many places I need to be. Between my college classes, my dorm, restaurants, concerts, my family home, grocery stores, friends’ apartments, meetings, hiking trails, local events, coffee shops, hot springs, sports games and an internship, I am constantly on the go. It is not unusual for me to spend … Continue reading The age of personalization: why industries should offer services based on taste

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As a college student, I have many places I need to be. Between my college classes, my dorm, restaurants, concerts, my family home, grocery stores, friends’ apartments, meetings, hiking trails, local events, coffee shops, hot springs, sports games and an internship, I am constantly on the go. It is not unusual for me to spend over three hours commuting every day. Normally these commutes would be something to dread, but I have actually found them to be what I look forward to during my day.

Why personalization works: a use case

A few years ago I, like millions of others, was part of the population that despises commutes. However, my attitude completely changed when I was introduced to the Spotify music streaming app. Until that point, I had used many other music streaming systems, but grew tired of the same songs and the time it took to find new content I could enjoy. When I discovered Spotify, I found that it changed my listening habits dramatically. I could listen to new songs from my favorite genre or one of my favorite artists. I started to enjoy listening because Spotify offered me a curated, personalized experience. What truly changed my commutes, though, was my introduction to Spotify’s “Discover Weekly” playlist.

Spotify creates this playlist every Monday just for me based on my music listening tastes. They collect data on me, and analyze it in order to uncover what drives my preferences. I specifically remember the first time I discovered Discover Weekly, because I spent the entire night listening to it playing on repeat.

According to Spotify, Discover Weekly listeners stream more than double the amount of users who don’t listen to the playlist because of the personalized experience it offers.”

I have been listening to my Discover Weekly playlist for a couple of years now.  It has quite literally changed the course of my life. I schedule my week more around the release of the playlist than anything else. I take the scenic route to a destination so I can listen to just one more song. And even started streaming music outside of my commutes, making me a recreational music listener.

The need for personalized services in all industries

Personalization has not just hit the music industry, however. E-commerce and other forms of online retail have also been using personalization to help customers find the right product at the right time. Amazon’s recommendation engine, for instance, drives 35% of its revenue. Many other e-commerce websites partner with AI and analytics start-ups to provide their customers with personalized shopping experiences.

Another industry starting to benefit from personalization is finance. Albeit, the transition to incorporate new data-driven technologies has been very slow. Finance lags far behind other industries in how it determines consumer trends and tastes, and it is not nearly as effective as it should or could be. The good news is that banks have begun the journey towards personalized experiences for consumers. For example, the Russian bank Sberbank has introduced an AI-based tool ‘Tips’, which offers customers personalized financial advice based on their customers’ banking behavior.

A Singapore-based AI and big data startup, Crayon Data has been leveraging personalization on behalf of both the banking and e-commerce industries. Their propriety AI recommendation engine maya.ai helps banks create, launch, and execute offer campaigns based on their customers’ personal taste. I could not be happier about this. I look forward to the day when my bank can give me personal offers based on my actual preferences. They have my data already, and it will be incredible when they can send me campaign offers tailored to me.

The future scope

One area I know I would also enjoy personalization is in the food sector. I occasionally receive offers for dining discounts, but they are almost always to food options I do not enjoy. I crave a service that can help me find offers for food vendors that I am not yet aware of but will likely enjoy based on my previous transactions. Currently, I have two favorite vendors that account for over 50% of my food purchases every week. I do not have the time or patience to explore other options near me. But this would be completely changed with personalization.

It is clear that personalized recommendations have worked, and we will be seeing a lot more of them as time goes on. I only hope it comes sooner rather than later.

Akin to Spotify and my listening habits, a change in a bank’s effort (or any industry for that matter) to leverage personalization would revolutionize my use of discount offers. Until that time, I will continue to enjoy personalization wherever else I can find it.

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The modern workplace: ways how we work differently https://bigdata-madesimple.com/the-modern-workplace-how-innovation-has-changed-the-way-we-work/ https://bigdata-madesimple.com/the-modern-workplace-how-innovation-has-changed-the-way-we-work/#respond Thu, 11 Jul 2019 10:45:49 +0000 https://bigdata-madesimple.com/?p=35237 Technology has revolutionized the way we work. This is nothing new, as technology revolutionized farming practices in the 17th and 18th centuries, and it was the driving force behind the first, second, and third industrial revolutions. The role of technology today is enabling humans to work anywhere, anytime, which has fully revolutionized the way people … Continue reading The modern workplace: ways how we work differently

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Technology has revolutionized the way we work. This is nothing new, as technology revolutionized farming practices in the 17th and 18th centuries, and it was the driving force behind the first, second, and third industrial revolutions. The role of technology today is enabling humans to work anywhere, anytime, which has fully revolutionized the way people work and collaborate with one another.

Advanced technologies like video conferencing, VoIP phone systems, 3D printing, digital mail, robotics, AI, machine learning, and VR have completely changed the way people do businesses and the way the workplace is used. People no longer need to be in the office in order to work; many work remotely and hire a virtual office to handle their mail and meet people; others work from home or their favorite coffee shop, and some have embraced the digital nomad lifestyle.  Thanks to wireless technologies, people only need a smartphone, tablet, or laptop to successfully work regardless of time or place.

From 9 to 5 to 24/7

It seems only natural then, that if people can work anywhere, anytime, that the traditional 9 to 5 job is already sort of obsolete. There’s a downside to working from wherever you like at whichever time you like: people might expect you to always be on. And that’s what happened. Instead of having a fixed schedule, many people who work from home or remotely find it hard to disconnect from work.

Even though they might not be actively working (like me writing an article or blog), they are checking mails and responding on collaboration apps. There’s a reason “workcation” (work-vacation) visas are now a reality in some countries. Instead of working 9 to 5 and taking two weeks’ vacation, people take longer vacations that involve some sort of work.

Still, it’s a pretty sweet deal and technology is poised to further revolutionize the way we work; to the extent that many experts predict humans will be working alongside robots in the near future.

Here’s a list of the top technologies that are revolutionizing work and the workplace.

IoT (Internet of Things)

The IoT is a networking of physical devices, vehicles, appliances, and other items (lightbulbs for example), that connect with electronics, software, sensors allowing them to share and exchange data. IoT is the technology behind smart buildings.

IoT is positively impacting the workplace by making spaces more efficient, easier to customize to the end user’s needs, and easier to interact with. Lights turn themselves on when they sense movement, the temperature is automatically adjusted based on the time of day and the amount of people in the building, sensors and other connected devices gather usage data that can be used to understand how people use the space, etc.

By making buildings more efficient, the IoT is also helping companies tackle sustainability challenges.

AR and VR

Augmented and virtual reality are changing the way we work by allowing users to have immersive experiences. The gadgets are also pretty neat. Augmented reality combines elements of the real world with digital components. Virtual reality takes it a step further and basically, creates a whole new world that can be accessed through a headset.

These technologies have a variety of potential applications: immersive and more realistic meetings, product creating, workplace design, and more.

Cutting edge virtual office solutions could, in the coming years, incorporate AR/VR technology into their conference rooms to provide an immersive virtual meeting environment. Instead of looking at a picture or pixelated video of a colleague, you could interact with a hologram, pull out a CAD model of your latest product and share ideas on a virtual whiteboard.

Though these technologies are in their infancy, they have a promising future.

Robotics and artificial intelligence

Though some of the talk around robots and work is somewhat apocalyptic, the fact is robots are far from making human beings obsolete. They will take over some jobs, but for the most part, experts predict a lot of robot + human collaboration in the future.

Robotics, combined with artificial intelligence (AI), has the potential to maximize humans’ work potential and productivity. They are the technology behind automation and AI can go through thousands, if not millions, of data in minutes.

These technologies can complement human capabilities in a plethora of ways. In the medical field, AI is helping doctors make more informed medical decisions and diagnoses, while robots are helping make surgeries more accurate and safer. In factories, robots are speeding things up and adding safety. Robots are also making delivery a much more lucrative and faster business (one-day shipping is a marvelous thing in today’s fast-paced world).

Digital assistants

Often called virtual assistants, digital assistants like Alexa, Siri, Cortana, Watson Assistant, Cisco’s Spark Assistant and Google Echo are already making a big boom in the world of work. They are helping workers increase their productivity and making it easier for them to do certain types of tasks.

These assistants are fountains of information; they can read and interpret information, book appointments, record calls, and meetings, enter data, translate, and much more. These AI powered digital assistants are task-oriented and they are helping organizations in their digital transformation efforts.

Conclusion

For centuries now, technology has revolutionized the way people work. Technology today is evolving faster than ever and reaching new capabilities, however, like in the past, technology is helping make human beings more productive and more efficient.

The more technology reaches new capabilities, so do humans. Technology, in the end, is an enabler.

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4 ways big data is changing the healthcare industry https://bigdata-madesimple.com/4-ways-big-data-is-changing-the-healthcare-industry/ https://bigdata-madesimple.com/4-ways-big-data-is-changing-the-healthcare-industry/#respond Wed, 10 Jul 2019 12:13:19 +0000 https://bigdata-madesimple.com/?p=35230 When it comes to healthcare, big data is saving lives. Although the healthcare industry has been slow to adopt it, big data is now bringing about rapid changes that will change healthcare for the better. Ensuring staff availability Getting the right level of staff is always a challenge for management. Using big data, we can … Continue reading 4 ways big data is changing the healthcare industry

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When it comes to healthcare, big data is saving lives. Although the healthcare industry has been slow to adopt it, big data is now bringing about rapid changes that will change healthcare for the better.

Ensuring staff availability

Getting the right level of staff is always a challenge for management. Using big data, we can analyze trends and use them to forecast surges in patient numbers in an emergency department, for example.

There are obvious trends – we already know admissions are likely to increase around public holidays. But there are also subtle trends that are hard to detect using the human brain alone. Big data enables hospital managers to step outside their own view of the world and predict trends based on real numbers and facts. This reduces hospital waiting times and ensures people are able to access the care they need when they need it.

Improving clinical trials for new medicines

The development of new medicines is an essential component of healthcare, with the FDA approving around 20 new drugs each year. Almost all of these new medicines will undergo clinical trials to ensure they are safe for human consumption, and effectively treat the conditions they are to be prescribed for.

Big data is helping to make these clinical trials more effective, by enabling them to pick the right subjects and identify opportunities to test existing drugs for the treatment of alternative health conditions. For example, the antidepressant known as Desipramine was recently hypothesized to be a potential treatment for certain types of lung cancer. Researchers made this discovery by scanning a huge number of gene-expression profiles to identify trends. This discovery would not have happened without big data.

Reducing the costs associated with healthcare

Big data can help healthcare providers use their budgets effectively, reducing the costs associated with their operations. For example, it can be used to optimize the supply chain – using knowledge of patient demand and order histories. This can benefit healthcare providers by ensuring they have an adequate stock of pharmaceuticals and consumables available when they need them, without ordering more than is likely to be required. Not only does this free up tight budgets, but it also maximizes the use of on-site storage and reduces operating costs associated with storing volatile substances.

Providing innovative ways to treat injuries and health conditions

Healthcare is changing. Thanks to big data, we’re no longer confined to the traditional methods for treating and preventing ill health. Innovation in healthcare means we are breaking new ground every year, constantly transforming our approach to treating conditions impacting millions of people across the globe.

The FDA, for example, have now approved battery powered hearts for implantation in humans. Game-changing breakthroughs such as this, which push the limits of what we previously thought to be possible, would not be happening without the technological advances brought about by big data.

There’s still so much we don’t know – but it will be exciting to see where big data leads us over the coming decades. From thought-controlled robotic legs to exact replicas of the human brain, are there any limits to what technology can help us achieve?

 

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Education and technology: top apps digitizing the learning process https://bigdata-madesimple.com/education-and-technology-top-apps-digitizing-the-learning-process/ https://bigdata-madesimple.com/education-and-technology-top-apps-digitizing-the-learning-process/#respond Tue, 09 Jul 2019 14:04:47 +0000 https://bigdata-madesimple.com/?p=35226 Let’s face it: school is hard. Whether you are a teacher or a student, there are a lot of things that you have to do for your classes. Prepare study material, take down coherent notes, set questions (or learn answers) and manage study timetables to name a few. There’s good news though. With the rise … Continue reading Education and technology: top apps digitizing the learning process

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Let’s face it: school is hard. Whether you are a teacher or a student, there are a lot of things that you have to do for your classes. Prepare study material, take down coherent notes, set questions (or learn answers) and manage study timetables to name a few. There’s good news though. With the rise of the internet, there are now many digital tools designed to help you, whether you’re learning or imparting knowledge.

Like any other field or industry, technology has opened up newer ways of learning. Several companies have created tools, apps or run successful websites that are designed to make education easier for both students and teachers. Here are a few that may assist you with your school experience.

Quizlet

A great way to learn the material is to create flashcards and use them to memorize the information.  Quizlet is a tool that allows you to create custom digital flashcards and diagrams.  They can be used the same way as the paper ones.  There is also Quizlet Live, which is a game that teachers can use in the classrooms to add a little extra fun to the learning process.

Khan Academy

People behind Khan Academy believe that everyone should be able to get an education, and they want to help foster that without asking to purchase anything.  They built a platform that offers courses of any topic you may be looking to learn.  These courses are presented via a series of videos taught using visuals and other engaging techniques.  Activities and challenges are included to ensure that you are effectively learning the information.  This can be a great way to help students get new information.

Grammarly

Most classes require students to write an essay.  You will need to make sure that it is a quality essay if you don’t buy one online via Edusson or any other reliable website where one can buy quality papers online.  It is essential that your writing is clear and error-free.  Grammarly can check your homework for spelling and grammar mistakes.  It can be added to your internet browser as an extension, so you can use it when writing emails, tweets and so on.

Socrative

Socrative is an app that allows teachers to interact with students easily and test how much they understand the information they have been learning.  Rather than require everyone to write papers, a teacher can assign small quizzes to students on classroom computers or tablets.  Since these are assigned specifically to each person, every quiz can be a great way to interact with learners on an individual level.  The results allow the teacher to evaluate one’s performance quickly.

Seesaw

It is not only important that students learn the information taught in their classes, but they should also develop as scholars.  Seesaw helps with this by providing a way for them to document their progress in school.  Each student gets their own portfolio that they, their teachers, and parents can look at to reflect on.  This allows everyone to help the student thrive in school.

Scratch

For students who are learning to program, a service such as Scratch can be a great tool to help them develop their skills in a fun way.  Users can create games and other presentations using coding techniques.  It integrates multimedia such as music and pictures to make engaging end products that they can be proud of.

Adobe Spark Video

A great way to learn information is to explain it to someone else.  Writing essays is one way to accomplish this.  Adobe Spark Video offers students an alternative.  They can create small animated videos with added voice recordings to present a topic.  Adobe Spark Video can be used for creating class presentations as well, giving students a chance to add pictures or video clips that will make their presentations more exciting.

CK-12

One of the things that can cost the most when it comes to school is textbooks. People who created cK-12 recognized this, so they came up with a website that would allow students to assess the materials they need without buying anything.  This website enables users to create interactive “books” that can be used alongside other coursework.  These online resources can be customized so that they can be best suited to the individual.

Class Dojo

It is important that students are well-behaved and focused.  This creates a positive classroom environment that can help everyone learn better.  Class Dojo is one of the digital tools for teachers that are available.  It allows teachers to track their students’ progress in these categories, and that information can be easily passed along to their parents, so they know how their children are doing in school.  Teachers can also create tasks that are tailored to each student to encourage good behavior and development in the classroom.

Google Classroom

It can be discouraging to not understand information and feel like you are alone when you are a student.  Google Classroom now offers a solution to this problem.  It is a way for a student to post questions they have about the material they are learning and receive answers from their teachers and fellow students.  Instructors, in turn, can post extra material and interesting points to ponder at home.  It allows everyone to interact and learn together outside the classroom.

These are just some of the digital tools for learning that are out there.  From apps to websites, there are many ways that can help make the classroom experience beneficial for teachers and their students.  Feel free to check these out and to find some more that will be useful to you in the future.

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Cybersecurity: how artificial intelligence has changed the way we secure our data https://bigdata-madesimple.com/cybersecurity-how-artificial-intelligence-has-changed-the-way-we-secure-our-data/ https://bigdata-madesimple.com/cybersecurity-how-artificial-intelligence-has-changed-the-way-we-secure-our-data/#respond Mon, 08 Jul 2019 09:53:52 +0000 https://bigdata-madesimple.com/?p=35221 In recent years, the growth of AI & ML has been unprecedented. Recent studies predict the rapid adoption rate of AI across all business, estimating that the AI market will reach an approximate of $13 trillion by 2030. To define it, artificial intelligence refers to the machine’s ability to simulate human intelligence without explicit programming. … Continue reading Cybersecurity: how artificial intelligence has changed the way we secure our data

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In recent years, the growth of AI & ML has been unprecedented. Recent studies predict the rapid adoption rate of AI across all business, estimating that the AI market will reach an approximate of $13 trillion by 2030.

To define it, artificial intelligence refers to the machine’s ability to simulate human intelligence without explicit programming. Machine learning is an application of AI that develops mathematical models based on training data and leverage these models to make predictions when new data is supplied.

For instance, you can train a computer-vision ML model using hundreds of image samples that have been labeled by humans, so that it is able to automatically classify images in an object.

Though the principles of AI and ML have been around for decades, it is only in the past couple of years that it has garnered attention. The recent surge in popularity can be attributed to two main factors: the growth of cloud computing and the availability of big data. With cloud computing, AI/ML algorithms can be run practically and big data has enhanced the effectiveness of AI/ML, enabling them to better in a number of applications than humans.

The reality of AI in cyber security

Cyber security is one of the most promising areas for AI/ML. Theoretically, if the machine is able to access all your data, both good and bad, then it can be trained to detect any anomaly or malware as soon as it surfaces. Practically, three are three core requirements for this to work.

  • Availability of massive amount of data – Your model’s effectiveness depends on the volume of benign and malware data that you have.
  • Data pipeline – You must have data engineers and scientists who are able to create a data pipeline for continuously processing the samples and design effective models
  • Providing Insights – You must have security domain specialists who are able to categorize what is good or bad and also has the ability to explain why is that the case.

Most organizations that boast of AI/ML powered security solutions are lacking in one or more of these requirements.

Getting into the process

A fundamental principle of security is a defense in depth. The defense is depth relates to having a number of security layers and not depending on one single technology such as AI/ML. The recent hype around the new AI/ML enabled security endpoints touts that it can do it all. However, if you want to shield a user from cyber fraud, ensure that all user accessed content is scanned and that their system is updated regularly. The scanning of each and every file before you allow downloading needs the ability to stop SSL-encrypted communications between the destination server and the user’s client. Or else, the scanner will be imperceptive to it. As scanning all the file can consume a lot of time,  latency can be introduced and lead to issues in user experience. Anyway, the rapid blocking of the threats and permitting the already white-listed stuff is effective in balancing user experience with security.

After known threat intelligence has been employed and no conclusion is available, we enter the space of zero-day threats which is basically unknown threats. Theses zero-day threats do not have recognizable signatures, so sandboxing is used for scanning such kind of unknown threats. Sand-boxing consists of the installation of a suspicious file in a virtual machine sandbox that imitates the end user’s system and then identifying whether the file is good or not based on the behaviour observed. This process can take several minutes. As you know, today’s users want quick results and loathe waiting. With a properly trained AI/ML model, results for such files can be obtained in milliseconds. Most new attacks use exploit kits and they might borrow exfiltration and delivery techniques from previous attacks. AI/ML models can be trained to identify these polymorphic variants.

One critical consideration while using AI/ML for detecting malware pertains to the ability to offer a reasonable explanation regarding the classification of a particular sample as malicious. For instance, if a customer demands an explanation on why a sample was blocked, the answer cannot be on the lines of ‘AI/ML said so’.  It is important to have a security domain expert who is able to understand which behaviours/attributes got triggered and who is also able to analyze false positives/negatives. This is required not only to understand why a certain prediction was made, but also to continuously improve the accuracy of the model prediction.

Training AI/ML models

When we talk about the training of AI/ML models, the debate is regarding the use of supervised learning or unsupervised learning. Supervised learning, based on labeled data that is extracted to attain a prediction model. What this means for malware is that human specialists from data sets, take each sample and label them as good or bad, and perform feature engineering to find out what malware features are relevant to the prediction model before training. In unsupervised learning, patterns are obtained to determine structure from data that is not categorized or labeled. The proponents of unsupervised learning claim that this type of learning is not free from feature selection bias and is also not limited by the confines of human classification. The usefulness of unsupervised learning, however, remains to be validated.

The best security areas where AI/ML can help

There are some kinds of security challenges that suit AI/ML more than others. For example, let’s consider the example of Phishing detection. It has significant visual components. With the use of images, logos and other ‘look and feel’ elements, an adversary will be able to make a fake website to resemble its legitimate counterpart. The advancements in AI/ML vision algorithms has made it possible for the technology to identify fake websites that are designed to cheat unsuspecting users.

Additionally, AL/ML algorithms can be employed to detect anomalous user behavior, getting insight into what constitutes the user’s normal behavior and then flagging when there is a notable deviation from the norm.

In conclusion

When AI/ML model is trained effectively under the expertise of data scientists and cyber security experts, it can prove to be a valuable tool to the cyber security defense-in-depth armoury. However, today we are still miles from declaring AI/ML as the penultimate remedy for curbing all cyber frauds.

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Healthy work culture: tools to create efficient employee schedules https://bigdata-madesimple.com/healthy-work-culture-tools-to-create-efficient-employee-schedules/ https://bigdata-madesimple.com/healthy-work-culture-tools-to-create-efficient-employee-schedules/#respond Tue, 02 Jul 2019 11:13:45 +0000 https://bigdata-madesimple.com/?p=35168 One of the most important components of a company is its culture. When you have a culture that encourages employee happiness, it can make a massive difference to how your company performs. As studies have found that companies with happy employees outperform the competition by 20% and earn 1.2 to 1.7% more than peer firms. … Continue reading Healthy work culture: tools to create efficient employee schedules

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One of the most important components of a company is its culture. When you have a culture that encourages employee happiness, it can make a massive difference to how your company performs. As studies have found that companies with happy employees outperform the competition by 20% and earn 1.2 to 1.7% more than peer firms.

So, when you make any changes or additions to important components like the employee schedule at your company, you should be extremely meticulous. This will ensure that it only has a positive effect on your employee culture and no negative effects at all.

Therefore, to help you create an employee schedule that creates a happy work atmosphere and culture I have put together this quick guide for you.

#1 Ask employees what they want

A healthy work culture will only exist if you know what your employees want. It should match their requirements, personalities and skill sets collectively. This is why while creating a schedule that promotes a positive culture, you need to find out what your employees want.

Start by either interviewing employees individually or by getting them to take a survey. Find out things like their favourite time to work at, the colleagues/team members they prefer working with most and other questions that will help you gather better information about what they prefer at work. Also, ask questions that will better understand their personalities.

You can easily set up this survey by using a tool like Survey Monkey.

Next, conduct a group meeting so that your employees can sit together and discuss what an employee schedule they prefer would look like. Make sure you record this meeting and get someone to take notes.

Taking these two steps will help you create an employee schedule that pleases your employees both individually and collectively. When you run surveys like these it shows your employees that you care. This assurance will spur them to work harder. They just want to have their say as found by this study.

For example, Facebook conducted a survey and asked 30% of its employees whether or not they were personally committed to improving their work experience there. This resulted in the employees being 12% more likely than their colleagues to request a curated list of additional tools and resources to help them become more engaged at Facebook.

#2 Set up the schedule

After you gather the data from the above method you can set up the schedule. Combine this newly acquired information with data from other sources like the best-performing companies and your previous employee schedules to set up a schedule that not only promotes a healthy culture but also boosts performance.

Make sure you execute this step by using a dedicated software to manage your employees’ schedule. Modern software comes inclusive of templates, AI and more advanced features. This will save a lot of time.

You should set up this schedule at least 2 weeks in advance.

Making minor improvements to employee scheduling and ensuring that the schedule is executed properly can improve your sales by 3% at least. When GAP began releasing employee schedules 2 weeks in advance and made some other changes to their schedule their labour productivity increased by 5% which helped them earn $2.9 million.

#3 Allow employees to communicate and make changes

After you release the schedule, you will find that some of your employees will get back to you to inform you that they would like some changes in timings. To make things easier, you should let employees communicate with each other directly and make changes to the schedule by themselves. Employees can themselves contact their colleagues and find people who would be happy to cover their sift while they are absent. You should only step in if it is absolutely necessary.

In the above study with Gap, one of the other changes they made was allowing employees to swap shifts with each other through the scheduling app without the requirement of approval from the managers.

This will not only give you less work to do but will also improve communication between employees. This will help promote a healthier work culture.

#4 Measure employee happiness and productivity

You won’t create the perfect version of the employee schedule in your first attempt. It will take several attempts before you create something all of them will be happy with. This is why you should measure employee happiness and performance periodically (at least every month). It will help you check if the schedule is faring better or if things have worsened.

This should be measured by two methods. One of them is through the aforementioned interviews and collective meetings. You only need to change the questions you ask. This will help you check their happiness levels.

To measure productivity, you mainly need to compare the productivity levels and company performance before and after the implementation of the schedule. You can even install employee tracking on your employees’ devices (laptops and phones) to check the effect the new schedule has had on them.

You can use the data you get from these two methods to modify the schedules. Through this experimentation, you will be able to create a newer and more accurate employee schedule and work culture.

A company that has great success with better tracking employee activity is Afton Manufacturing. After implementing better employee time tracking methods, they realised that they were losing 10 minutes a day per employee. And after making necessary modifications in the first year alone they were able to save up 300 hours and $6,000.

Conclusion

These are the 4 steps you must take to create an employee schedule that promotes a healthy culture. It requires a lot of work. But you will see the effects of it in increased profits.

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Ten predictions for ransomware: the past, present and future https://bigdata-madesimple.com/10-predictions-for-ransomware-the-past-present-and-future/ https://bigdata-madesimple.com/10-predictions-for-ransomware-the-past-present-and-future/#respond Wed, 26 Jun 2019 10:49:16 +0000 https://bigdata-madesimple.com/?p=35139 Ransomware has come a long way, from the days of fake antivirus to now when the approach is a little different, but the objective remains the same. Ransomware is basically a malware that locks a computer and uses law enforcement imagery to intimidate victims into making payments in order to facilitate unlocking. It has spread … Continue reading Ten predictions for ransomware: the past, present and future

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Ransomware has come a long way, from the days of fake antivirus to now when the approach is a little different, but the objective remains the same. Ransomware is basically a malware that locks a computer and uses law enforcement imagery to intimidate victims into making payments in order to facilitate unlocking. It has spread across the globe initially from Eastern Europe to Western Europe, the United States, and Canada. The scam has been copied and professionalized from initial early attacks, with established online criminal gangs now branching out into the scheme. Each gang has separately developed or bought a different version of the ransomware.

This malware is highly profitable, with as many as 20% of compromised users paying out according to statistics. An investigation into one of the smaller players in this scam identified 68,000 compromised computers in just one month, which could have resulted in victims being defrauded of up to $400,000 USD. A larger gang, using malware called Reveton (aka Trojan.Ransomlock.G), was detected attempting to infect 500,000 computers over a period of 18 days. Given the number of different gangs operating ransomware scams, a conservative estimate is that over $5 million dollars a year is being extorted from victims.

The scam has evolved over time, using various techniques to disable a computer. A lot of individuals do pay up, either because they believe the messages or because they realize it is a scam but still want to restore access to their computer. Unfortunately, even if a person does pay up, the fraudsters often do not restore functionality, the only reliable way to restore functionality is to remove the malware.

From just a few small groups experimenting with this fraud, several organized gangs are now taking this scheme to a professional level and the number of compromised computers has increased. We have identified several different versions of ransomware. Multiple gangs have retained Software engineers to develop these different versions independently. In fact, there is not just one single family of ransomware composed of multiple variants, but rather multiple families each with their own unique behavior.

In light of the foregoing, the future seems to be bleak but there is hope, below is some of the probable things that may be witnessed in the coming season.

# 1 | More targeted actions shall bring some firms to ruin

We’ve engaged with plenty of IT groups who believed that if they had a ransomware attack, they would decipher it with easy. Unfortunately, enterprises that still hold this belief will be victims of data compromises sooner rather than later and they will be caught unawares. The fact is that hackers are smarter than they’re known for, which buttresses the possibility that more enterprises will succumb without a strategy for quick restoration, so intrusion monitoring and protection strategies aren’t optional.

# 2 | Unnecessary false alarm alerts.

Businesses have started to set up safeguards, but those may not be sufficient if the information isn’t reliable. If threat monitoring solutions regularly identify every small thing, IT groups will eventually start ignoring the alerts— hence putting them plus the data they’re securing at greater risk. Businesses will want to ensure they have an intelligent system that raises flags when there is a real threat versus churning out a high volume of non-actionable alarms.

# 3 | All business shall be susceptible

Businesses of all levels underestimate how exposed they are, but they can’t dare to make this assumption in 2019. When firms don’t believe they’re vulnerable, they don’t see the need to implement systems and processes to ensure survival in case of an attack. For instance, it wasn’t suspected last year that PGA of America’s servers may suffer an attack, but firms that least anticipates it could readily become the next objective for these attacks. And, the worst moment to start meditating upon it is when your firm is in a state of uncertainty.

# 4 | Backup, as well as protection strategies, will fail

Businesses that have security or disaster restoration plans in place are bound to be susceptible to ransomware incidents if they don’t consistently test and confirm for their environment. Several clients have taken up our disaster recovery systems because a routine exercise exposed areas for further growth or they didn’t successfully recover from a backup into a cloud hosting environment. Corporations that are keen on testing their disaster recovery and backup systems will more certainly have what’s necessary to recover from a cybersecurity compromise incident. In the absence of frequent tests, they might actually not have a recovery plan at all.

# 5 | Concerns will heighten around cloud security

Generally, clouds are as stable, or even more stable, than majority data centers. But they have an equal level of exposure to risk that data centers do. This issue has featured prominently among our clients over the last couple of months. They are now more eager to know about the extra features we offer around ransomware. In some situations, we’ll mention the need for those features only to discover that that’s already a priority to them. It just makes a lot of sense that system security issues will be such a priority when resources exit the four walls of a firm.

# 6 |The next couple of attacks shall be more sophisticated

The businesses have put systems in place to shield themselves in the event of that initial wave of attacks, but we are yet to encounter the worst that ransomware can do. Hackers will only grow in aggressiveness and we’ll witness an increased demand for enterprises to install more sophisticated cyber security solutions. They’ll demand a comprehensive solution rather than a simple quick-fix if they plan to withstand the never-ceasing threat cycle ahead.

# 7 | Cloud hosting service providers’ efforts won’t be sufficient

Cloud hosting providers avail infrastructure, but it shall the duty of the enterprise IT teams to ensure they have higher standards of security in the season ahead. Similarly, we’ve discovered that our clients would rather ensure the frameworks they set up around their software and data can move with them if they ever decide to change service providers. Overall, if a company doesn’t have the correct protections in place, it’ll be detrimental to them. A cloud service provider may walk away in short notice.

During the past few years, end users were subjected to misleading applications claiming to be antivirus applications (fake antivirus). Estimates of fraudulent earnings amounted to tens of millions of dollars. While the fake antivirus problem seems to have faded, similar distribution and development techniques are being re-used by ransomware.

It is likely that some of the gangs responsible for the original ransomware are part of this expansion, but other established criminal gangs are also becoming involved. As awareness of these scams increases, the attackers and their malware are likely to evolve and use more sophisticated techniques to evade detection and prevent removal. The “ransom letter” will likely also evolve and the attackers will use different hooks to defraud innocent users.

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