Category Archives: Technology

In The Fast Lane: Connected Car Hacking A Big Risk

In The Fast Lane: Connected Car Hacking A Big Risk

Connected Car Hacking

Researchers and cybersecurity experts working hard to keep hackers out of the driver’s seat.

Modern transportation has come a million miles, and most all of today’s vehicles are controlled entirely by digital technology. Millions of drivers are not aware that of the many devices in their digital arsenal, the most complex of them all is the car they drive every day. Vehicles are globally connected, smart, intuitive, adaptive, and loaded with assistive technology and because of this—vulnerable to attack.

Over the last year researcher have been conducting numerous proof-of-concept demonstrations to test the vulnerability of connected cars. Results are staggering, and range from potential hackers gaining unwarranted entry to completely appropriating control over the car. This includes controlling the media console and radio to actually hi-jacking pilot controls—steering, accelerating and braking.

It is a scary concept for consumers to think that their car can be taken over by hackers, fully controlled and stolen without the thief ever physically touching it. New research suggests that the only way to avoid security breaches is by integrating cybersecurity, cyber forensics and social media with advanced mobile cloud processing.

With completely autonomous cars on the horizon for the average consumer, and connected smart cars already in the mainstream, upping the ante in advancing security for our cars is at the forefront of cybersecurity research and IT specialist’s testing. Because once a hacker is in—he can pretty much do whatever he wants with your vehicle.

If protecting the safety of your own car isn’t enough to worry about—people who use Uber are about to have something else to worry about thrown at them. The company is launching a small brigade of about 100 driverless taxis in Pittsburgh. The fully autonomous vehicles are specially designed Volvos that will be picking up unsuspecting Uber customers.

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(Image Credit: The Newswheel)

Initially there will be a person who sits in the front seat to monitor safety and to satisfy the regulation that currently prohibits cars from driving around without a human in the driver’s seat. If all goes well in Pittsburgh, it is likely that Uber will roll out their cars all over metro cities. For the testing period, customers receive their ride for free.

It is a grand idea, but in the scale of things, some worry that driverless taxis only invite hackers into another realm of illegal possibilities. The question remains whether people will take their ride from a car with no driver, which is where it is heading once legislation allows cars to drive around without a human behind the wheel.

Researchers have their hand full and are making leaps and bounds in cybersecurity. But law enforcement is looking into counter-hacking technology also, and advancements are evolving which allow officers to stop a thief-less car-jacking with some cyber-tricks of their own—but that is something for an entirely different article.

By CJ Callen

Having Your Cybersecurity And Eating It Too

Having Your Cybersecurity And Eating It Too

The Catch 22

The very same year Marc Andreessen famously said that software was eating the world, the Chief Information Officer of the United States was announcing a major Cloud First goal. That was 2011. Five years later, as both the private and public sectors continue to adopt cloud-based software services, we’re interested in this question: how in the world do you eat cloud software?

Cybersecurity today seems to have an unfortunate Catch-22. You want to test (and re-test) your live cloud services to see if they are really secure, but testing too aggressively or frequently will disrupt, degrade, or even leave those services more vulnerable. Keeping your live services up and running is difficult: your aggressive scanning and testing is essentially eating those services — to see if they are good or bad — at the same time you are trying to keep them all in one piece.

Splitting In Half

As the title of this blog hints, running a live system and fully testing that same live system is exactly like trying to have your cybersecurity cake and eat it too — pick one, not both, or more realistically pick half of each. We’ve even heard penetration testing on a live network described as “running fast while shooting at your own feet to see if your boots are really tough enough for the journey.” (Please do not try this at home!)

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It’s no secret that classical vulnerability and penetration testing is filled with wise caution, legal landmines and detailed guidance to mitigate the impact on real operations and businesses. At least one way to try to maneuver around this Catch-22 requires a separate non-production environment of equivalent hardware and software. It’s not easy to keep that non-production environment up-to-date and it demands a lot of constant investment of time and money. The unfortunate reality is that such environments quickly diverge from real operational systems, making them less meaningful. It’s often double the cost for just a fraction of real cyber security benefit.

As businesses rapidly accelerate their dependence on cloud services and the federal government puts sensitive data into the cloud, achieving more secure cloud-based services is critically important. We’re all interdependent and have a shared stake in the outcome.

With a lot on the line there is no shortage of expectations – from financial sector penetration testing requirements to a new military effort calling for more proactive testing of critical operational systems. And we can’t help but mention the groundbreaking Cyber Grand Challenge using artificial intelligence based techniques.

Government Embracing The Cloud

Likewise, as security concerns cause the federal government to step more firmly into the cloud — there’s even a cloud.gov these days after all — the government’s own penetration testing penetration has also anticipated this seeming Catch-22 in cybersecurity. The government expressly allows “testing in a non-production environment” to “limit the impact on business operations.” Then, in the same breath, they wisely require that the non-production environment be “identical to the production environment.” And to reinforce the point they even use italics, noting that the “environments must be exactly same” and not just “almost” the same. We couldn’t agree more!

The Clone

Our answer, then, to the original question — how in the world do you eat cloud software? Leverage the inherent ability of any cloud environment to generate and operate exact (cloned) image of the live systems. Then test those exact images. It’s a bit like interacting with a hologram, except in the cyber world the hologram behaves and reacts exactly like the real thing — because it is as real as the original due to the inherent design of the cloud’s serviced-based architecture. Once you’ve set up the parameters for the cloud service, it makes little sense to ask Amazon, for example, which particular servers in which racks you are running on, because it doesn’t make one bit of difference operationally.

As the cloned versions are setup, the live cloud services keep going while the cloned version is taking the heat. Even if during testing the cloned version goes down in flames, so to speak, that’s ok for two reasons. First, the live operational system is still running fine — keeping your customers and users happy — and, second, you have proactively uncovered an issue before it could have grown into an even larger, real one.

Meanwhile, you can just restart another cloned image and get right back to testing — no need to clean up or try to rewind time. And this approach works across multiple cloud platforms, whether hosted or on premises or a mix, so you can choose your cloud provider — or more likely choose a few of them. Furthermore, your existing investment in scanning, testing, and security tools can also be applied to the exact images.

We agree there’s really no silver bullet in cybersecurity, as it clearly takes a diverse range of tools and techniques to keep a system secure, but a service-based cloud infrastructure really does have one particular silver lining: by scanning and testing fully cloned images, you can have your cybersecurity and really eat it too.

By Ernesto DiGiambattista, Co-Founder and CEO, Cybric

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Prior to founding Cybric, Ernesto DiGiambattista was the Chief Technology & Security Officer for Sentinel Benefits & Financial Group, where he was responsible for transforming a legacy technology team into a technology innovation service group.

In addition, Ernesto was a senior member of Bank of America’s Information Security & Resiliency Group and Corporate Audit organizations. Further, Ernesto has been a trusted advisor on private and public cybersecurity policy to members of the U.S. Senate and the U.S. House of Representatives.

In June 2015, Ernesto was recognized by the Boston Business Journal as a 2015 Finalist for Boston CIO of the Year.

Building A Data Security Strategy – More Important Than Ever

Building A Data Security Strategy – More Important Than Ever

Data Security Strategy

Security and privacy have been an integral concern of the IT industry since its very inception, but as it expands through web-based, mobile, and cloud-based applications, access to data is magnified as are the threats of illicit penetration. As enterprises manage vast quantities of data, they find themselves exposed to regularly revised malicious attacks through complex malware which today has many more access portals than our previously unconnected infrastructures provided. Moreover, thanks to innovations in the Internet of Things (IoT), more data is being collected than ever before, much of it highly personal and particularly sensitive. Of course, the value we gain through big data analytics means we’ll be seeing greater collection and storage of such personal data in the years to come—so a focus on data security is imperative.

Platform Security

value-of-security-analytics

The security of the infrastructure, tools, and processes of a platform play a significant role in the overall security of data, and with an upsurge in the availability of low-cost and free platforms, one has to consider the vulnerability to hacking. This isn’t to suggest that because a solution is cheap or free it isn’t a quality build – though this can, of course, be the case – but the very fact that it is developed to be so readily available to many means there are far more vulnerabilities that need to be adequately secured. When considering data security, we often study the storage facilities and access requirements for these vaults; it’s easy to forget about the security of the platforms that collect, access, and analyse this information.

Device Security

Although the adoption of IoT devices continues to grow, many of the more personal devices remain highly insecure. Users often falsely believe that the information they’re collecting can have no value to anyone else and so they fail to activate safeguards. Unfortunately, in the hands of the wrong person, just about any data can be dangerous, and of further concern is the fact that some IoT devices make access to other smart devices and their data possible, creating a security loophole.

Cloud Security

The development and adoption of the cloud is probably one of the most important and beneficial IT trends of recent years, but with the many tools and enhanced accessibility cloud platforms provide comes a heightened risk to data security and privacy. For organizations using big data and cloud platforms, cloud security should be a top priority.

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Regrettably, many making use of cloud platforms assume that relevant controls and defenses are in place without properly analyzing the underlying structures. And making the situation more challenging is the constant development and improvement of cloud platforms and tools; having the requisite knowledge to understand what security measures should be in place is a full-time job for an expert and leaves little time for anything else.

Cyber Security & Cyber Analytics

Fortunately, cyber security can help organizations by providing an essential layer of cyber analytics to enhance existing security defences. Big data analytics has a place in just about all environments, not least of all security. Enhancing cloud data security, device security, platform security, and much more, cyber analytics used to the advantage of cyber security delivers insights into security gaps existing in systems, exposes breaches which have already occurred, and identifies areas which may be more prone to attack. SAS Cybersecurity is one solution that puts an organization’s information to use countering cyber attacks, putting the advanced and predictive analytics in the hands of the experts. By implementing a trusted and dexterous cyber security solution, network visibility can be magnified, threats quickly identified and acted upon, and data appropriately whittled down for more accurate analysis and recognition of risks.

Data privacy and security should always be a top priority, but when the necessary steps are taken it needn’t cause sleepless nights. Although it’s always advantageous to have as much information as possible, the IT security landscape is too broad for all of us to be specialists. Implementing the right solutions negates risks and vulnerabilities and leaves companies free to focus on their core activities.

Article sponsored by SAS Software and Big Data Forum

By Jennifer Klostermann

THE GOLDEN AGE OF WEARABLE TECHNOLOGY

THE GOLDEN AGE OF WEARABLE TECHNOLOGY

The Golden Age

One of the biggest fads in the technology sector right now is wearable tech. From Smartwatches that let you check your emails, chat with friends and search the web, to fitness accessories that monitor your heart rate and your sleep patterns, this is truly the Golden Age of wearable technology.

But some of these innovations are older than you think. Virtual Reality sets like Oculus and VR Lite can trace their origins back to 1963. This is when the idea of bringing the TV screen to you in order to create more depth and more immersion was first proposed. In the 1970s, the first calculator watch was created, and while this is someway from the Apple Watch, the beginnings are there and this was a huge innovation at the time.

(Infographic discovered via Siliconrepublic)

The-History-Of-Wearable-Tech

We may be living in an age that is dominated by technology, but a lot of the ideas that you think are new were actually formed many years or generations ago. The Tablet is a perfect example of this. We all think of the Apple iPad as the first tablet, but the name “Tablet PC” was actually coined by Microsoft, who released a similar device back in 1999. And even this device was predated by the Palm Pilot, the Newton and several other mobile PCs.

Of course, for every game-changing invention, there are a few obscure, baffling inventions that really shouldn’t have made it off the drawing board. And as this infographic proves, there have been no shortage of those throughout the last few hundred years.

By David Jester

MARKETING EXECS BEEFING UP ON MARTECH STRATEGIES

MARKETING EXECS BEEFING UP ON MARTECH STRATEGIES

Martech Strategies

As budgets shift from traditional marketing streams to marketing technology, it’s essential that both marketers and business leaders understand marketing technology and keep up with the developments. According to eMarketer, 78% of US senior marketers surveyed believe gaining this understanding of marketing technology is increasingly relevant to their success, and the majority of Western European senior marketers feel the same way. With global spending by advertising and marketing professionals increasing on data-driven activities, it’s necessary to develop a strong appreciation of the fundamentals of marketing technology, while keeping an eye on all of the latest trends and developments.

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Identifying Valuable Customers

Customer satisfaction has long been recognized as a leading factor in business success, but identifying the most valuable customers can enable business strategies which yield even greater profits. Peter Fader, marketing professor at Wharton, has developed the Customer Lifetime Value metric which estimates likely future spend by customers based on past buying trends, enabling companies to target those customers most attuned to their brand. Similar predictive analytics models are available as part of marketing technology platforms and solutions, putting the masses of customer data collected to better use.

Internet of Things (IoT)

Many senior marketers also recognize the value of IoT, and it’s likely this popular technology will assist in its evolution. It may be difficult to imagine a world more connected than we already see today, but with the increasing development and adoption of IoT devices that’s exactly what’s in store. And as these IoT device developmentscontinue, so too advances the connections, providing individuals with greater convenience and industries with even more customer-specific data. Correctly applied, marketers are able to connect phenomenal amounts of behavior data about current and prospective customers through IoT devices, and though today tracking is mostly of buying behaviors, in the future we’re likely to furnish marketers with details so personal that personalized advertising might feel more like the pertinent advice of a close friend.

Augmented Reality (AR)

Initially focused on the gaming industry, we’re becoming more accustomed to seeing virtual reality in our daily lives. But augmented reality, the display of a virtual world over the real world, is proving to have its own unique advantages. Consider Pokemon GO, a meteoric success story that’s left developer Nintendo able to pull audiences to chosen locations at will. For the marketer, using augmented reality in advertising campaigns could mean placing targeted AR advertising over real world advertising, floating AR banner ads in the skies above us, and popping relevant AR pamphlets into view at just the right time, in just the right place.

Artificial Intelligence

A key area in marketing is, and always has been, customer service, but the expectations of customers today are far grander than those of customers 20 years ago. We expect constant, always-on, personality-attuned attention, and so the cost of top-quality customer services reps is skyrocketing. A few businesses are ‘peopling’ their service centers with robots, particularly useful for the less complex interactions. However, with the developments we’re seeing in artificial intelligence, these robots are becoming far smarter and are even imbued with emotional intelligence which helps with the detection of sarcasm and allows for tailored responses. Moreover, because artificial intelligence allows robots to continuously learn from their interactions they become better able to understand and assist customers the more they’re used.

The promise is near limitless, and it’s important to recognize that such martech tools aren’t only for big business. Small and medium enterprises are already putting innovative solutions in place. Collecting and analyzing data, and then utilizing data insights, helps improve customer targeting and engagement and once over the initial bewilderment of all such technology can offer, it’s an exciting arena to be involved in.

By Jennifer Klostermann

4 MONETIZATION MODELS FOR THE DIGITAL BUSINESS ERA

4 MONETIZATION MODELS FOR THE DIGITAL BUSINESS ERA

4 Monetization Models

Digital business is expected to generate billions in new revenue in the next four to five years. However, MGI Research predicts that digital businesses will need to increase their time to market by 40 percent. Many global executives admit they are unprepared to monetize their operations. The million dollar question is: how do you get from here to there?

Getting there requires adopting a new mindset that focuses on “revenue moments” instead of product sales. Revenue moments can occur whenever a customer interacts with your company through product, website, email, billing, servicing, provisioning, or other similar activity. For example, when a customer is notified that they are reaching a usage threshold on their plan, you offer them a plan upgrade. The good news is that there are hundreds of potential touch points that provide opportunities for customers to purchase additional upgraded services. Each of these interstitial points of connection with your consumer gives your business the opportunity to build customer lifetime value (CLV)—a key metric in measuring the health of your recurring business. Over time, this method of strengthening your customer relationship—which can be as significant and long-lasting as a marriage— not only increases profitability, but also cements customer loyalty to your brand.

In a recurring revenue model, monetizing your business goes way beyond exchanging products and services for money. You must leverage each and every revenue moment. Only then will you maximize customer lifetime value (CLV), retain more customers, and leave the door open for existing customers to buy more of what you’re selling.

Yet, retention starts with customer acquisition. Choosing an enticing monetization model that is also well suited to your business is key. Here are four popular ones worth considering:

  1. One-Time

This is the tried-and-true way to sell. Cash is exchanged for goods and services, and the buyer and seller part ways. But there’s a lot that remains unknown: Will the buyer come back? Who knows? One-time transactions depend heavily on constantly luring new customers and direct-contact methods of bringing old customers back, both of which are prohibitively expensive.

Pros: This model is widely known and used. Cons: Your business always starts at zero.

  1. Flat-Rate Subscription

In this basic entry into recurring revenue, the customer receives a good or service, like software or magazines, and they pay the same amount every month to receive or use it. With subscriptions, a high percentage of customers are retained, and their CLV can immediately be added to the bottom line. The good news is that retaining a customer also costs up to 10 times less than acquiring a new one.

Pros: The flat-rate subscription model increases CLV. Cons: It can be a limited, one-size-fits-all solution.

  1. Usage Based

Usage, or consumption based monetization is used for everything from car sharing to cellular data. Pay for what is used, no more, no less. Usage-based business is usually done on a membership or contract basis, so the recurring revenue and increased CLV that comes with subscriptions usually applies here too.

Pros: Usage-based services are a fair and easy way for the customer to buy your product with a low cost of entry and very low risk. Cons: Usage-based recurring revenue is not guaranteed. Usage can also vary, making revenue difficult to predict.

  1. Tiered

Tiered pricing can be based on usage (price per unit increases or decreases with usage). It can be offered along with additional features and levels of quality (silver, gold, platinum) or a combination of the two. The increasing price model is applied to reduce usage (think water and power). The decreasing price model can encourage customers to buy more, but pay less per unit. For example, for cloud storage, you might pay $.029 per GB up to 1TB, but you pay $.019 per GB for 1TB or more.

Pros: Tiered models provide more choice for customers, and more opportunities for revenue moments and additional revenue. Cons: Basic billing systems and many homegrown solutions may not be able to handle complex hybrid models, and customer service is more difficult without an integrated, single source for customer information.

What’s Right for Your Business?

Unless you are selling houses, one-time transactions are probably not the best way to sell your product. When you look at using any of the other models, you have to think about your technology and the processes necessary to handle the sophisticated transactions.

It may seem complex to pull off, but the end game is simple really. The goal is to serve the customer and create the best experience for them. To do so you’ll need to make sure all factions of the company and resources are aligned. With that in place, both your customer and business stand to gain.

Think of your digital business like any good marriage, you want to make sure that your partner (in this case, the customer) has excellent experiences with you to remember over the years. That will strengthen your commitment to each other, so you’ll live happily (and profitably) ever after.

By Tom Dibble

CYBERSECURITY EXPERTS RACING TO KEEP PACE WITH GROWING CYBER THREATS

CYBERSECURITY EXPERTS RACING TO KEEP PACE WITH GROWING CYBER THREATS

The cyberwar is on!

At this stage of the game, the stakes are higher than ever, and safeguarding networks from cyberattacks is a devilish combination of Chicken and Cat-and-Mouse. Attacks are now so commonplace that many events of serious cybersecurity breaches go uncovered by mainstream media.

Despite the rapid advancements in IT security technology, hackers continue to invent even more sophisticated ways of infiltrating systems around the globe. No one is safe—and although the awareness is there, and the threats are very real, some companies still think they are safe and have it covered.

The fact is that it is second by second battle. Entire global networks can be comprised by a single click of the mouse or the press of a button at any given time. Everything is at risk: content, data and network security concerns for businesses, consumers and even governments. Although cyberterrorists always seem to find a way in, leaving the experts scratching their heads, the outlook is not at all as grim as one might suspect.

According to an August 22, 2016 article on Forbes.com magazine, “3 Hot Cybersecurity Stocks,” hacking is now a global growth industry! The cyberwar is on, which is why cybersecurity is the fastest growing sector in technology today. Not only do the good guys want to stop the bad guys—they want to make a profit doing it. It is a win-win from a business standpoint. Attached is an attractive security infographic discovered via IDG Enterprise.

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Close to 170 cyber attacks against corporations and other industry leaders have been documented by Privacy Rights Clearing House thus far in 2016. The massive breach upon DNC leading the pack as one of the most shocking.

What Companies Should Be Doing

Upwards of 40 percent of investment firms reported increasing the budget for cybersecurity for the year. Given the state of matters, IT security experts have a lot to say to those firms lagging behind. Cybersecurity is a daily investment every company can’t afford not to make.

From small startups to large corporations, everyone in business needs to put network and system security at the top of their priority list. The areas most in need of heightened security are application encryption, event and information management systems, user access management, data-at-rest defenses, and tokenization (the process of substituting a sensitive data element with a non-sensitive equivalent).

Even the little guy on the block should invest in professional IT security management. Your neighbor who just graduated from an online cybersecurity school might not have the chops under his belt to keep up with the lightning speed this cyberwar is gaining. You need serious guards against serious attackers who take no prisoners and spare nothing to get at information and control, sometimes just for the fun of it.

By CJ Callen

6 REASONS WHY BIG DATA ANALYTICS IS A SMART CAREER CHOICE IN 2017

6 REASONS WHY BIG DATA ANALYTICS IS A SMART CAREER CHOICE IN 2017

Big Data Analytics Career Path

With the inception of Big Data, we have witnessed a data revolution around us. Big Data Analytics is one of the biggest trends in IT sector at the moment and the buzz around it is not going to subdue anytime soon. Big Data is everywhere now-a-days, and if the industry forecasts are to be believed, then Big Data Analytics market will continue to grow bigger as businesses realize the importance of making data-driven decisions.

Wondering whether to take up a career in Big Data Analytics or not? If you are not convinced yet, then here are 6 reasons why making the switch to Big Data Analytics is a smart career move in 2017.

1. Exponential Growth Rate

Big Data sector has recorded six times faster growth than the average growth rate of IT industry in the past couple of years. According to the market experts, Big Data sector would sustain the momentum and continue to outpace other IT sectors by a significant margin in the years to come. Currently the size of Big Data Analytics market is around one-tenth of the global IT market, but it is expected to evolve to at least one-third by the end of 2020. So if you are looking to make a career in one of the fastest growing IT sectors, there is no better alternative than Big Data Analytics.

2. Soaring Demand for Qualified Professionals

Big Data initiatives were once reserved only for the giants like Microsoft and Amazon. That’s not the case anymore. Today, organizations of all sizes are venturing out to leverage the power of Big Data. As more and more IT companies are getting involved in Big Data projects, currently there is a big demand for engineers who can help process data at large-scale.

A closer look at the prominent job sites can give you a sense of the huge demand. There has been a steady increase in the number of job opportunities related to Big Data Analytics and the trend is still swinging upwards. It’s no wonder that qualified Big Data professionals are becoming the hottest targets of IT recruiters from all around the globe.

3. Lack of Skilled Professionals

Data is useless without the skill to process and analyze it. Being a relatively young field, the Big Data sector is currently witnessing severe shortage of technical expertise. While the demand is going up steadily, there is a huge deficit on the supply side. Lots of vacant positions have remained unfilled due to the scarcity of skilled professionals. In an industry where opportunities are plenty but skills are scarce, finding a suitable job shouldn’t be too difficult for the candidates having the right qualification.

4. Fat Paychecks

Thanks to the inadequate supply of Big Data skills, companies are willing to shell out lucrative salaries to attract professionals with the right kind of technical expertise. A quick look at the current salary trend for Big Data professionals indicates an exponential growth. According to a recent survey conducted by US-based recruitment agency Burtch Works, Big Data professionals tend to be the highest compensated group of IT employees with an average salary of $115,000 – which is around 30% more than that of other IT professionals with the same experience level.

5. Adaptation Across Different Industry Verticals

The astonishing growth of Big Data is largely attributed to its relevance across different industry verticals. All types of businesses can use the insights derived from Big Data to get an edge over their competitors. Besides the technology sector, Big Data is increasingly being utilized by other industry verticals for business intelligence, predictive analytics and data mining tasks.

Healthcare, consumer appliances, energy sector, manufacturing industry, and banking are a few of the verticals where Big Data has made its presence felt. As a result, the rate of Big Data implementation has increased by leaps and bounds. So the professionals with Big Data expertise can choose which industry to work for, based on their own preferences.

6. Wide Range of Roles and Responsibilities

Last, but not the least, Big Data professionals have a wide variety of positions to choose from. From Data Engineer to Business Analyst, Visualization Specialist to Machine Learning Expert, and Analytics Consultant to Solution Architect – there are so many options available for the aspiring professionals to align their career paths according to their interests and preferences.

Conclusion: Big Data Analytics help organizations derive meaningful insights from raw data to make the right business decisions at the right time. In today’s competitive job market, technology professionals with the right kind of skill-set are finding themselves in high demand as businesses look to harness the power of Big Data. With the increase in demand, shortage of talent, bigger paychecks, multiple job titles and relevance to different industry verticals, Big Data Analytics is certainly a smart career choice in 2017.

By Jack Danielson

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Cost of the Cloud: Is It Really Worth It?

Cost of the Cloud: Is It Really Worth It?

Cost of the Cloud Cloud computing is more than just another storage tier. Imagine if you’re able to scale up 10x just to handle seasonal volumes or rely on a true disaster-recovery solution without upfront capital. Although the pay-as-you-go pricing model of cloud computing makes it a noticeable expense, it’s the only solution for many…

Disaster Recovery – A Thing Of The Past!

Disaster Recovery – A Thing Of The Past!

Disaster Recovery  Ok, ok – I understand most of you are saying disaster recovery (DR) is still a critical aspect of running any type of operations. After all – we need to secure our future operations in case of disaster. Sure – that is still the case but things are changing – fast. There are…

What the Dyn DDoS Attacks Taught Us About Cloud-Only EFSS

What the Dyn DDoS Attacks Taught Us About Cloud-Only EFSS

DDoS Attacks October 21st, 2016 went into the annals of Internet history for the large scale Distributed Denial of Service (DDoS) attacks that made popular Internet properties like Twitter, SoundCloud, Spotify and Box inaccessible to many users in the US. The DDoS attack happened in three waves targeting DNS service provider Dyn, resulting in a total of about…

Choosing IaaS or a Cloud-Enabled Managed Hosting Provider?

Choosing IaaS or a Cloud-Enabled Managed Hosting Provider?

There is a Difference – So Stop Comparing We are all familiar with the old saying “That’s like comparing apples to oranges” and though we learned this lesson during our early years we somehow seem to discount this idiom when discussing the Cloud. Specifically, IT buyers often feel justified when comparing the cost of a…

Cloud-Based or On-Premise ERP Deployment? Find Out

Cloud-Based or On-Premise ERP Deployment? Find Out

ERP Deployment You know how ERP deployment can improve processes within your supply chain, and the things to keep in mind when implementing an ERP system. But do you know if cloud-based or on-premise ERP deployment is better for your company or industry? While cloud computing is becoming more and more popular, it is worth…

Is Machine Learning Making Your Data Scientists Obsolete?

Is Machine Learning Making Your Data Scientists Obsolete?

Machine Learning and Data Scientists In a recent study, almost all the businesses surveyed stated that big data analytics were fundamental to their business strategies. Although the field of computer and information research scientists is growing faster than any other occupation, the increasing applicability of data science across business sectors is leading to an exponential…