In 2016, blockchain technology came close to hitting its peak on Gartner’s annual Hype Cycle, signaling an imminent shift from an emerging, theoretical technology to widespread adoption. Like cloud, big data, and the Internet of Things (IoT) before it, blockchain is the tech industry’s latest Next Big Thing. Analysts and industry experts say it holds immense potential for organizations, but many business leaders don’t yet see a practical application for their operations. While a lot of people know blockchain is the technology behind Bitcoin, Ethereum, and other cryptocurrencies, what about enterprise applications in other industries?

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MongoDB Atlas leverages VPC peering for AWS, a service that allows multiple VPC networks to interact. This includes VPCs that belong to other AWS account holders. By performing cross account VPC peering, users ensure networks that host and communicate their data are secure.
In his session at 20th Cloud Expo, Jay Gordon, a Developer Advocate at MongoDB, will explain how to properly architect your VPC using existing AWS tools and then peer with your MongoDB Atlas cluster. He’ll discuss the security advantages you immediately gain, easier configuration of whitelisting networks and potential cost savings on bandwidth.

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Imagine having the ability to leverage all of your current technology and to be able to compose it into one resource pool. Now imagine, as your business grows, not having to deploy a complete new appliance to scale your infrastructure. Also imagine a true multi-cloud capability that allows live migration without any modification between cloud environments regardless of whether that cloud is your private cloud or your public AWS, Azure or Google instance. Now think of a world that is not locked into that rigid appliance vendor or specific public cloud provider, where all silos are now unified into one. No longer do you have to imagine as that is Composable Infrastructure.

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In his session at Cloud Expo, Alan Winters, an entertainment executive/TV producer turned serial entrepreneur, will present a success story of an entrepreneur who has both suffered through and benefited from offshore development across multiple businesses:
The smart choice, or how to select the right offshore development partner
Warning signs, or how to minimize chances of making the wrong choice
Collaboration, or how to establish the most effective work processes
Budget control, or how to maximize project results within possible constraints

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As more and more traditionally slower-moving industries start to move their resources to the cloud, an interesting note from Evolve IP: healthcare IT professionals believe their data is safer in the cloud than on-premises when faced with a hardware issue or environmental disaster.

The report, which surveyed 180 healthcare professionals, found that for environmental disasters, 61% of respondents felt their information was safest in a private cloud, compared to 27.5% for a private cloud and 11.5% on premise, while for malicious attacks and hardware malfunctions 58.5% each also preferred a private cloud. Interestingly, for attacks on premise (32%) was significantly the second most popular option.

Healthcare organisations have on average between two and three services in the cloud with data backup, servers and data centres being the most widely deployed services. 85% of all organisations polled said they had at least one service in the cloud, while more than four in five respondents (81%) say they plan on adding new or additional cloud services in the next three years.

The research also found that rollouts had not been a universal success, however. Almost two in five said they had deployed a cloud solution on their own as opposed to using a third party provider – lower than the figure for all industries – with a third (32.5%) admitting they would outsource to a solution provider given the chance next time.

One of the key elements for healthcare organisations moving to the cloud is HIPAA accreditation; 85% of respondents said they were aligned with HIPAA requirements, with a further 32% also citing PCI (payment card industry) compliance.

Writing for this publication last year, Karin Ratchinsky, director of vertical marketing strategy at Level 3 Communications – since acquired by CenturyLink – argued that while using cloud-based technologies for back end functions was steadily rising, the use cases elsewhere were similarly important. “Healthcare leaders want to funnel capital into cash flow-generating activities that allow them to deliver improved outcomes,” Ratchinsky wrote.

“Cloud computing lets healthcare organisations focus on healthcare rather than data centres, digital real estate to house them, and skilled professionals to maintain and operate them.”

A recent report from Gartner predicts that 40% of data science tasks will become automated by 2020. Since the data science skills gap has been a concerning topic over the past few years, this news comes as a relief to some.

It was Gartner who said, back in 2012, that by 2020 there will be a shortage of 100,000 data scientists. The new report has prompted some to wonder what exactly is the future of jobs in data science and what will the field look like in coming years. To understand where data science is heading, it’s important to understand first what parts of data science can and will be automated and also understand the tasks that won’t be automated in the coming years.

Data science tasks that will be automated

According to the report, certain tasks are set to automate in the coming years: «With data science continuing to emerge as a powerful differentiator across industries, almost every data and analytics software platform vendor is now focused on making simplification a top goal through the automation of various tasks, such as data integration and model building.»

Simplification is key for data scientists. Automating mundane and repetitive tasks frees up employee time to work on more complex algorithms.

Data integration, for example, combines data from multiple sources and provides a unified look at the data as a whole. This process can and should be automated, in order to quickly pull together trusted data from multiple sources so that a skilled data scientist can analyse the results.

Model building involves collecting data, analysing and searching for patterns, and using data to make predictions. There are already tools that can automate model building – machines can collect data and point out patterns. Furthermore, these tools are becoming smarter, in that they are learning what type of patterns to detect.

Machine learning and automation are already impacting data integration and model building, helping data scientists complete jobs faster and more effectively. A machine does not have the error risk that humans have, so for tasks such as these, automation is vital.

Data science tasks that can’t be automated yet

Artificial intelligence (AI) can only go so far. Right now the technology is not quite there to automate the majority of data science tasks.

Data wrangling, for example, is the process of manually converting “raw” data into another form that is easily consumed. Data wrangling, also known as data munging, takes good judgement from a human – a concept AI tools don’t have quite yet.

Data interpretation and visualisation will not become automated in the sense that there will always be people that need to walk executives through the data for understanding. Only then can leaders make data-driven decisions for the good of the company.

Aspects of data visualisation may become automated in the future. Since more and more data is being produced at a rapid rate, the human workforce simply cannot keep up with the demand. Low-level pieces of data visualisation can be automated, but there will always be human intelligence factor needed to interpret and explain the data itself. Humans are still needed to write the various AI agents that can soon take over the mundane data science tasks as well.

The future of data science in the age of automation

So will data science tasks become automated? Certain aspects of low-level data science can and should be automated. Data collection and combining data takes valuable time away from trained experts, but there are many tools out there that help to automate all or parts of these tasks.

However, AI tools do not yet have human curiosity or the desire to create and validate experiments. That part of data science most likely will never be automated in our lifetime, simply because the technology has a long way to go.

Data scientists who are advancing in their field should not fear unemployment in the near future. Data scientists are typically programmers, mathematicians, and thought leaders all wrapped up in one, so no matter where the industry goes, it is unlikely someone with those qualifications will be on the job hunt for too long. More importantly, humans will still be needed to understand and collaborate with other humans for data science projects to be successful. This collaboration is key to transforming data into actionable data for decision-making.

Data science will scale thanks to automation tools, and data scientists will be able to work more efficiently and effectively. But human intelligence is still very much needed in this field, so though automation will and should help, it cannot completely take over.

If there is one thing we can be certain about when it comes to cybersecurity, it’s that the landscape will remain dynamic and turbulent over the coming years. Today, news headlines are dominated by cyberattacks and breaches that span across all industries – causing security to be top of mind for almost all businesses. However, these headlines don’t seem to be slowing down, which means that businesses are still struggling to keep up with the rapidly evolving threat landscape.

So, what are the biggest obstacles businesses face in achieving a stronger cybersecurity posture, and how are MSPs best suited to help clients and prospects overcome these obstacles?

Cybersecurity Insiders’ 2017 Cybersecurity Trends Report recently uncovered that lack of skilled employees, lack of budget and lack of security awareness among employees are the three biggest cybersecurity challenges for businesses. Let’s break these down one by one.

Lack of skill

The problem: Finding qualified talent remains an ongoing challenge in the business world – specifically when it comes to IT security. In the report, 45 percent of respondents list lack of skilled employees as the first major obstacle to achieving stronger cybersecurity. It’s clear that cybersecurity is a rising concern today, but why is it still so difficult for businesses to find and retain security talent? For some, this can be attributed to the lack of training, certification, or even hands-on experience, while others believe that conventional education and policies simply can’t meet demand. Nevertheless, lack of skill has become a major obstacle in preventing businesses from achieving stronger cybersecurity.

In fact, this will remain a major obstacle for businesses because it’s estimated that by 2019, 1 to 2 million cybersecurity jobs will remain unfilled. The struggle to find employees with the right security skill set is plaguing businesses, including the small- and medium-sized businesses (SMBs) that you serve. More often than not, these businesses don’t have the necessary resources or bandwidth to support their cybersecurity needs. Unfortunately, this leaves them very vulnerable to attack.

The solution: To address this skills gap, SMBs can leverage a managed services provider who has the appropriate technology, level of skill, experience and understanding of IT systems. Your clients won’t have to worry about learning curves or lacking the right IT skills because they’ll have access to your team of highly-trained technicians. With 24x7x365 monitoring and support, any issues that arise will be promptly remediated and taken care of. Additionally, the preventative solutions you provide, such as remote monitoring and management (RMM) and antivirus, will help bolster your clients’ cybersecurity defences and reduce their vulnerability to threats.

By leveraging your IT services, your SMB clients will have peace of mind knowing that you’ll always be working in the background to monitor and manage their IT systems, scan for any malicious activity and ensure that their network and endpoints remain secure.

Lack of budget

The problem: No matter the issue, lack of financial resources always seems to be a major roadblock for businesses. Although we’re seeing a slow increase in the investment of cybersecurity, 45 percent of respondents still list lack of budget as the next major obstacle to achieving stronger cybersecurity. The problem is that cybersecurity spending is still not at a level that matches the changing threat landscape.

Often, security budgets are hard won because you can’t see the results right away – it’s more about protecting against future issues. And for SMBs especially, financial resources are already limited, which means that not having the budget to invest in stronger cybersecurity can make them much easier targets.

The solution: Fortunately, one of the biggest values of managed services is greater cost savings. Instead of spending thousands of dollars on security hardware and software, your clients can leverage your technology, services and expertise – all at a fixed monthly cost. Also, when SMBs outsource their IT security needs to an MSP, they won’t have to deal with the added costs of onboarding new employees, training processes or paying for their benefits.

By handing off some of these needs to a trusted technology partner, SMBs can free up time for their in-house staff to think more strategically – which, in turn, increases profitability. Overall, an MSP can provide businesses with scalable IT services that can be customized to their needs, fit within their budget and keep them protected against current and future threats.

Lack of security awareness

The problem: In a perfect world, employees would act as a company’s most effective security defense. However, this is not a perfect world. Sometimes the greatest vulnerabilities are created by employees who did not receive proper security awareness training. We all know that human error has been responsible for some of the worst data breaches, and this happens mostly when security training is an afterthought. In fact, 40 percent of respondents say that lack of security awareness among employees is the third highest obstacle to strengthening cybersecurity. Organizations could risk their reputation, customer trust, and potentially their bottom lines when employees aren’t properly trained and end up mishandling data or falling for a phishing attack.

The solution: Working with an MSP is one of the best ways to overcome this obstacle. It’s in an MSPs nature to stay up-to-date on today’s threats so that they can provide the security awareness education employees need to guard against malicious schemes.

In working with an MSP, clients will have continuous support for not only their IT systems, but also their security-related planning, procedures and protocol. MSPs work with standards such as PCI compliance day in, day out, and should be able to steer clients within the specific parameters and regulations they need to adhere to. All in all, leveraging the knowledge and expertise of an MSP can allow businesses to close the security awareness gap and ensure that they’re well-equipped to face the cybersecurity landscape – with both internal and external defences. 

Need additional help? Continuum’s Cybersecurity Sales Success Kit: 2017 Edition provides you with custom, white-label content you can leverage to tailor your pitch and grow revenue for your security offering. Download the kit here.

The article ‘Overcoming Cybersecurity Challenges with Managed IT Services’ first appeared on Continuum Blog.

Lots of cloud technology predictions and analysis are still dealing with future spending and planning, but there are plenty of real-world cloud use cases and implementations happening now. One approach, taken by stalwart GE, is to use SaaS applications for non-differentiated uses. For them, that means moving functions like HR, finance, taxes and scheduling to SaaS, while spending their software development time and resources on the core apps that make GE better, such as inventory, planning and sales. Essentially, as for more and more large enterprises, GE is getting out of the infrastructure business.

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