Thanks to the Internet of Things (IoT), our world is more automated and connected than ever before. Just about everything, from cars to refrigerators, to coffee machines, has the ability to connect to the Internet, allowing us to micromanage each individual device. This type of automation is an exciting direction for the world to be moving in and the benefits it brings to businesses are huge.

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Discover top technologies and tools all under one roof at April 24–28, 2017, at the Westin San Diego in San Diego, CA. Explore the Mobile Dev + Test and IoT Dev + Test Expo and enjoy all of these unique opportunities: The latest solutions, technologies, and tools in mobile or IoT software development and testing. Meet one-on-one with representatives from some of today’s most innovative organizations

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Thanks to its many business benefits, cloud computing is becoming commonplace within organizations of all sizes. Historically, companies have struggled to determine which model – public or private – best met their needs. But of late, IT professionals are increasingly starting to realize that both public and private clouds can exist harmoniously within the same organization, and that, in many instances, a hybrid cloud model can actually be the most effective approach.

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Bitcasa, the developer-friendly cloud storage platform based in Mountain View, is ‘no more’ according to a statement from former CEO Brian Taptich.

The statement, which appears on the Bitcasa homepage and is redirected to from other pages on the site, is cryptic in tone, only noting that the company has “become a part of something much, much bigger.” A VentureBeat article reported that the company had been acquired by Intel, something the latter subsequently denied.

“We have no doubt that Bitcasa has found the right home to fulfill a mission that has driven the company from its 2011 beginnings – to eliminate the storage and computing limitations of your connected devices, however small, in the most secure and efficient way possible,” the statement from Taptich read. “We remain optimistic that, before long (and though you may not realise it), Bitcasa’s technology will yet contribute significantly to fulfilling this mission.

“Looking back, it seems impossible to simplify a Bitcasa experience that, at times, felt so complicated,” Taptich added.

Bitcasa started life as a single-user platform for unlimited cloud storage in 2011 – something of a rarity in those days – yet the company hit the news in 2014 when it announced the end of its unlimited storage plan, citing what it called “abusers” – in other words, businesses caning individual accounts – as part of the reason.

By coincidence, in the same week Microsoft announced its first unlimited OneDrive cloud storage packages, to Office 365 subscribers, yet almost a year to the day that was also nixed for similar reasons; users were taking advantage of the offer by backing up “numerous PCs, entire movie collections and DVR recordings”. Bitcasa announced it was pulling out of consumer storage in April last year to focus more on its platform business.

Speaking to this publication in November 2015, Taptich explained that Bitcasa had reservations about its unlimited plan as far back as 2013, as well as citing the company’s “small but passionate” user base. Referring to Microsoft’s decision, Taptich said: “I suspect Microsoft just learned that, however theoretical models may have supported the efficacy of offering unlimited storage of a fixed – and low – fee, in the almost entirely frictionless world of data transfer, the first users who show up to the all you can eat buffet break the model with their unimaginable volumes of data.”

For now though, the future of Bitcasa remains unknown. “Our hope is that everybody in the Bitcasa extended family – including our partners and end-users – feels as if they reaped some benefit, however small, from this remarkable and intense experience,” the statement concluded.

CloudTech has reached out for comment and will update this story in due course.

As the network has moved from a physical entity to a more abstract one, IT has valiantly kept pace by researching and deploying new network devices and functionality. IT teams have had to shift workloads and mindsets to the cloud and to SaaS providers, while remaining responsible for end-user experience-which is ever more important.

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Enterprises prefer Microsoft Azure as their primary cloud provider while smaller businesses are more likely to be Google houses, according to the latest research from B2B analysis firm Clutch.

The findings, which polled almost 250 users of AWS, Google and Microsoft, appear in the firm’s latest report, found almost 40% of Azure users polled identify as enterprises, compared to only 25% for SMBs and 22% as startups or sole proprietorships. In contrast, 41% of Google Cloud Platform users identified themselves as SMBs.

The reasons are varied, although the argument that smaller businesses are more conscious of price, as opposed to security or toolsets, again reared its head. “It goes back to the trust and familiarity issues,” said Nicholas Martin, principal applications development consultant at IT solutions provider Cardinal Solutions. “Windows Server and other Microsoft technologies are prevalent in the enterprise world. Azure providers the consistency required by developers and IT staff to tightly integrate with the tools that Microsoft-leaning organisations are familiar with.”

More than one in five (21%) of respondents argued that a better selection of tools and features were key to their choice of cloud provider, ahead of familiarity with a brand, and stronger security capabilities.

The findings resonate similarly to those reported by BetterCloud in 2015, who argued there was a “clear trend” for larger organisations to use Office 365, as opposed to Google Apps for cloud offices.

Clutch gave three recommendations for organisations looking to make the right decision over their cloud provider:

• If your business is either an enterprise, requires Windows integration, or needs a strong platform as a service play, consider Microsoft
• If longevity, expertise in infrastructure as a service, and a wide selection of tools are key, go with AWS
• If you are an SMB with a limited budget or need to place heavy emphasis on analytics, consider Google Cloud Platform

This is all pretty sound advice from where CloudTech is standing. You can read the full report here.

JavaScript redefined web applications ushering in a new era of dynamic websites with fluid responsive designs. It has gained a strong following among developers, popular libraries and frameworks like JQuery and Angular JS are all built with JavaScript. The endless design possibilities that JavaScript provides coupled with the numerous libraries available today makes it an indispensable part of web application development.

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• U.S. retailer supply chain operations who have adopted data and analytics have seen up to a 19% increase in operating margin over the last five years.
• Design-to-value, supply chain management and after-sales support are three areas where analytics are making a financial contribution in manufacturing.
• 40% of all the potential value associated with the Internet of Things requires interoperability between IoT systems.

These and many other insights are from the McKinsey Global Institute’s study The Age of Analytics: Competing In A Data-Driven World published in collaboration with McKinsey Analytics this month. You can get a copy of the Executive Summary here (28 pp., free, no opt-in, PDF) and the full report (136 pp., free, no opt-in, PDF) here. Five years ago the McKinsey Global Institute (MGI) released Big Data: The Next Frontier For Innovation, Competition, and Productivity (156 pp., free no opt-in, PDF), and in the years since McKinsey sees data science adoption and value accelerate, specifically in the areas of machine learning and deep learning. The study underscores how critical integration is for gaining greater value from data and analytics.

Key takeaways from the study include the following:

• Location-based services and U.S. retail are showing the greatest progress capturing value from data and analytics. Location-based services are capturing up to 60% of data and analytics value today predicted by McKinsey in their 2011 report. McKinsey predicts there are growing opportunities for businesses to use geospatial data to track assets, teams, and customers across dispersed locations to generate new insights and improve efficiency. U.S. Retail is capturing up to 40%, and Manufacturing, 30%.  The following graphic compares the potential impact as predicted in McKinsey’s 2011 study with the value captured by segment today, including a definition of major barriers to adoption.

• Machine learning’s greatest potential across industries includes improving forecasting and predictive analytics. McKinsey analyzed the 120 use cases their research found as most significant in machine learning and then weighted them based on respondents’ mention of each. The result is a heat map of machine learning’s greatest potential impact across industries and use case types.  Please see the report for detailed scorecards of each industry’s use case ranked by impact and data richness.

• Machine learning’s potential to deliver real-time optimization across industries is just starting to evolve and will quickly accelerate in the next three years. McKinsey analyzed the data richness associated with each of the 300 machine learning use cases, defining this attribute as a combination of data volume and variety. Please see page 105 of the study for a thorough explanation of McKinsey’s definition of data volume and variety used in the context of this study The result of evaluating machine learning’s data richness by industry is shown in the following heat map:

• Enabling autonomous vehicles and personalizing advertising are two of the highest opportunity use cases for machine learning today. Additional use cases with high potential include optimizing pricing, routing, and scheduling based on real-time data in travel and logistics; predicting personalized health outcomes, and optimizing merchandising strategy in retail. McKinsey identified 120 potential use cases of machine learning in 12 industries and surveyed more than 600 industry experts on their potential impact. They found an extraordinary breadth of potential applications for machine learning.  Each of the use cases was identified as being one of the top three in an industry by at least one expert in that industry. McKinsey plotted the top 120 use cases below, with the y-axis shows the volume of available data (encompassing its breadth and frequency), while the x-axis shows the potential impact, based on surveys of more than 600 industry experts. The size of the bubble reflects the diversity of the available data sources.

• Designing an appropriate organizational structure to support data and analytics activities (45%), Ensuring senior management involvement (42%), and designing effective data architecture and technology infrastructure (36%) are the three most significant challenges to attaining data and analytics objectives. McKinsey found that the barriers break into the three categories: strategy, leadership, and talent; organizational structure and processes; and technology infrastructure. Approximately half of executives across geographies and industries reported greater difficulty recruiting analytical talent than any other kind of talent. 40% say retention is also an issue.

• U.S. retailer supply chain operations who have adopted data and analytics have seen up to a 19% increase in operating margin over the last five years. Using data and analytics to improve merchandising including pricing, assortment, and placement optimization is leading to an additional 16% in operating margin improvement. The following table illustrates data and analytics’ contribution to U.S. retail operations by area.

• Design-to-value, supply chain management and after-sales support are three areas where analytics are making a financial contribution in manufacturing. McKinsey estimates that analytics have increased manufacturer’s gross margins by as much as 40% when used in design-to-value workflows and projects. Up to 15% of after-sales costs have been reduced through the use of analytics that includes product sensor data analysis for after-sales service. There are several interesting companies to watch in this area, with two of the most innovative being Sight Machine and enosiX, with the latter enabling real-time integration between SAP and Salesforce systems. The following graphic illustrates the estimated impact of analytics on manufacturing financial performance by area.