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With the rise of the cloud comes an explosion in the value of data. Because of the increasing prevalence of cloud infrastructure in nearly every industry, data is easier to collect, and the tools needed to glean intelligence from it are growing in accessibility. The potential that data offers has catapulted it to the forefront of an organization’s priorities. In fact, the demand for both data scientists and data engineers is projected to grow by 39% by 2020, according to a recent IBM report.
Aside from the spiking demand for data professionals, what’s interesting is how the rise of data is reshaping countless roles within companies, from marketers to operations management. Almost any job critical to a business can be improved with data. Content can be strategically marketed to consumers based on their preferences and location; doctors can diagnose patients more accurately with real-time disease studies; even sports stadiums can tap user data to bring fans an interactive experience from the second they set foot in the arena.
To create data-intensive apps, organizations are looking to their developers and, in turn, their data scientists. As we shift toward a data-first approach, these two teams -- which have historically operated in close but separate silos -- are finding themselves thrown together as they identify, design and create technologies that harness data.
When joined together with the right cloud tools and open technologies, developers and data scientists can help each other to analyze and pick out key data trends and patterns, build new AI and machine learning models, and make sure that the right data gets to the right business stakeholders at the right time -- whether they are customers, employees or decision makers.
Bridging The Gap
The distinctions between data scientists and developers have always been somewhat ambiguous, and it seems they continue to become more unclear every day. For example, if you examine almost any programming model, what you will find is that core analytics functions that data scientists have traditionally managed (data handling, statistical analyses and calculations) have always been at the heart of app development.
Data scientists have always played a role in building these models by creating the tools developers need to power their apps. However, this has historically been done in a process akin to a relay handoff, with data scientists translating incoming raw data into analytics-friendly languages such as Python, analyzing it, building models with the resulting insights and then handing it back over to the development team, which then typically translates the data again into the best programming language for its app. After building in these data models, developers then provide feedback to the data science team on what needs improvement and the process starts again.
In today’s world of constant innovation, this pace is not fast enough. To build with data at a competitive pace, it’s imperative for these two roles to take advantage of new tools and approaches that allow them to work together. A few ways include:
Turning to the cloud: Data platforms and notebooks, powered by the cloud, allow teams such as data scientists, developers and business analysts to work together across different languages and data models.
Implementing a collaborative, trusted environment to share data: Data owners are often hesitant to share intelligence across teams, as they can be unsure of how to share data as well as what is safe to share broadly. Creating a data governance strategy, as well as implementing tools that simplify the cleansing and sharing of data with trusted parties, helps break down barriers and facilitate collaboration.
Eliminating data analysis silos: Data analysis has typically been done in a conveyor belt-style approach, with each data scientist performing a separate step. While organized, this means a single mistake has the power to ruin an entire workload. Automation tools can help to eliminate these silos by simplifying and accelerating data discovery, cleansing and training, thus giving data scientists the capacity to focus on analysis and collaboration with others.
As an example, let’s take an airline that wants to decrease the amount of turbulence each flight experiences. Working together on a unified cloud platform geared toward both data science and app development, the airline’s developer and data science teams can work in a centralized environment to explore data patterns and identify ideas for a solution. Previously, these teams would have had to spend a tremendous amount of time passing data back and forth and iterating potential ideas and machine learning models to build out instead of collaborating on them together in one space.
This new level of communication and iteration would yield a product ready to be put into production much more rapidly. For example, imagine a mobile app for pilots that would place the most relevant weather data, previous flight reports and recommended route changes into their hands, helping them to achieve the smoothest flight possible. In this case, the combined team could bring in multiple data streams from flight routes, weather patterns and previous flights.
Working side by side with developers, data scientists can analyze trends across these sources, communicating with developers to identify and visualize the most relevant findings. As data scientists create machine learning models, developers can simultaneously build out features around these models, giving immediate feedback about what’s working and what’s not.
The Power Of Collaboration
Technology is enabling developers and data scientists to do more and share more while using fewer resources. To streamline processes and effectively share knowledge, both teams need to be equipped with a cloud platform and embrace a collaborative environment instead of being restricted to working in separate silos with different tools and programming languages.
But this shift is not just about adopting new technologies -- a culture shift is also required. Business leaders must also open a line of direct communication with their data science and development teams to be sure a collaborative mindset is implemented and adopted.
So, what can your organization do to best serve the people who handle such a valuable asset? More on that to come.
This Article Source is from : https://www.forbes.com/sites/forbestechcouncil/2017/09/14/as-data-and-cloud-rise-lines-are-blurring-between-developers-and-data-scientists/#1dfaecc75036
Atlassian on Wednesday is rolling out a number of product enhancements to improve collaboration and visibility across different corporate teams, with many of the updates geared towards customers operating on the cloud.
Already, more than 70 percent of Atlassian's existing customers are using cloud products, while more than 75 percent of new Atlassian customers start with a cloud deployment.
To solve some of the pain points that exist for Atlassian Cloud customers, the company is rolling out Identity Manager, a product with four features: SAML single sign-on for identity management, enforced two-step verification, advanced password policies, and priority cloud support. The cloud support feature promises a one-hour response time for customers facing critical issues on the weekend.
The product is primarily designed for customers that are large enough that they need identity management but may not be ready to adopt a third party identity manager.
"When we look at our customers who are growing and continue to grow on Atlassian Cloud, user management gets to be less convenient than it was when you knew everyone," Rahul Chhabria, product manager for Enterprise Cloud at Atlassian, told ZDNet. "We want customers to trust their data is secure and that our products will be up all the time."
Next, Atlassian is adding Trello boards to Bitbucket Cloud, which brings the project planning capabilities of Trello to Bitbucket, the software collaboration tool. Combining the collaboration tools bridges a gap that existed between software developers and non-technical teams such as designers or marketers.
"We find this experience makes Bitbucket a one-stop shop for software development teams and brings in everyone else that participates in shipping great software," Chhabria said.
In another move focused on hybrid customers, Atlassian is collaborating with Microsoft Azure to let customers deploy Jira Software Data Center on Azure, through a jointly developed customized template. Atlassian introduced AWS support last year.
"We're trying to provide deployment flexibility for them, for whatever environment they're comfortable with," said Junie Dinda, product marketing lead for server products at Atlassian.
Meanwhile, Atlassian is making it easier for support teams to offer help to customers with the new Embedded Portal in Jira Service Desk Cloud. Instead of having to navigate to a different page or send an email to raise a Jira Service Desk request, customers can use an embedded help button that lives anywhere.
Lastly, Atlassian is updating Portfolio for Jira, a project management tool, with two new features. With the new programs feature, business leaders can get an aggregated view of multiple projects -- this gives them visibility into projects that all tie into broader business objectives.
"This is extremely important for executives and managers to understand what's actually going on in their agile software development and how it ties to their business priorities, Dinda said.
Similarly, the dependencies reporting feature gives a visualization of factors on which a project may be dependent. The feature helps managers spot project bottlenecks and find any risks to the project.
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Article Source is From : http://www.zdnet.com/article/atlassian-rolls-out-several-cloud-focused-product-updates/
Fasten your harnesses, because the era of cloud computing’s giant data centers is about to be rear-ended by the age of self-driving cars. Here’s the problem: When a self-driving car has to make snap decisions, it needs answers fast. Even slight delays in updating road and weather conditions could mean longer travel times or dangerous errors. But those smart vehicles of the near-future don’t quite have the huge computing power to process the data necessary to avoid collisions, chat with nearby vehicles about optimizing traffic flow, and find the best routes that avoid gridlocked or washed-out roads. The logical source of that power lies in the massive server farms where hundreds of thousands of processors can churn out solutions. But that won’t work if the vehicles have to wait the 100 milliseconds or so it usually takes for information to travel each way to and from distant data centers. Cars, after all, move fast.
That problem from the frontier of technology is why many tech leaders foresee the need for a new “edge computing” network—one that turns the logic of today’s cloud inside out. Today the $247 billion cloud computing industry funnels everything through massive centralized data centers operated by giants like Amazon, Microsoft, and Google. That’s been a smart model for scaling up web search and social networks, as well as streaming media to billions of users. But it’s not so smart for latency-intolerant applications like autonomous cars or mobile mixed reality.
“It’s a foregone conclusion that giant, centralized server farms that take up 19 city blocks of power are just not going to work everywhere,” says Zachary Smith, a double-bass player and Juilliard School graduate who is the CEO and cofounder of a New York City startup called Packet. Smith is among those who believe that the solution lies in seeding the landscape with smaller server outposts—those edge networks—that would widely distribute processing power in order to speed its results to client devices, like those cars, that can’t tolerate delay.
Packet’s scattered micro datacenters are nothing like the sprawling facilities operated by Amazon and Google, which can contain tens of thousands of servers and squat outside major cities in suburbs, small towns, or rural areas, thanks to their huge physical footprints and energy appetites. Packet’s centers often contain just a few server racks—but the company promises customers in major cities speedy access to raw computing power, with average delays of just 10 to 15 milliseconds (an improvement of roughly a factor of ten). That kind of speed is on the “must have” lists of companies and developers hoping to stream virtual reality and augmented reality experiences to smartphones, for example. Such experiences rely upon a neurological process—the vestibulo-ocular reflex—that coordinates eye and head movements. It occurs within seven milliseconds, and if your device takes 10 times that long to hear back from a server, forget about suspension of disbelief.
Immersive experiences are just the start of this new kind of need for speed. Everywhere you look, our autonomously driving, drone-clogged, robot-operated future needs to shave more milliseconds off its network-roundtrip clock. For smart vehicles alone, Toyota noted that the amount of data flowing between vehicles and cloud computing services is estimated to reach 10 exabytes per month by 2025.
Cloud computing giants haven’t ignored the lag problem. In May, Microsoft announced the testing of its new Azure IoT Edge service, intended to push some cloud computing functions onto developers’ own devices. Barely a month later, Amazon Web Services opened up general access to AWS Greengrass software that similarly extends some cloud-style services to devices running on local networks. Still, these services require customers to operate hardware on their own. Customers who are used to handing that whole business off to a cloud provider may view that as a backwards step.
US telecom companies are also seeing their build-out of new 5G networks—which should eventually support faster mobile data speeds—as a chance to cut down on lag time. As the service providers expand their networks of cell towers and base stations, they could seize the opportunity to add server power to the new locations. In July, AT&T announced plans to build a mobile edge computing network based on 5G, with the goal of reaching “single-digit millisecond latency.” Theoretically, data would only need to travel a few miles between customers and the nearest cell tower or central office, instead of hundreds of miles to reach a cloud data center.
“Our network consists of over 5,000 central offices, over 65,000 cell towers, and even several hundred thousand distribution points beyond that, reaching into all the neighborhoods we serve,” says Andre Fuetsch, CTO at AT&T. “All of a sudden, all those physical locations become candidates for compute.”
AT&T claims it has a head start on rival telecoms because of its “network virtualization initiative,” which includes the software capability to automatically juggle workloads and make good use of idle resources in the mobile network, according to Fuetsch. It’s similar to how big data centers use virtualization to spread out a customer’s data processing workload across multiple computer servers.
Meanwhile, companies such as Packet might be able to piggyback their own machines onto the new facilities, too. ”I think we’re at this time where a huge amount of investment is going into mobile networks over the next two to three years,” Packet’s Smith says. “So it’s a good time to say ‘Why not tack on some compute?’” (Packet’s own funding comes in part from the giant Japanese telecom and internet conglomerate Softbank, which invested $9.4 million in 2016.) In July 2017, Packet announced its expansion to Ashburn, Atlanta, Chicago, Dallas, Los Angeles, and Seattle, along with new international locations in Frankfurt, Toronto, Hong Kong, Singapore, and Sydney.
Packet is far from the only startup making claims on the edge. Austin-based Vapor IO has already begun building its own micro data centers alongside existing cell towers. In June, the startup announced its “Project Volutus” initiative, which includes a partnership with Crown Castle, the largest US provider of shared wireless infrastructure (and a Vapor IO investor). That enables Vapor IO to take advantage of Crown Castle’s existing network of 40,000 cell towers and 60,000 miles of fiber optic lines in metropolitan areas. The startup has been developing automated software to remotely operate and monitor micro data centers to ensure that customers don’t experience interruptions in service if some computer servers go down, says Cole Crawford, Vapor IO’s founder and CEO.
Don’t look for the edge to shut down all those data centers in Oregon, North Carolina, and other rural outposts: Our era’s digital cathedrals are not vanishing anytime soon. Edge computing’s vision of having “thousands of small, regional and micro-regional data centers that are integrated into the last mile networks” is actually a “natural extension of today’s centralized cloud,” Crawford says. In fact, the cloud computing industry has extended its tentacles toward the edge with content delivery networks such as Akamai, Cloudflare, and Amazon CloudFront that already use “edge locations” to speed up delivery of music and video streaming.
Nonetheless, the remote computing industry stands on the cusp of a “back to the future” moment, according to Peter Levine, general partner at the venture capital firm Andreessen Horowitz. In a 2016 video presentation, Levine highlighted how the pre-2000 internet once relied upon a decentralized network of PCs and client servers. Next, the centralized network of the modern cloud computing industry really took off, starting around 2005. Now, demand for edge computing is pushing development of decentralized networks once again (even as the public cloud computing industry’s growth is expected to peak at 18 percent this year, before starting to taper off).
That kind of abstract shift is already showing up, unlocking experiences that could only exist with help from the edge. Hatch, a spinoff company from Angry Birds developer Rovio, has begun rolling out a subscription game streaming service that allows smartphone customers to instantly begin playing without waiting on downloads. The service offers low-latency multiplayer and social gaming features such as sharing gameplay via Twitch-style live-streaming. Hatch has been cagey about the technology it developed to slash the number of data-processing steps in streaming games, other than saying it eliminates the need for video compression and can do mobile game streaming at 60 frames per second. But when it came to figuring out how to transmit and receive all that data without latency wrecking the experience, Hatch teamed up with—guess who—Packet.
“We are one of the first consumer-facing use cases for edge computing,” says Juhani Honkala, founder and CEO of Hatch. “But I believe there will be other use cases that can benefit from low latency, such as AR/VR, self-driving cars, and robotics.”
Of course, most Hatch customers will not know or care about how those micro datacenters allow them to instantly play games with friends. The same blissful ignorance will likely surround most people who stream augmented-reality experiences on their smartphones while riding in self-driving cars 10 years from now. All of us will gradually come to expect new computer-driven experiences to be made available anywhere instantly—as if by magic. But in this case, magic is just another name for putting the right computer in the right place at the right time.
“There is so much more that people can do,” says Packet’s Smith, “than stare at their smartphones and wait for downloads to happen.” We want our computation now. And the edge is the way we’ll get it.
Article Source is From : https://www.wired.com/story/its-time-to-think-beyond-cloud-computing/
Customer expectations have changed massively thanks to the internet. Instant gratification is simply expected as normal and it’s harder than ever for service to stand out. Meanwhile, significant growth in customer contact is also putting serious pressure on organisations to offer a prompt response.
It’s great that customers feel more connected to brands, but as we’ve come to expect instantaneous replies to queries, organisations are reaching their physical limits in terms of how much their human workforce can handle.
To deal with the demand for tailored 1-to-1 customer/company conversations, businesses are using AI. In fact, by 2020, Gartner predicts that 85% of customer interactions will be handled this way.
But when we talk about AI for customer service, we don’t just mean customer service bots replacing human agents. AI technology is also easing admin workloads – allowing representatives to focus on providing the human touch.
Here are four important ways AI is transforming how organisations communicate with their customers and manage increasing workloads.
1. Using AI for customer service helps solve small problems – before they grow
Remember the last time you demanded to speak to a call handler’s supervisor? If only that escalated complaint could have been nipped in the bud early. That’s why AI is now helping organisations to deal with small issues early, before they become big ones.
If customers are provided with the means to contact a company with minimal effort, such as through a messenger window while they work instead of a phone call, they’re more likely to report minor concerns, rather than waiting until the problem can no longer be avoided. This can prevent issues from escalating beyond what’s necessary – improving brand satisfaction.
In turn, reducing the number of escalated complaints means human agents are under less pressure when it comes to getting to grips with more complicated cases. That’s good for brand satisfaction too: according to the Ombudsman Service, 75% of shoppers in the UK feel encouraged to make a repeat purchase if their complaint is well dealt with.
2. AI for customer service can improve your multichannel offering
Customers spend a lot of time on their smartphones, communicating through messaging apps. So if this is how your customers prefer to communicate, why wouldn’t you give them this option?
Messaging means talking to your customers on their terms, through their choice of application. But the Harvard Business Review says the biggest benefit is the ability for a brand to immediately understand the customer’s query in context – helping to provide quick, no-nonsense responses.
More organisations than ever are now allowing their customers to contact them this way, to good effect – research by Aberdeen Group suggests that companies with a strong omnichannel presence have on average an 89% customer retention rate.
The challenge is handling the resulting increase in customer contact. Automation can help, but only for basic enquiries – and that’s where AI for customer service can help. By using intelligent deep learning capabilities, AI can make decisions on whether to reply to a customer automatically – giving an instant response – or transfer them to a human agent if the enquiry is more involved.
3. Making self-service smarter – the rise of AI customer service bots
AI customer service bots – whether on a website or a messaging app – allow customers to address their own issues instantaneously – without putting unnecessary pressure on contact centre teams.
But it’s important that AI complements the human aspect of customer service.
A recent report from Accenture suggests that AI will dominate the way the big 3 banks in the UK interact with their customers – but it also notes that, even though customers are willing to embrace AI, they still want to be safe in the knowledge they can speak to a human.
And the great news is, bots are getting better at making that happen. Organisations gather more data from their customers, AI becomes more competent at diagnosing customer issues and offering first point resolution – allowing physical agents to optimise those human-to-human interactions.
4. AI can predict what your customer’s going to do next
Good predictions about customers’ likely behaviour are among the most prized assets an organisation can get its hands on – because it means you’re ready to respond.
Whether it’s being able to predict stock demand based on the weather, or identifying problems before they affect customers, AI has the ability to make real-time decisions on a scale we’ve never seen before.
Customer issues are generally not unique. And if one customer is contacting customer service with a problem, it’s safe to assume there are more to follow. But it’s this repetition of issue cases that helps AI to learn and understand the common – but sometimes complex – reasons why customers interact with a brand, and the solutions that go with them.
This is where AI deep learning comes into its own. By linking up data silos across the organisation, companies can pinpoint customer issues and resolve them quickly.
And this will only get better with time. As organisations accrue more data on customers, their predictive accuracy will increase.
Introducing Service Cloud Einstein – Salesforce’s AI for customer service
There’s no doubt, great customer service still leaves a lasting impression – and AI has an increasing role to play in providing what your customers demand. That’s why we’re excited to introduce Service Cloud Einstein:
Einstein Supervisor – empowering contact centre supervisors with real-time, omni-channel insights and AI-powered analytics to increase productivity and customer satisfaction Einstein Case Management – using machine learning for automatic case escalation and intelligent information gathering to save valuable time for agents
Intelligent Mobile Service – keeping your team in the field connected, providing personalised and exceptional service wherever they go.
To discover more about how AI can revolutionise your customer interactions, Follow Us & Like our Page @Solunusinc
This Article Source is From : https://www.salesforce.com/uk/blog/2017/08/ai-for-customer-service-4-ways-to-get-ahead-of-the-curve
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Stronger Security and Disaster Planning Fuel Healthcare's Migration to the Cloud
New cost reductions make cloud options more compelling than ever but, in a twist, experts say cloud platforms can be more secure than managed data centers.
Healthcare did not lead the charge into the cloud. But it has been making up for lost time. The use of cloud platforms has grown substantially within healthcare provider organizations.
A recent HIMSS Analytics survey of provider C-suite executives found that more than half are using Infrastructure-as-a-Service (Iaas) cloud platforms to provide an environment for a wide range of uses ranging from hosting internally developed programs to a running fully functional EHR.
HIPAA privacy and security concerns were one reason for the slow start. But once HHS provided clear guidance on how to address PHI issues and work through Business Associate (BA) relationships, everything changed.
Today, very few healthcare CIO’s consider security a reason to avoid the cloud. Quite the opposite. The HIMSS Analytics survey found that disaster preparedness is now one of the leading reasons why healthcare CIO’s are making the decision to shift resources onto cloud platforms. The savings are compelling. Why rent storage in a redundant data center to maintain a fully functioning backup when you can pay for only what you need in the cloud?
“You don't have to worry about your infrastructure and data center,” said Jason Bickford, Applications Director of Health Information Management Systems at Banner Health and president of the HIMSS Arizona Chapter. “Cloud-based is the right way to go.”
Disaster recovery in the cloud also has value as a stepping stone on the way to moving production-level clinical applications into a cloud environment. The logic is compelling. Once the backup clinical application has been confirmed to be running smoothly in parallel, the cloud option has proved itself reliable, so why not take advantage of the potential savings?
That is not to say that security isn’t a priority. After budget limitations, HIMSS Analytics survey respondents cited security concerns as a reason to move slowly toward the cloud.
“Regardless of whether a solution is hosted in your own data center or in the cloud, security should be a critical factor in your review,” advises Susan Snedaker, Director, IT Infrastructure & Operations at Tucson Medical Center and author of the book IT Security Management. “There’s nothing inherently more or less secure about a cloud option, but some cloud-based solutions may not meet today’s stringent security requirements.”
In selecting a cloud platform vendor, Snedaker advises a careful review of the vendor’s documentation and contracts. Pay attention to the provider’s security program and make sure that audits take place on a regular basis.
“If your database is going to be hosted on the same server as another database from another company, what happens if the other database is attacked? Can the attacker then gain access to your data?” Snedaker says. “Be sure to understand the specifics of the hosting solution so you are clear about your vulnerabilities. Then take steps to mitigate them – select a different solution, select a different hosting model, ask the vendor to modify policies, processes, procedures, access methods, etc. or accept the risk if it cannot be overcome and there are no better options.”
Security consultant Tod Ferran of Halock Security Labs has performed audits of the large cloud platforms, Microsoft, Amazon and Google, and found the services are maintaining a very high level of security. “In many ways,” Ferran said, “the cloud is a better choice because many hospitals can’t afford the staff to make their systems secure enough.”
As the nature of risk has changed, so has the value equation. Strong security means constant maintenance of operating systems and applications with the healthcare enterprise. HIT managers can gain peace of mind from knowing the updates are being performed by a vendor that is guaranteeing round-the-clock support, rather than by a hospital staff already stretched with aggressive internal project loads.
Many healthcare providers use multiple cloud vendors, cherry picking among the different options to align with specific demands of each application.
“Organizations are not putting all their eggs in one basket,” said Sandra Yu, cloud client executive at CDW. “It’s a multi-cloud world.” CDW partners with a wide number of cloud hosts in providing managed cloud services , so Yu has experience with many vendors.
“If you have needs for hyper computing, we would recommend a public hyper-scalar for that,” she said. For PHI she would recommend a private cloud.
When it comes to applications that have a heavy computational workload, you need to be sensitive to the cloud’s latency and so she would recommend a cloud data center that is geographically closer. But for something that is not PHI-sensitive, she would recommend a public cloud where the costs should be lower.
“The clinical apps that can work well in the cloud are typically those that are not transferring large files or data streams,” Snedaker says. “If you’re going to host a data intensive clinical application in the cloud, you should be sure you have the right connectivity solution in place.”
When factoring in all of the reasons to move to the cloud, in the end, cost is still a prime motivation. The savings are derived not only from reducing the cost of maintaining data centers. The pricing for IaaS continues to go down.
“It’s like a race to the bottom,” Yu said, noting that when one of the major vendors lowers its price, the others are quick to match it. Pricing among the leading public cloud vendors is generally on par now, so decisions should be made after shopping for the services and support that you’ll need. Pay as you go options are readily available, so trials are simple to setup.
This Article Source is From : http://www.healthcareitnews.com/news/stronger-security-and-disaster-planning-fuel-healthcares-migration-cloud
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I signed up for AppSumo Black, with only a handful of the apps in the collection being relevant. Part of the reason for signing up was the promise that "new apps are added weekly, so the investment grows over time." Two months in, and I have not seen any new apps added to AppSumo Black - though I have purchased a few additional apps on top of the Black subscription.
So, can AppSumo please confirm if new apps are added to the Black subscription and how often?
Invoice Processing Services for Businesses
A streamlined invoice processing capacity is imperative to organizations. Blunders and oversights in solicitations can bring about compromise disparity and client disappointment. Organizations can't organize their attention on center esteems because of the extreme time and assets expended in finishing receipt handling. By outsourcing this procedure organizations would now be able to focus on business development.
Utilizing a product to process your invoicing benefits your business from numerous points of view as it lessen the cost to manual information passage and cost related with it and make the procedure speedier. In manual process, the blunder rate is high while overseeing receipt process by programming limits the mistake rate and assets are utilized as a part of extremely productive way. The greatest advantage is that the budgetary reports of the business get more precise and regularized, and give greater deceivability and control as all invoicing data will be brought together.
QuickBooksSupport.DSS is outsider help supplier who turned into your dependable outsourcing accomplice for an assortment of organizations everywhere throughout the world. We help organizations to deal with their non-gainful exercises. We esteem our client relationship and give our administrations as per your business forms and turn into your long haul accomplice.
How we actualize Invoice Processing System
QuickBooksSupport.DSS has given modified receipt administration arrangements that incorporate programmed dealing with and preparing of solicitations to different organizations crosswise over English talking nations. To execute invoice processing framework, our procedure incorporates following:
- Utilization of mechanized receipt acknowledgment programming.
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- Quick handling of solicitations to serve customer earnestness.
- Simple openness of your invoicing information as it will be put away on Cloud
- Designating a devoted asset to keep up your receipt data to stay up with the latest.
Points of interest of Outsourcing Your Invoice Processing to QuickBooksSupport.DSS
- Tweaked receipt forms that assistance lessen representative and IT framework costs
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It’s hard to imagine any business that doesn’t use any form of technology these days. The problem is, any computing infrastructure or equipment can be exposed to various methods of cyberattacks. Just last May, the WannaCry ransomware affected more than 10,000 organizations of all sizes in more than 150 countries. The attack caused stoppages in critical services and operations such as the UK’s National Health Service and several of Renault’s automotive manufacturing plants. Last year, one billion Yahoo users saw their accounts hacked, costing the company dearly.
While these reported ones were about large organizations, there were many anecdotal accounts of SMEs getting hit by the attack. Many of these smaller organizations are running on older systems and have little to no protection. Startups often get tied up with the more pressing parts of the business such as sales and operations that most often overlook security as part of your agenda. Here are 7 things entrepreneurs need to know about cybersecurity.
1. No such thing as too small
You may think that cybercriminals only target high profile organizations like the incidences we often hear and read about on the news. However, a Ponemon Institute study reports that 55 percent of SMEs experienced some form of cyberattack. If your business uses any computing device or the internet or has a digital presence such as a website or cloud accounts, then you are at risk of cyberattacks. Most attacks are now carried out by automated malicious software and scripts that seek out vulnerable computers and networks regardless of the size and nature of the organization.
According to cloud security provider Indusface, SMEs, which are more at-risk due to their limited experience with cybersecurity measures, are required to deal with today’s complex threats. Most small businesses have no dedicated IT staff that focuses on such things. This is why it’s important for startups to make security a shared responsibility across all members.
2. Threat 1: Data breaches
There are several common cyberattacks that you should be aware of. The first one is data breach. This is when cyber criminals seek to steal your company’s data by gaining access to your databases. Personal and financial information are sold on the black market for use in identity theft and fraud. Startups who have websites or apps that gather customer information such as ecommerce, online support, or CRM are prime targets for such attacks.
You may think that large organizations that have experienced data breaches such as Sony, Dropbox and LinkedIn survived the data breach fallout so you shouldn’t worry too much about such attacks. However, these major companies have resources and longstanding relationships to weather such issues. Startups don’t fare too well dealing with loss of customer trust and stained reputations. According to the U.S. National Cyber Security Alliance, 60 percent of small businesses fail within six months after suffering from such attacks.
3. Threat 2: Ransomware and malware
Security company Kaspersky identifies ransomware among the top cybersecurity threats to businesses today. Ransomware are a specific type of malware (malicious software) that infect computers (including mobile devices) over a vulnerable network. The ransomware encrypts files on the compromised computer. Users won’t be able to access the files unless they get a decryption key by paying ransom to the attackers. Even with paying the ransom, there’s no assurance that attackers will actually honor your payment.
Most ransomware attackers demand between $500 to $1,000 in exchange for your files. Some ransomware such as Jaff demand as much as $4,000. Ransom payments are often in cryptocurrencies like Bitcoin due to the anonymity these methods offer. The major impact to businesses isn’t exactly the ransom but the disruption to the business. Getting locked out of all your work files can halt your operations indefinitely.
4. Threat 3: DDoS attacks
Distributed denial-of-service attacks (DDoS) render your website or server inaccessible by overwhelming your network with traffic. An hour of downtime from a DDoS attack can cost up to $20,000 for a third of companies. For high transaction websites such as ecommerce services, this figure can be upwards $100,000 for every hour.
Small businesses are often left to weather the downtime and absorb lost sales and productivity. Even if not directly targeted, SMEs could still be affected by DDoS attacks on larger infrastructure providers. Last year, thousands of sites and services went down after a massive DDoS attack hit DNS provider Dyn.
5. People are often the weakest link
People are often the weakest link in a security chain. A BakerHostetler report found that most security breaches are caused by human lapses. Many systems are left vulnerable to data breaches and ransomware attacks through phishing where people are tricked into clicking on links and installing malware.
Some can even bring these threats into your infrastructure by carelessly plugging in their own phones, notebooks, and storage devices to your network and computers. Educating yourself and your staff on the best day-to-day security practices would be a worthwhile investment to prevent attacks caused by human error. Have security policies in place that would govern how you and your staff should be using your IT resources.
6. Access control counts
Know to whom you’re giving infrastructure access. As a startup, you may be unnecessarily handing out critical infrastructure access to just about anyone like that freelancer you hired to build and maintain your page may still have access to your servers or the guy you let go last week may still have the passcode to void transactions on your POS system.
Today, most administration tools and services allow you to set user roles with corresponding levels of access so that you can control who gets to do what on your infrastructure. Encourage people to use strong passwords and protect them at all times. Revoke access of anyone not working for your company as soon as they go. Cover yourself legally as well by putting in nondisclosure clauses to prevent them from leaking passwords on agreements with people you involve in the business.
7. Invest on security
As a startup, you may be averse to take on added expenses. However, cybersecurity is just one of the IT investments you have to make. Besides, there are cost-effective anti-malware and security software that you can use for your office computers.
In addition, security-as-a-service is now a thing which means you don’t have to make heavy upfront investments on security applications and appliances to protect your network. Instead, you can subscribe to scalable security services such as web application firewalls and DDoS mitigation services for your online infrastructure and applications. Startup cyber security is just among the many realities IT professionals must focus on. Know the risks and put up programs in place that would help you avoid getting hit by cyberattacks down the line.
This Article Source is From : http://www.cio.com/article/3201744/data-protection/7-things-startups-need-to-know-about-cybersecurity.html
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The latest update to Salesforce Service Cloud is designed to help service agents offer better, mobile customer service and is more customizable.
Salesforce.com has announced the “next generation” of its Service Cloud platform that has been redesigned with new features as well as improvements for easier application setup and management.
Service agents can manage and resolve customer issues regardless of whether they are on the road, at the home office or at a customer's site using the new native Service Cloud mobile app for iOS and Android that are due for release later this year.
Salesforce customers can also extend Services Cloud functionality with additional apps available from the Salesforce AppExchange or they can customize the platform with Lightning Builder.
Lightning Components can be added simply by dragging and dropping them to Service Cloud. Currently-available Service Cloud apps include several with telephony and call center management features from Dialpad, NewVoiceMedia and Talkdesk; internet of things asset tracking and mapping from MapAnythingLive, and patient and healthcare provider communications from Healthwise.
On the management front, Salesforce has added new capabilities to the Lightning Service Console including the “Case Kanban” visual dashboard that shows cases in the queue to help service agents prioritize their time.
Another component, Community Agent 360 shows a customer’s community history giving the agent some context about recent customer activities, such as a recent support article the customer may have read so the agent doesn’t repeat information or suggest a fix the customer has already tried.
A Federated Search feature lets agents find relevant information across Salesforce and external data sources such as Confluence, YouTube, Dropbox and Box.
There is also a Macro Builder capability that helps agents quickly create reusable macros for specific customer service scenarios. Agents can then easily deploy that macro if the issue comes up again.
As a measure of how easy it is to set up, Salesforce asserts that companies of any size can use Service Cloud to build a feature rich customer service center in a day or less.
“Any company, large, medium and small, can be empowered to deliver personalized service experiences in less than a day with clicks, not code,” Keith Pearce, vice president of marketing for Service Cloud at Salesforce, told eWEEK.
Features such as case management are now built-in to Service Cloud. In as little as five steps, service administrators can add a customer community and knowledge base, as well as connect to email, Facebook and Twitter feeds, according to Pearce.
“We’ve set up service flows for Twitter and Facebook and it takes all the learnings from similar cases the agent can get to" in just a few clicks, said Pearce.
For additional features and customization, Salesforce offers Trailhead, its online, gamified training platform, with more than twenty free, guided modules to learn how to deploy, configure and customize Service Cloud.
“The new cloud-based deployment and management features Salesforce has added to its Service Cloud are designed to address core issues of concern to its business clients,” Charles King, principal analyst at Pund-IT, told eWEEK in an email.
“Central to that is the evolution of digitally-enabled, proactive customers with access to powerful communications technologies and platforms to highlight unusual experiences and share their feelings," King said.
Proactive customers with access to social media and other web communications will often freely vent their frustration with service providers that perform poorly, King noted.
"Anyone who doubts that their business or brand might suffer from this often unconstrained venting hasn't been paying attention to the news. The new Salesforce offerings aim to help clients address these issues with next gen service cloud solutions that are quick to deploy, simple to learn and easily managed,” he said.
The Salesforce Service Out-of-the-Box, Lightning App Builder for Service, Lightning Service Console, Federated Search and Case Kanban view are available today at no additional cost with any edition of Service Cloud.
A pilot edition of Community Agent 360 is available today at no additional cost with a Customer Community Cloud license. A beta version of Macro Builder is available now at no additional cost with any edition of Service Cloud. Salesforce said it plans to make a pilot version of the Service Cloud Mobile app for iOS and Android available in the second half of 2017 with any edition of Service Cloud.
This Article Source is From : http://www.eweek.com/cloud/salesforce-service-cloud-update-provides-new-tools-for-service-agents