Cyber Security Advice for Medical Practices

The sudden increase in cyberattacks happening all around the world is not without its reasons. More than 80% of information – including private details about ourselves – are now stored digitally. Every information is valuable to attackers, which is why we are now seeing more attacks as well as new forms of attacks targeting individuals and large corporations.Cybersecurity for medical practice

For medical practices, information security is essential. Patient information and details about the practice’s operations are too valuable to handle carelessly. There are ways to improve cybersecurity throughout your medical practice and we are going to discuss some of them in this article.

Follow the Standards

The healthcare industry is highly regulated down to the last letter and information security is no exception. The HIPAA medical information security guidelines are something that every healthcare service provider must follow.

Fortunately, most solutions available to the industry already take HIPAA compliance very seriously. You know you can count on the software, devices, and other solutions that comply with HIPAA to safeguard your information. Following the correct security standards is a great first step to take.

Secure the Equipment

Using the correct, well-secured equipment is another must. You can’t count on poorly secured equipment, especially in today’s world where attacks to IoT and electronic devices are more common than ever. Similar to choosing software and solutions, there are standards to follow.

According to Rishin Patel Insight Medical Partners’ President and CEO, newer equipment is designed to be more secure from the ground up, especially compared to older alternatives. His company provides easy access to the most advanced products and technologies so that medical practices can remain safe and protected.

Have a Backup Routine

To have a strong information security foundation, the third thing you need to add is a good backup routine. Maintain on-site and off-site (cloud) backups of sensitive information so that your medical practice can recover from catastrophic cyberattack seamlessly.

In the event of a ransomware attack, for instance, you can wipe your computers and restore essential data from various sources. When hardware fails, there is still a cloud backup to turn to. Adding a good backup routine to the practice’s everyday workflow completes the equation and provides your medical practice with a good security foundation.

Train the People

Once the foundation is laid, it is time to tackle the biggest information security challenge of them all: the people. Bad habits like using a weak or common password, exchanging login information or user access with coworkers, clicking URLs from illegitimate sources, and copying data to a flash drive and then not handling it properly are still the most common causes of cyberattacks.

It is imperative that the people involved in handling information know how to handle information securely. Information security trainings are great for changing some of the more common bad habits quickly. As an extra layer of security, putting in place a set of security policies is also highly recommended.

There are still so many things you can do to protect your medical practice from cyberattacks, but these first steps are the ones to take to get started. Be sure to implement these measures immediately before your practice becomes the victim of a cyberattack.


NewPush Recognized as Top 20 VMware Cloud provider 2016

CIO Review recognition

NewPush started using VMware technologies from its inception in 1999. At the time the first dot com boom was just heating up. Many virtualization technologies were emerging for the Intel platform. Over the years we kept focusing on providing enterprise grade infrastructure. Meanwhile, we have kept increasing the role of VMware as we understood that for Intel based hardware VMware provided the most reliable enterprise soluitons. As a result, we have moved the use of VMware from our development labs to our production systems and data-centers. Since the 2010’s we are formally a VMware partner providing VMware Cloud solutions. Most noteworthy, the last few years have shown a tremendous growth in the capabilities VMware Cloud delivers. Therefore it is our pleasure to announce that CIO Review has recognized NewPush as a top 20 VMware technology provider.
20 most promising VMware Cloud solution providers - 2016

VMware Cloud Solutions

Important milestone for NewPush

This recognition is a milestone that is important to us. We have worked hard to pioneer and to be successful deploying state of the art VMware based cloud technologies. Our recent work focuses on NSX, vSAN, and the vRealize suite. As we continue our quest to provide the best cloud services to our customers, we look forward to deploy the new Docker and Hadoop enablement technologies.

Looking ahead

Cloud technologies keep changing at an ever increasing pace. Companies who stay ahead are going to continue to have a competitive advantage, by providing a better customer experience. By partnering for technology decisions with NewPush, you can spend more time with your core business, while ensuring that you have a trusted partner with a proven track record to help you keep a competitive edge on the IT front. If you would like the NewPush advantage for your company, please do not hesitate to get in touch today. We are here to help 24 hours a day, seven days a week.


Customer Journey Analytics: Mining Behavioral Data to Boost Retail Sales

by Barbara Thau –

Customer journey analytics examines an increasingly complex path in the modern retail landscape. Today’s typical path to purchase includes not only in-store interactions, but also online research and browsing, as well as mobile actions. Research shows that 56 percent of modern customer engagements take place over multiple days across multiple channels.

This evolving journey from initial interaction to purchase makes it hard for retailers to gain definitive insights on consumers. According to eMarketer, 35 percent of marketers admit that they don’t understand the customer journey and more than 60 percent said their incomplete data prevents them from personalizing communications.

For this reason, retailers are increasingly turning to data analytics for a nuanced read on shoppers’ distinct purchasing paths. Companies that tap into insights from behavioral data have the opportunity to customize merchandise offers, drive store loyalty and boost sales and profit margins.

Retailers struggle with customer analytics

Behavioral data and other customer analytics can be extremely influential when retailers are revamping marketing or operational strategies, yet many companies still struggle to effectively gather and parse this information.

“Many [retailers] still do not leverage customer analytics for operational decisions, often because of a lack of fully integrated customer data as well as integration into other operational data,” Dave Nash, director of customer experience at West Monroe Partners, explained to CMSWire.

Companies need a solution that allows them to collect data through all steps of the buying journey, from the first brand interaction to online browsing, social media interactions, mobile application use and ultimately purchase, whether it’s online or in store. Only by aggregating and analyzing this information will retailers be able to fully map purchase paths. As a result, many organizations are adopting advanced customer journey analytics solutions.

 

Read more here:

http://www.ibmbigdatahub.com/blog/customer-journey-analytics-mining-behavioral-data-boost-retail-sales


Opting for a Big Data as a Service Solution

By Raymie Stata –

As organizations work to make big data broadly available in the form of easily consumable analytics, they should consider outsourcing functions to the cloud. By opting for a Big Data as a Service solution that handles the resource-intensive and time-intensive operational aspects of big data technologies such as Hadoop, Spark, Hive and more, enterprises can focus on the benefits of big data and less on the grunt work.

The advent of big data raises fundamental questions about how organizations can embrace its potential, bring its value to greater parts of the organization and incorporate that data with pre-existing enterprise data stores, such as enterprise data warehouses (EDWs) and data marts.

The dominant big data technology in commercial use today is Apache Hadoop. It’s used alongside other technologies that are part of the greater Hadoop ecosystem, such as the Apache Spark in-memory processing engine, the Apache Hive data warehouse infrastructure, and the Apache HBase NoSQL storage system.

In order for enterprises to include big data in their core enterprise data architecture, adaptation of and investment in Big Data as a Service technologies are required. A modern data architecture suited for today’s demands should be comprised of the following components:

* High-performance, analytic-ready data store on Hadoop.  How can big data be speedy and analysis-ready? A best practice for building an analysis-friendly big data environment is to create an analytic data store that loads the most commonly used datasets from the Hadoop data lake and structures them into dimensional models. With an analytic-ready data store on top of Hadoop, organizations can get the fastest response to queries. These models are easy for business users to understand, and they facilitate the exploration of how business contexts change over time.

This analytic data store must not only support reporting for the known-use cases, but also exploratory analysis for unplanned scenarios. The process should be seamless to the user, eliminating the need to know whether to query the analytic data store or Hadoop directly.

 

Read more here:

http://www.networkworld.com/article/3032528/big-data-business-intelligence/big-data-as-a-service-delivers-the-analytics-benefts-without-the-grunt-work.html

 

 


Data Security – the Trends We Do Not See Coming

By Stephane Ibos –

With the emergence of the Internet of Things (IoT) and the continuous growth of cloud adoption among small businesses and large corporations, it is no wonder that the security industry is going through an unprecedented time of challenge and re-invention. But if we were to focus on data security alone, what would we recognize as the emerging trends and needs?

Cloudifying the Security

This is an interesting paradigm. It is all about providing Security as a Service (SECaaS), which is essentially an outsourcing model for security management. The irony lies within the fact that SECaaS will use the cloud as a mainstream deployment platform, when part of its own reason of existence is to enhance the protection of…the cloud!

SECaaS has evolved from delivery of a security software (such as an anti-virus) on a Software as a Service (SaaS) model to security management provided in-house by an external organization. Generally, large security service providers integrate their products into a corporate infrastructure on a subscription basis, making security more cost effective to large corporations.

The growing trend in the SECaaS sector is for the provisioning of authentication and security event management services, which brings SECaaS a step closer to Security at the Core – the ultimate objective of security implementation.

The benefit of SECaaS, aside from traditional cost savings, speed of deployment and ease of scaling inherent to cloud products, is continuous protection, due to the constantly updated threat databases.

Emerging players such as Cloudbric, CloudFlare and Incapsula are now offering SECaaS free of charge, therefore, challenging existing major players like Avast. Business models may change in this market in the coming years, with more traditional players having to adapt to remain competitive.

This trend will consist in broadening the scope of SECaaS, while strategic alliances and possible acquisitions may occur in the process.

 

Read more here:

http://themsphub.com/data-security-the-trends-we-do-not-see-coming/

 

 

 


Consumer Product Warranties

3 Ways Big Data Can Optimize Value

by Ritika Puri –

 

News of poor service reaches more than twice as many people as praise for a good experience, according to the White House Office of Consumer Affairs in a Better Business Bureau report. That’s why CPG brands need to see their sales through for years to come. With consumer product warranties, companies can back the value of the goods they sell. Shoppers, knowing that their purchases are covered, can rest assured that they’re safe from investments gone wrong.

The challenge, however, is optimization. It’s impossible for brands to know ahead of time whether or not a product will fail and generate unforeseen costs. Not to mention, consumers may not be aware of the warranties that come with their purchases. Here are three ways big data can help.

1. Synthesize field product performance

Sheila Brennan, a program manager for IDC Manufacturing Insights, explains that by “synthesizing field product performance, service and customer data from multiple sources,” companies will be able to detect potential problems earlier, optimize spare-parts planning and improve forecasting accuracy.

CPG leaders can reinvest this knowledge into product enhancements. When flaws are caught early enough, companies can make faster incremental changes to their product pipelines. Field product performance in the moment expedites information transmission through a big-data feedback loop.

Over time, this process will become faster and more efficient. The key is to use consumer product warranties as mechanisms to listen and learn.

2. Optimize price and duration

A paper in the Journal of High Technology Management points out that warranties fulfill two marketing needs. First, they offer promotional value in attesting to a product’s reliability. Second, they provide assurance to consumers who may experience post-purchase remorse.

There is, however, a tipping point where warranties stop being cost effective, and where expenses outweigh sales revenue. Determining an ideal time limit and coverage scope can feel like a game of darts in the dark. Over time, though, companies improve their precision.

Big data improves the prediction process. According the Journal of High Technology Management paper, by evaluating multiple variables such as optimal price and warranty length, analysts can estimate the overall maximum profit for a particular product. From there, organizations can build models to optimize warranty price points and durations.

 

Read more here:

http://www.ibmbigdatahub.com/blog/consumer-product-warranties-3-ways-big-data-can-optimize-value

Related content:

IoT Security: Prevention and Management Tips for CPG (by  Ritika Puri):

https://newpush.com/2016/02/internet-of-things-security-prevention-and-management-tips-for-cpg/

Consumer Goods Industry Trends: How Companies are Driving Product Sales via Big Data (by Barbara Thau):

https://newpush.com/2016/02/consumer-goods-industry-trends-how-companies-are-driving-product-sales-via-big-data/

 


Spark Takes on the Big Security Threats

by Peter Schlampp –

Amid an onslaught of ever more sophisticated cyber attacks, organizations everywhere are seeking enhanced cybersecurity capabilities that can help them respond to the growing threat to data. Understandably, then, businesses in a variety of sectors are turning to big data solutions such as Hadoop for help. Indeed, Hadoop, which is designed to handle data without respect to variety or volume, is the natural choice for an organization wishing to build an enterprise security solution that can manage a wide range of risks.

Using Apache Spark, businesses can enable a workflow that encompasses the full range of assets in a Hadoop environment, thus making behavioral analysis accessible as well as iterative. Indeed, Spark can obviate the need for many different and specialized resources, instead enabling self-service solutions that put core analytical capabilities directly into the hands of business analysts. Because a Spark-powered big data discovery environment can help provide the event series analysis and advanced segmentation capabilities on which analysts rely for security analysis, a Spark environment is uniquely equipped to address two of businesses’ most formidable security challenges: mitigation of new threats as they arise and detection of advanced persistent threats.

Mitigating emerging threats

In the modern business environment, organizations put in place a wide range of security mechanisms designed to prevent security breaches. Even so, breaches can occur. When a new threat emerges, everything depends on the timing and coordination of a company’s response. However, chief information security officers (CISOs) and their teams often lack the data and tools that can help them efficiently investigate and mitigate breaches, not least because in many organizations, information is scattered among multiple systems. In such an environment, security analysts must pivot among multiple data sources—network, endpoint, user behavior data and the like—to conduct a security investigation in which they can answer questions such as the following:

  • Which internal servers make connections to internationally based servers?
  • How has a user’s pattern of access to internal resources changed over the past year or month—or week, day or hour?
  • Which users have demonstrated abnormal patterns of behavior, such as by connecting using nonstandard ports or applications?..

 

Read more here:

http://www.ibmbigdatahub.com/blog/spark-takes-big-security-threats

Related content:

Becoming cognitive: A new disruptor remakes the business landscape (by James Kobielus):

http://www.ibmbigdatahub.com/blog/becoming-cognitive-new-disruptor-cognitive-computing-reorders-business-landscape

 


Reshaping the Business Analyst Experience

by Robert Routzahn –

Obtaining good data for use in business analytics has always presented challenges. From figuring out which data is needed to finding it to validating its accuracy, analysts spend considerable time just preparing for analysis rather than doing the analysis. A recent Forbes studyrevealed that while more than 80 percent of all organizations are prioritizing data analytics in their budgets, more than 40 percent of those same organizations report legacy system bottlenecks and poor data quality. That poor quality impedes the progress of those high-priority analytical projects.

This revelation indicates a significant return on investment (ROI) problem. The historical challenges an analyst faces intensify exponentially in a big data world containing multiple internal and external data sources of varying formats and data definitions, extremely high volumes of data to review and ongoing concerns about data security and privacy.

Experiencing the problem through the analyst’s eyes

Consider a scenario in which a busy executive notes that store sales growth seems to be consistently stronger for some locations than it is for others. The executive has several theories why: local staff management skills, regional differences in receptivity to national advertising campaigns, relative affluence of the local customer bases and so on. The executive would like to find a way to help the underperforming locations improve their sales but needs to know which of those theories is closer to the truth to make wise investment choices. Therefore, the executive tasks an analyst to dig into the numbers and find out what is really going on.

The analyst builds a model to try to weigh the relative impact of the different elements of the executive’s theories and then needs to find data to feed into the model. Where does the analyst look? The analyst asks the IT department for sales data by store for the past several quarters and goes online to look for Twitter feeds that reference the national chain and specific locations. Store managers and corporate human resources (HR) personnel are also contacted to provide employee satisfaction surveys and performance review data. The analyst of course meets resistance from an already overburdened IT team and is told that assembling the data will take up to two weeks. When the data does arrive, it is missing fields, and the analyst has no idea how useful or current the data is…

 

See more here:

http://www.ibmbigdatahub.com/blog/cloud-data-preparation-reshaping-business-analyst-experience

Related Content:

How to boost telecommunications customer satisfaction (by Gaurav Deshpande):

www.ibmbigdatahub.com/blog/how-boost-telecommunications-customer-satisfaction

 

 


Patient Engagement and Big Data Analytics

What can medical providers learn from other industries?

by Paddy Padmanabhan –

While health systems are using high-tech and high-touch approaches to reach patients, active patient engagement remains elusive, a recent report by HealthLeaders magazine indicates. Recognizing this, many nontraditional players are entering the healthcare market, including several Silicon Valley startups that are disrupting healthcare with digital business models that mimic the successful tactics of more mature business-to-consumer enterprises.

The talk today is all about who will be the next Amazon or Uber of healthcare—call this the consumerization of the healthcare industry. As healthcare follows in the steps of other B2C industries and becomes more consumerized, medical providers need to consider how to leverage big data to improve patient engagement if they want to maintain their standing as industry leaders.

Big data, digital health and patient engagement

The push today seems to be the using big data to better understand healthcare consumers in an attempt to better serve their needs.

However, the organizations leading this push are not necessarily the traditional health systems. Instead, they are digital health “unicorns” like ZocDoc, which puts the needs and wants of patients first. Considering that ZocDoc is a five-year-old company valued at over a billion dollars, it is safe to say that the doctor-patient relationships in the traditional healthcare setting are being reinvented.

A recent study by Frost & Sullivan explains that the proliferation of wearables and connected devices will also drive patient care in the future. The report indicates that healthcare offers that promise opportunities for the application of wearable technology may have a competitive edge over those from technology laggards. Consumers are drawn to providers who leverage the latest devices, such as smartwatches, and these types of gadgets now enable clinicians to exchange patient data and messages in a secure and HIPAA-compliant manner, according to Healthcare IT News

 

Read more here:

http://www.ibmbigdatahub.com/blog/patient-engagement-and-big-data-analytics-what-can-medical-providers-learn-other-industries

 

 


Battle Between Utilities and Renewable Energy Newcomers

by Aylee Nielsen –

In today’s ever-changing technological climate, no business model is immune to upheaval—but the utilities industry may be subject to even more disruption than most, for its business model is under siege by alternative energy competitors. Having thrown down the gauntlet, renewable energy suppliers are gaining ground in the classic battle of the tried-and-true versus the new. But there’s a twist: Both sets of competitors can bring big data and analytics to bear in their race to create the future of energy generation, transmission and distribution. Indeed, the battle between traditional utilities and renewable energy will be decided by those who learn to leverage analytics to swiftly deliver sustainable energy efficiency.

Seizing the renewable energy advantage

The pursuit of energy independence, environmental sustainability and economic development is heightening global reliance on an array of alternative energy sources that see the harnessing of sunlight, wind, waves, tides, rain and geothermal heat, with solar and wind power the most popular of such methods. Indeed, use of renewable energy technologies offers significant advantages, incurring less environmental costs than conventional energy sources do while providing greater long-term energy security.

In the first quarter of 2004, investment in renewable energy stood at $9 billion, but that figure had risen to a whopping $50 billion by the first quarter of 2015, according to Bloomberg New Energy Finance. Indeed, the US Energy Information Administration expects renewable energy to capture market share more quickly than any other power source until at least 2040.

The future of renewable energy lies in battery storage. Indeed, low-cost, efficient electric battery systems that can easily store collected power on location pose perhaps the greatest threat to traditional utilities. However, despite the advent of batteries such as the Tesla Powerwall, modern battery solutions aren’t yet affordable enough to be financially viable, even at scale.

Read more here:
http://www.ibmbigdatahub.com/blog/battle-between-utilities-and-renewable-energy-newcomers-heating