Monday 30 April 2018

The Seventh Sense Summary Joshua Cooper Ramo

The Seventh Sense Summary – You might not realize it, but every time you surf the internet, you are entering one of the world’s most complicated and intricate systems. After all, your smartphone or laptop is interacting with millions of others across the globe, and it has access to well over a billion interconnected web pages.

Complex systems such as the internet have undoubtedly made our lives easier, and, as technology improves, they’ll increasingly improve our existence. But we need to be careful.

If we want to make the most of complex networks, society must keep up with technological change. At the moment, it’s far too easy for people to use networks against us: terrorists can use the internet to spread their message, criminals can hack into our data and speculators can use the increasingly complex financial system to crash the economy. Only by constantly keeping our institutions and infrastructure up-to-date can we hope to prevent this disruption.

This article explains how we as individuals and as a society can survive and thrive in this complex age.

Back in the nineteenth century when the industrial revolution was in full swing, the philosopher Friedrich Nietzsche shrewdly said that people needed a “sixth sense.” In other words, he meant that, as a society, humans would need to develop another instinct in order to keep up with the pace of technological change.

Today, it’s necessary for people to develop a Seventh Sense to comprehend the complex connections of networks which have formed between people, mobile devices, computers and financial markets as a result of technological advancement.

To develop a Seventh Sense, you first have to understand that everything is interconnected. Take the unveiling of the first iPod in 2001. The device not only fundamentally changed the way people listen to music; it altered the music industry itself. After the product was launched, people stopped using Discmans, and CD shops began to close while MP3 sales flourished. Eventually, this led to the rise of streaming services such as Spotify.

As technology moves rapidly, old network systems are frequently replaced by new ones – the author refers to this process as network power.

To understand network power, look at the way that English is presently used as a global lingua franca. The language enables information to be shared in a simple manner among people from different countries across the world.

Currently, switching languages seems inconceivable. However, eventually, lingua francas like English will be replaced with real-time machine translation between many languages because that is the nature of network power.

Advanced connectivity has allowed this technology to develop. One day, you’ll be able to jump into a taxi in Madrid and say “good morning,” and your taxi driver will instantly hear “Buenos días.” There will come a time when a translation algorithm will be more vital than having the ability to speak and comprehend English.

Rewind to the dawn of the internet age is more far-reaching than anyone could have anticipated.

Pentagon analysis team surveyed records of terrorists’ deleted phone calls and SMS and discovered that terrorist networks were developing at a much faster rate than the government or military were able to monitor.

In 2003, US troops learned that a terrorist in Baghdad had managed to conceive a way to make a bomb that was able to penetrate American tanks. A mere ten days later, an identical bomb killed a US official in rural Afghanistan.  The terrorists’ network of communication was simply more advanced.

Even newly recruited, barely educated terrorists on the internet manage to elude the government’s old-fashioned, slow systems. The Pentagon’s task force, known as the Joint Improvised Explosive Device Defeat Organization (JIEDDO). Found that terrorists tended to visit sites containing instructions on how to make bombs. Other terrorists would also provide real-time advice in encrypted chat rooms. The American government was unable to gain access.

To combat their activity, JIEDDO installed devices to monitor the streets. Although this plan worked to prevent individual attacks, it did nothing to address the heart of the problem.

Historically, emperors, presidents, kings, queens and authority figures like doctors or lawyers have presided over power and influence in predetermined hierarchical structures……

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How technology is shaping smart cities

Humanity is going urban. Today, more people live in urban areas than ever before, with a whopping 54.293% of the world’s population being concentrated in cities. While this has a number of economic benefits, the mass rural-urban migration has created challenges in terms of resources being spread too thin, and deepened the divide between the rich and the poor. It’s no surprise, then, that more and more countries are working towards creating Smart Cities that leverage internet and communication technologies to elevate the quality of residents’ lives and further economic growth. And as with everything ‘smart’, the one thing that has played an integral role in the development of these cities is technology.

While the impact of innovations like smartphones and the internet is widely known, up-and-coming developments like blockchain, artificial intelligence and augmented reality are playing key roles in shaping Smart Cities, and here’s how:

e-Governance

Even the most well-planned cities and countries can crumble if they aren’t backed by good governance, which, in an increasingly digital world, is synonymous with e-governance.

The benefits of e-governance are perhaps best illustrated in the case of Turkey, where the social assistance platform is used by 16 public institutions and has been found to save time and resources, in addition to boosting transparency and accountability.

mHealth

Too many people lose out on access to high quality healthcare because of geographical distance. Fortunately, the advent of mHealth is bringing people virtually closer to top-notch practitioners and facilities at the click of a button.

Healthcare helplines, e-diagnostics, mobile applications that bring medication and practitioners to a patient’s doorstep, and medical records stored on the cloud are some of the innovations revolutionising healthcare.

Open Education

Education is one of the tenets of a Smart City, and technology is revolutionising the way people learn.

Massive open online courses (MOOCs) have made lessons and professors from the world’s leading universities available to anyone with an internet connection. And that’s not all. Their voluntary nature means MOOCs help people develop and hone skills beyond what conventional education has afforded them, fostering a culture of lifelong learning.

Open Data Initiatives

So far, governments have rightfully kept data about their citizens closely guarded. And while individuals’ security and privacy are of the utmost importance, open data initiatives are gaining popularity across the globe.

Not only do they increase transparency in the functioning of a government, but innovators and academics can also learn from this data and use it to improve operations in their city.

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The 5 Most Promising Companies in AI Development

Whether it’s stealing our jobs or helping us diagnose disease, artificial intelligence is going to have a huge impact on the future of humanity. Research on how to make machines learn and think like people is one of the hottest areas of technology right now, but some companies are clearly at the forefront. Here are the five companies making the biggest contributions to AI right now.

Google

Google has invested heavily in AI research. In fact, almost every publication coming out of Google’s research arm right now has something to do with neural networks. The company’s work has led to awesome user-facing features like Google Assistant, Google Photos, and HDR+ photography. Knowing there’s a shortage of engineers with the training to build these systems, Google has even rolled out a DIY cloud AI platform for developers called AutoML. Its TensorFlow AI platform is fast becoming an industry standard.

IBM

Who can forget Watson’s appearance on Jeopardy back in 2011? The AI trounced the human players, but that’s not why IBM created it. Watson is a collection of algorithms for understanding natural language and processing massive amounts of data in fields like healthcare and cybersecurity. IBM doesn’t have the same user-facing profile it once did, but businesses could use the Watson platform a lot in the future.

DeepMind

While DeepMind is technically part of Google, it’s operated as an independent entity and focuses on pure research. It’s also responsible for some of the most impressive feats of AI engineering from a purely scientific standpoint. DeepMind researchers succeeded in building an AI that could defeat the world’s best Go players, and many thought that game would be too complicated for a machine ever to win. It’s also developed better voice synthesis and taught AI to navigate a parkour course.

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Reset Ellen Pao Summary

Reset Ellen Pao Summary – The Pao vs. Kleiner case garnered some heavy media attention, and there’s a good chance you’re aware of it. But perhaps the struggles and obstacles Pao had to endure leading up to the trial are less well known.

What was it like working at Kleiner? What were the challenges faced by Pao and other women working at the firm? And how did she come to pursue a lawsuit against one of the most powerful venture capital firms in the world?

This article will give you an insight into the events leading up to and surrounding the case, as well as how Pao dealt with the blow of losing to Kleiner.

Ellen Pao grew up believing that a good education would inevitably lead to success, and so when she graduated from Harvard Law School in 1994, she saw endless career opportunities laid out in front of her. When she began working at the well-known New York City law firm Cravath, Swaine & Moore as a corporate lawyer, however, she quickly realized things weren’t going to go quite how she’d expected.

One of the things Pao noticed was that sexual discrimination had become so deeply rooted in the workplace that it often happened without anyone noticing it, sometimes not even the person on the receiving end.

A coworker who was black and female was constantly mistaken for an administrative assistant or a paralegal, despite being dressed in suits donned only by attorneys. Furthermore, even though as a lawyer she had the authority to use company cars, Pao’s coworker faced difficulties in doing so.

At the time, Pao’s coworker didn’t think too much about it, and thus never reported what happened. Ultimately, however, she was so distressed by these experiences that she ended up leaving the profession entirely.

The case of Pao’s coworker serves as a reminder of how it’s nearly impossible to ascend the corporate ladder if you’re not one of “the boys,” despite your hardest efforts.

Pao relates a time when the head of her department invited 12 male coworkers to dinner, following it up with a visit to a strip club. Pao pointed out that going to the strip club allowed the male coworkers an opportunity to get to know their boss on a more personal level, which is a massive advantage.

These men-only events happened all the time. Pao managed to get a ticket to a hockey game once, but she was only allowed to come if she didn’t sit beside the senior partner.

Such behaviors excluded women from important conversations and opportunities, and as a result, they had to double their efforts just to keep pace with their male counterparts.

Pao finished her two-year MBA at Harvard Business School and in 2005 joined the influential venture capital firm Kleiner Perkins Caufield & Byers as chief of staff. Venture capital firms receive financial support from wealthy individuals, universities, families and pension funds, which they invest into startups, hoping for a return on investment.

The venture capital industry is dominated by men, being a real “boys club”, and is predominantly white.

On a business trip to New York, Pao shared a table with four white male colleagues. One of whom was a tech CEO and investor named Ted. The tech CEO expressed his desire to have a woman join his board. Which consisted of only men, and Pao suggested that he invite one of Google’s founding partners, Marissa Mayer. Upon Pao’s suggestion, Ted said Mayer would be too controversial.  While the rest of the men remarked that they would like her to join because she was hot.

The men at the table then continued to openly discuss the type of sex worker. They liked and bragged about meeting Jenna Jameson, a porn star, leaving Pao cringeing and uncomfortable. She was aware that the male colleagues didn’t like her being there.  And the men organized a night out without extending an invitation to Pao. As a result, Pao missed out on the exchange of advice and information that occurs during these men-only events.

During the early days of Twitter. Pao saw promise and potential in the platform’s ability to connect people all over the world. And so she decided to get in touch with their CEO, Jack Dorsey. She then pitched Twitter to a partner at Kleiner, but he showed no interest and dismissed her proposal.

Almost four years later, Kleiner would finally invest in Twitter, upon the suggestion of a male junior partner, of course. By that point, Twitter’s value had gone up by 400 percent.

Though she was aware of the inequality rampant in the world of venture capital. Pao decided to stay at Kleiner because she enjoyed the work……………

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Five myths about artificial intelligence

Artificial intelligence is the future. GoogleMicrosoftAmazon and Apple are all making big bets on AI. (Amazon owner Jeff Bezos also owns The Washington Post.) Congress has held hearings and even formed a bipartisan Artificial Intelligence Caucus. From health care to transportation to national security, AI has the potential to improve lives. But it comes with fears about economic disruption and a brewing “AI arms race .” Like any transformational change, it’s complicated. Perhaps the biggest AI myth is that we can be confident about its future effects. Here are five others.

MYTH NO. 1

You can differentiate between a machine and a human.

It is certainly true that conversations with AI chatbots are often unintentionally funny. And no one who interacts with Alexa or Siri or Cortanais going to say they pass the Turing Test. “Their responses, often cobbled together out of fragments of stored conversations, make sense at a local level but lack long-term coherence,” Brian Christian wrote in a 2012 Smithsonian Magazine article. Garbled sentences and ridiculous responses often make clear just how poorly machines mimic human capabilities — or even, sometimes, how they process information. “Machines don’t have understanding,” Garry Kasparov told TechCrunch last year. “They don’t recognize strategical patterns. Machines don’t have purpose.”

But AI is already writing financial news, sports stories and weather reports, and readers aren’t noticing. From the Associated Press to The Washington Post, it’s becoming increasingly common. AI is also producing “deep fake” videos — from invented speeches by politicians to pornography featuring celebrities’ computer-generated faces — that many people think are real. These rapid advances present significant concerns, shaking the public’s confidence in what they see and hear. As a 2017 Harvard study warned, “The existence of widespread AI forgery capabilities will erode social trust, as previously reliable evidence becomes highly uncertain.”

MYTH NO. 2

The U.S. is falling behind in the race for AI breakthroughs.

China’s national strategy to lead the world in artificial intelligence — which calls for “the training and gathering of high-end AI talent” — has elicited fear and loathing in the United States. “China’s prowess in the field will help fortify its position as the dominant economic power in the world,” Will Knight observed in MIT Technology review in 2017. Writing in the Hill, Tom Daschle and David Bier warned in January that “the U.S. government is behind the curve.”

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Google’s Sergey Brin warns of the threat from AI in today’s ‘technology renaissance’

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Intelligent AI: why London is the global capital of machine learning

DeepMind is one of the best known AI companies in the world and it could only have started in London

Next time you’re at King’s Cross station, take a moment to think about this. Just yards from where you’re standing, the world’s most advanced artificial intelligence (AI) technology is being developed — by a London company called DeepMind.

You might assume that when it comes to AI, like lots of other new technologies, it’s Silicon Valley or Israel that’s out in front. The truth is that something incredibly special is happening in our city right now.

Today London is the global powerhouse of AI — the fiendishly difficult task of getting software and machines to perform tasks that require human intelligence to do.

The reason this is such an important area of technology is that experts believe it could transform entire industries, much like the internet has done — and might have a big impact on the way we work.

So it really matters that we’re leading the way. The benefits for our city in terms of growth, high-paid new jobs and investment could be huge.

To understand why the AI revolution is being spearheaded here, we need to look at the story of DeepMind, which was founded in London in 2010.

I first met the DeepMind team in 2013, in their first offices close to Russell Square. They’d chosen that location to be close to the brain science expertise of University College London in Bloomsbury and research prowess of the Wellcome Trust on Euston Road.

The founders of DeepMind believed that they’d have an edge over their rivals if they could take the most up-to-date analysis of how human brains work, and use it to design intelligent computer programmes.

As one of the company’s co-founders, Demis Hassabis, puts it: “You can harness insights from neuroscience to make software that can learn more quickly and effectively — and overcome some of the obstacles that had been holding back progress in AI for years.”

It turns out London is a much better place to do this than Silicon Valley — because San Francisco is totally dominated by the technology industry. Our city is the total opposite — the centre of more industries than any other metropolis, from media and politics to fashion and advertising.

And because so much innovation happens when different fields collide, it gives London a decisive advantage.

A good example is the way we have a massive financial services sector in the City, right next to the digital cluster in East London’s Tech City. As a result of these two spheres bumping into each other, we’re way ahead of the West Coast or Berlin in “fintech” — a valuable new field that’s changing how the banking system works.

For DeepMind, working in this interdisciplinary way was hugely effective — by combining neuroscience with computing, the team were able to leap ahead of everyone else.

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Sunday 29 April 2018

The Gatekeepers Chris Whipple Summary

The Gatekeepers Chris Whipple – There’s a story from the early days of the Eisenhower administration. Supposedly, soon after Eisenhower arrived at White House following his inauguration on 20 January 1953, a staffer came running up. He had a sealed envelope in hand, marked “private and confidential.”

Much to his surprise, the staffer got an earful. “Never bring me a sealed envelope!” yelled Eisenhower, “that’s what I’ve got aides for.”

He had a point. It wasn’t that Eisenhower was upset because he hated opening his mail. Rather, he knew that structures had to be in place to ensure that nothing was a surprise by the time it reached him. He knew he had to have capable, trustworthy and intelligent staff upon whom he could rely. He needed his gatekeepers.

The role of White House chief of staff embodies the concept of gatekeeper. At first, it was a relatively informal position, but now it is seen as one of the most important posts in the White House.

The story of the gatekeepers is one of power, control and influence. You’ll see how the greatest office of state in the world is run. But one thing will become clear: It’s not so much a question of who holds the reins of power, but who lets him hold them in the first place.

Richard Nixon’s reputation isn’t great these days, but he shaped the modern presidency through his use of a dedicated chief of staff.

Nixon’s Democratic predecessor, Lyndon B. Johnson – usually known as LBJ – hated the idea of concentrating power in one chief adviser. Instead, LBJ got personally embroiled in all the organizational aspects of the presidency. He opened letters and even arranged appointments with members of the cabinet himself. In doing this, he’d overstretched himself, and Nixon was determined not to make the same mistakes.

Nixon, therefore, turned to H. R. Haldeman to act as chief of staff. The role had existed before, but Haldeman shaped its modern form. Haldeman used his powers to organize procedures for White House staff.

For starters, he put a stop to the process of end running – gaining access to the president through lesser members of the administration. Those wanting to meet the president now had to go through the chief of staff first. This would keep the president focused on his main policy aims. Haldeman’s command over the administration meant he was the first person Nixon spoke to each morning and the last person each night.

It was also Haldeman’s responsibility to keep Nixon on the straight and narrow.

He wasn’t always successful though. The tape recorders that Nixon had installed to document Oval Office conversations provided evidence that Nixon wanted to illegally break into the Brookings Institute. He suspected that documents leaked to the media from the State Department were stored there.

On that occasion, Haldeman managed to restrain Nixon from authorizing the raid, but he couldn’t always keep his increasingly neurotic president in check.

The paranoia surrounding the White House led to the Watergate scandal, which involved forced entry and the planting of surveillance devices at the Democratic National Committee offices. Ironically, Nixon was caught on his own devices approving the payment for those who had broken in. His downfall soon followed.

Even though Haldeman wasn’t ultimately successful, the paradigm for the White House’s organizational staff system had been set.

The release of the incriminating White House tapes resulted in Nixon resigning on 9 August 1974. It was either that or impeachment.

Nixon’s Vice President Gerald Ford assumed the office. He’d need a strong chief of staff to prevent the same mistakes from occurring.

But it was a shaky start. Ford’s approval rating plummeted when he decided to issue Nixon with a free and absolute pardon to stop any possible indictment.

To stem the tide, Ford turned to Donald Rumsfeld to act as chief of staff. Rumsfeld had a reputation for no-nonsense discipline. His career in Congress demonstrated that he knew how to run a ruthlessly organized machine. He was the man for the job.

However, Rumsfeld had three conditions. He wanted absolute authority over the president’s schedule. He also demanded that he act as top adviser in all decision-making and that he would take a cabinet position as soon as one was free.

Ford agreed. Rumsfeld would put the White House back in order.

As part of his plan, Rumsfeld decided to delegate many tasks to his young deputy, Dick Cheney. They kept close to Haldeman’s playbook: schedules were tight, agendas meticulous, and the president was only given information relevant to the situation.

However, they couldn’t stop Ford from making public gaffes. Most memorably, in a 1976 presidential debate against Jimmy Carter, Ford claimed that there was no Soviet domination of Eastern Europe.

At one point in 1975, Ford found himself 33 points adrift from Carter in the polls. Rumsfeld saw that the writing was on the wall.

The Gatekeepers Chris Whipple – Consequently, Rumsfeld and Cheney sent a memo to the president, expressing their doubts and relating the changes that were needed to reverse his fortunes. Ford heeded their advice – his response was brutal. The Halloween Massacre saw a massive staff reorganization. Rumsfeld became defense secretary, and Cheney the new chief of staff.

It was no good. Although Ford managed to claw some points back, a difference of just 9,000 votes in Ohio and Hawaii meant that Carter would be the next president.

Carter’s successful presidential campaign team was led by Jack Watson – a Harvard Law graduate and Washington insider – together with Hamilton Jordan, a political strategist who’d been Carter’s primary advisor when he was governor of Georgia……

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Put a Google Assistant on your nightstand for $25

Insignia’s alarm-clock version of the Google Home makes a perfect addition to the bedroom — especially at this price. Plus: a Cheapskate-exclusive deal on Ecovacs’ new smart-vac!

This is a rerun of a deal from a few months back — and if you bought it last time, maybe just skip ahead to the bonus deals. Because, wow, the price dropped significantly.

I’ve said it before and it bears repeating: The Amazon Echo Dot makes a great addition to your nightstand — but it’s imperfect in two ways.

First, it has no display. Any bedside accessory worth its salt should be able to show you what time it is. Second, it’s a pretty weak speaker, which is why I always recommend pairing it with something bigger and better.

Or, you could just buy this: For a limited time, and while supplies last, Best Buy has the Insignia Voice Smart Bluetooth Speaker with Google Assistant for $24.99 shipped (plus tax). Regular price: $99.99. Price last time: $69.99. (I warned you: bigdrop.)

Available in all black or black and gray, the Insignia Voice is basically a Google Home designed for your nightstand. It’s a digital clock, an alarm and a smart speaker, one that’s large enough to deliver decent, room-filling sound — unlike the Dot or Google Mini.

Of course, if you prefer to sleep next to Alexa (so to speak), you’ll need a Dot. But if you’re just as happy with Google’s nameless Assistant (I don’t know why, but I want to call her “Barb”), the Voice gives you much of the same functionality.

For example, you can ask it to set an alarm (natch), tell you the weather, check traffic, look up movie showtimes, play music, request an Uber, control other smart-home gadgets and so on.

Indeed, it does pretty much everything a Google Home can do. The only thing it can’t do is make phone calls.

CNET hasn’t reviewed the Insignia Voice, but nearly 1,200 Best Buy customers collectively rated it 4.4 stars. Many of them praised the sound quality, noting that it was better than the Google Home’s. Some of the more negative reviews relate to a volume problem that appears to have been addressed with a firmware update.

I’m not sure I’d pay $100 for an alarm clock, even one with smarts. At $25, though? This almost makes me want to ditch my bedside Dot.

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Amazon has a new biggest bull on Wall Street, who predicts it will become the first trillion-dollar company ever in 12 months

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Who’s Firing? (Qualcomm, GoPro, and IBM—Again) Who’s Hiring? (Facebook, Apple, Amazon)

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1 Headwind IBM Will Face This Year

International Business Machines‘ (NYSE:IBM) return to growth after five years of declining revenue has been driven by a few different things. A weakening U.S. dollar has boosted the top line thanks to currency translation effects, the continued double-digit expansion of IBM’s growth businesses has offset slumping sales in some legacy businesses, and the launch of the newest z14 mainframe system has provided a boost to the hardware business.

The timing of the new mainframe system was just about perfect, coming when IBM absolutely needed to prove that it could grow. A 71% jump in mainframe sales during the fourth quarter of 2017 was enough to push IBM’s total revenue, adjusted for currency, about 1% higher. Momentum continued for the mainframe in the first quarter of 2018 with 54% growth, but currency-adjusted total revenue was just about flat.

Unfortunately, this strong mainframe growth probably won’t last. The initial spike in sales following a mainframe launch typically gives way once that launch is lapped. The z14 started shipping toward the end of the third quarter of 2017, so the second half of 2018 will likely feature a mainframe headwind that will test IBM’s ability to produce revenue growth.

The mainframe cycle

IBM refreshes its mainframe lineup every few years. The z14 was announced in July 2017, about two and a half years after the launch of the z13. Each new mainframe triggers some existing customers to upgrade. This creates a swell in mainframe sales, often lasting a few quarters.

After that initial surge, mainframe sales start to slump as the launch is lapped. That slump lasts until the next mainframe refresh, which starts the process over again.

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Saturday 28 April 2018

Get Better Todd Davis review (summary)

Get Better Todd Davis review – It may seem obvious, but every meaningful relationship, whether it’s personal or professional, requires a fundamental set of attributes, such as trust, credibility, and considerateness. But that’s only the foundation of what it takes to build and nurture a healthy relationship. Open-mindedness and our general attitude toward those around us is just as important.

In this article, you’ll find a toolbox full of tips and ideas that you can immediately start using to create a healthier work environment. With these tools, managers will be better equipped to build strong teams, not to mention construct safe and comfortable places where employees feel respected and appreciated. And any employee eager to improve relations with coworkers can use them, too.

It can happen to anyone: you think you have a complete understanding of something – and then, one fateful day, you discover that you had it all wrong.

Each of us experiences the world in a different way, but sometimes we get stuck seeing the world from a point of view that has room for only one truth. As a result, we adopt standard perceptions about ourselves and about others, and we begin to believe that this perception is the only reality.

You might get stuck thinking thoughts, such as, “I’m just not good enough,” “I’ll never change,” “My coworker is lazy” or “My friend is thoughtless.”

Here’s a common scenario: a coworker approaches you, saying that he’s frustrated with another colleague because he thinks that she’s so slow and lazy that she’s going to cause everyone to miss their deadlines. This is what the author, Todd Davis, was confronted with when his colleague Jon came to him with his concerns about their coworker Isabel. Now, Jon wanted Davis to talk to Isabel because Jon believed that he wasn’t a “people person.”

So, in Jon’s case, we have someone who believes himself to be bad at dealing with others and perceives Isabel as being slow and plodding. This is his truth, but it doesn’t have to be.

The better mindset is to reject narrow viewpoints about yourself, others and the world.

It’s your responsibility to take stock of your beliefs. Keep an open mind and hold yourself accountable for any narrow-minded perspectives you might have about yourself. The world or the people in your life.

You should also stay open to the perspective of others. The author reminded Jon that he was a good husband and father. Therefore, he likely isn’t so bad at communicating, and if he put his mind to it, he could probably have a productive conversation with Isabel. Perhaps he wasn’t as inept around people as he’d long believed.

Jon eventually realized that he’d unfairly labeled Isabel as slow and lazy, without taking the time to talk to her about it or understand her work ethic.

Here’s another unfortunately common scenario: A rude customer complains and you lose your temper, firing off a curt email in reply. After some time passes, you cool off and realize how badly you reacted.

In situations like these, we have a tendency to let outside factors, over which we have no control, dictate our mood and feelings.

For example, how would you react if you found out that a colleague had been secretly working on a competing project behind your back? Surely, you can imagine how this external event might result in your feeling brimful of bitterness the next time you saw the person.

When Todd Davis was a young recruiter. He hired a new colleague who managed to negotiate a salary that was far higher than his own. Davis was infuriated that his boss had approved this decision. Which made him feel as though his work were being undervalued and unappreciated. For days, he complained to friends and family while feeling unmotivated and in the dumps.

This is a common reaction to unpleasant external events, but there’s a far better way to deal. And the first step is to stop and quietly take a moment to reconsider the situation.

Pausing is a great way to stay in control of your mood and feelings. When you allow yourself to calmly stop and think about what’s happening. You give yourself the time to develop a more nuanced understanding of the situation. With calm reflection. You can begin to understand your feelings and why you’re tempted to react in certain ways. Which can lead to better solutions than casting yourself as the victim.

After days of complaining, Davis finally paused to consider the situation and he came up with a much better response. He thought to himself, “Why not talk to my boss and ask for a raise?” Sure enough, his boss was receptive to the idea of raising his salary. As long as Davis worked a bit faster on his recruitment tasks in the future.

So remember to cool down, breathe and take five minutes to think things over.

You’ve probably heard about how important trust is to any successful relationship. It’s true – if people don’t think you’re credible, chances are they won’t have much respect for you.

So the challenge is……..

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Why IBM Is An Attractive Turnaround Bet

Will International Business Machines manage to pull off a convincing recovery that some loyal Big Blue bulls suggest?

Once the kingpin of the technology universe, IBM has become a lumbering monolith whose stock has lagged behind its more spirited and sprightly peers, such as Facebook, Google and Microsoft. Currently trading at $145 a share, shares of IBM are way down from its high of $215 in 2013, and is also below its 52-week high of $179.

So is there a light at the end of the proverbial tunnel for IBM? Surprisingly, a number of devoted IBM believers remain undeterred in their optimism that hope definitely exists for the long-awaited IBM turnaround. So what’s holding it up? But there are also disbelievers who are as spirited in their disenchantment, who doubt that an IBM recovery is coming anytime soon.

One major reason for IBM’s travails is competition has been surprisingly fierce in the ever-expanding technology space.

“IBM competes in several concentrated and rapidly evolving markets, and faces competition from cognitive solution vendors, global business, and technology service vendors and systems vendors,” notes Arvind Ramnani, equity analyst at KeyBanc Capital Markets.

But even as he maintains a rating of “sector weight” on the stock, Ramnani argues that as IBM continues to transition its business model, “the pronounced near-term weakness could be an opportunity for patient investors.” He puts the stock’s “fair value” at $160 a share, based on 11 his 2019 earnings projection of $14.44 a share. IBM’s revenue growth in 2018 is positive and continues to be on a double-digit growth pathway, Ramnani points out in a recent note to clients. He sees IBM revenue growth continuing to accelerate in 2018 an 2019.

Nonetheless, he also points to certain risks that weigh on the stock, among them his contention that IBM failed to commercialize a “consistent stream of timely innovations” that Ramnani believes may adversely affect the company’s brand image, market share, and profit margins.

Even so, there are several IBM bulls who are still steadfast in their support of the stock, emphasizing that IBM is certainly in a better position now than in the prior year. The big question that investors are asking, however, is whether IBM’s efforts to reposition its business will pay off — and when it will come to fruition.

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Article Credit: Forbes

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Who will fix our Internal Banking Mess? TSB hires IBM amid online banking woes

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Why an Investor Is Predicting Bitcoin Could Hit $700,000

The annual Sohn Investment Conference in New York is usually a place where Wall Street’s best hedge fund managers and investors present their top stock picks—from Amazon to Valeant Pharmaceuticals. And for the first time in the event’s 23-year history, one of those investors used the Sohn conference stage Monday to recommend a certain digital investment: Bitcoin.

John Pfeffer, a partner at his London-based family office Pfeffer Capital, is not only betting on Bitcoin, but giving it a bold price target of $700,000—about 75 times the current Bitcoin price of nearly $9,500.

While Pfeffer did not put a time frame on his prediction, his target exceeds even optimistic forecasts from other influential investors such as venture capitalist Tim Draper, who earlier this month predicted the Bitcoin price would reach $250,000 by 2022.

“Bitcoin is the first viable candidate to replace gold the world has ever seen,” Pfeffer, a former partner at private equity firm KKR, told the crowd at the Sohn Investment Conference at New York’s Lincoln Center. “So if Bitcoin becomes the dominant non-sovereign store of value, it could be the new gold, or new reserve currency.”

Pfeffer’s math works like this: First, he assumes that Bitcoin can logically replace all of the gold bullion currently held by private investors—in other words, the gold bars that people keep in a safe-deposit box or bury in their backyard, simply as a way to park their money in something more dependable than paper. (The gold bars in this example are also what’s known as a “store of value.”) “Bitcoin is vastly easier to store and secure,” Pfeffer said.

The current value of all privately held gold bullion is about $1.6 trillion, according to Pfeffer. Assuming there will be 18 million Bitcoins in circulation by the time the cryptocurrency fully replaces gold bullion (about 17 million Bitcoins have been produced so far, out of the maximum 21 million that can exist), the implied value of a Bitcoin would then be $90,000. This is Pfeffer’s most conservative scenario, which he gives 8% odds of coming to fruition.

But Pfeffer has even higher hopes for Bitcoin—that it could eventually be to central banks what traditional foreign reserve currencies are today. (From euros to Japanese yen, governments hold foreign cash to pay down international debts and complete other cross-border transactions.) “It’s imaginable that Bitcoin displaces some form of reserves over time,” Pfeffer said at the conference.

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Article Credit: Fortune

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Mining Rewards Show You What The Bitcoin Price Will Do

We all need leading indicators to try and predict the future. For me, for Bitcoin and altcoins, an important one is the swings in value of mining rewards.

I consider the 1080ti GPU from Nvidia as the benchmark altcoin mining hardware for anyone mining altcoins. While ASICs demand awe, GPUs are the smart way to get into mining – low risk and frankly fun.

With an ASIC you buy a dodgy piece of fire hazard equipment, that is only good for one or perhaps two algos, that eats electricity, devalues before your eyes and might be ‘bricked’ by the time you get it.

With a GPU, you get a piece of kit you can sell tomorrow to gamers, that can mine a universe of old and new coins, doesn’t sound like a jet engine which will probably damage your hearing and get you cited by the city.

[Ed note: Investing in cryptocoins or tokens is highly speculative and the market is largely unregulated. Anyone considering it should be prepared to lose their entire investment.]

GPUs are the sweet spot for amateur miners and the 1080ti is the sweet spot amongst the GPUs.

Nvidia hate miners but I’m sure they secretly like the giant price premium they have created for their equipment. It can’t be bad for their brand that people will pay hundreds of dollars more for a 1080ti GPU.

A few weeks back a 1080ti was earning as much as $8 a day. This meant a miner could get their investment back in under four months. Happy days. Bitcoin had bounced from around $6,000 to $10,000 and rewards for mining had doubled.

Then general mining rewards started to dive, and then so did Bitcoin. A 1080ti hit $1.40 a day in mining rewards before they began to rally alongside the cryptomarket. The climb has taken the daily mining reward to a current $2.40 a day.

Often changes in mining rewards lead the Bitcoin price and as such are a very useful indicator of what will happen next in cryptocurrency prices. In a market as volatile as the cryptos a trader needs all the indicators they can get and the closer they are to the basic demand and supply fundamentals the better.

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Article Credit: Forbes

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Friday 27 April 2018

Adaptive Insights Integrates Business Planning Cloud with NetSuite ERP

Adaptive Insights recently announced the integration of its Adaptive Insights Business Planning Cloud with NetSuite ERP. The combination of data from NetSuite ERP and Adaptive Insights Business Planning Cloud gives customers the requisite insights for making better and faster decisions.

The Adaptive Insights Business Planning Cloud’s integration with NetSuite ERP uses open APIs and is built, owned, supported, and maintained by Adaptive Insights. The integration enables customers to utilize all their data in NetSuite ERP to effortlessly develop plans as well as reports with Adaptive Insights. Furthermore, the Business Planning Cloud facilitates importing an expanded set NetSuite standard and custom dimensions, thus giving customers access to a wider group of operational and financial data to enable users across the entire organization. This, in turn, facilitates deeper analyses, reports, and richer plans that driver more informed decision-making.

Tom Bogan, CEO, Adaptive Insights, said, “Planning is where strategy and execution meet; in developing a plan, you figure out how to execute your business strategy. A smooth and efficient planning process, informed by data about current business performance, is key to being able to make timely decisions. That’s why companies that want business agility are moving to companywide business planning, and why they’re integrating functional planning into our Business Planning Cloud. We pioneered cloud planning for finance and NetSuite pioneered cloud ERP. Together these purpose-built cloud platforms offer companies an integrated platform that enables far more business users to plan, analyze performance, and speed their decision making—and that’s a true competitive advantage today.”

Adaptive Insights Business Planning Cloud Makes Its Way to France

Besides that, the company recently also announced the introduction of Adaptive Insights Business Planning Cloud in France. Adaptive Insights noted that France constitutes one of its core markets and that it will continue to invest in support, services, and sales resources to meet growing demand in the region.

Adaptive Insights has established a team in-country, which includes a new channels director to oversee its French partner sales operations. The French channel network currently includes partners such as Censio, Alsight, Iena, Generation Conseil, ViaReport, and Kelerian Group.

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Article Credit: RIQ

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Predictive analytics power cyber-insurance industry

The rise in predictive analytics is revolutionising the insurance industry by enabling savvy insurers to predict risk

Dramatic advances in artificial intelligence and machine-learning technologies have accelerated the ability of insurers to predict risk. Algorithms can find trends and patterns that help forecast the probability of a risk situation occurring again.

By utilising internal and external data sources, algorithms are selected according to how a specific model fits with the insurer’s data. This model is applied to predict or detect the likelihood of an event happening, such as a person needing medical attention abroad for travel insurance or a house flooding for home insurance.

Insurance and assistance provider The Collinson Group uses a variety of predictive analytical tools to flash through terabytes of data to find variables, some of which it hadn’t considered, to help predict customer risk and purchasing behaviour.

With this technology, the company is able to identify fraud and the different networks of fraudsters acting in the market, as well as increase its understanding of customers, and ultimately tailor its offering to provide them with better products and services.

“Predictive analytics has enabled a more scientific approach to analysis, allowing us to analyse more data in little or no time, and to explore parameters and factors we could not have identified with the human eye,” says Jean Ortiz-Perez, the company’s head of analytics. “The concept and objective of what we do have not changed, but the mechanisms and techniques are now much more sophisticated.”

The role of predictive analytics in insurance can actually be traced back two or three decades in the area of natural catastrophes and climate. Analysis of 50 years of data on hurricanes, for example, has proven extremely powerful in terms of helping insurers to predict future hurricane behaviour and its likely impact.

However, this has required a large amount of human input and oversight. More recently property and liability insurers have been playing catch-up with the life insurance sector, where a rich trove of available data, including longevity, gender, country and quality of life, has allowed for clearer analysis and confident predictive outputs.

The rapid evolution of machine-learning capability and the wider availability of data through connected devices are now set to make the use of predictive analytics ubiquitous across the industry. And to accelerate the necessary collection of data, new health insurance models are emerging that actively link premiums to analytics.

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Article Credit: Raconteur

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Why data analytics initiatives still fail

Strong data analytics is a digital business imperative — and it all begins with smart data governance practices and an emphasis on quality and context.

Executives talk about the value of data in generalities, but Michele Koch, director of enterprise data intelligence at Navient Solutions, can calculate the actual worth of her company’s data.

In fact, Koch can figure, in real dollars, the increased revenue and decreased costs produced by the company’s various data elements. As a result, she is well aware that problems within Navient’s data can hurt its bottom line. A mistake in a key data field within a customer’s profile, for instance, could mean the company can’t process a loan at the lowest cost.

“There’s money involved here, so we have a data quality dashboard where we track all of this. We track actual and potential value,” she says.

An early data-related initiative within Navient, an asset management and business processing service company based in Wilmington, Del., illustrates what’s at stake, says Barbara Deemer, chief data steward and vice president of finance. The 2006 initiative focused on improving data quality for marketing and yielded a $7.2 million ROI, with returns coming from an increased loan volume and decreased operating expenses.

Since then, Navient executives committed themselves to supporting a strong data governance program as a key part to a successful analytics effort, Koch says. Navient’s governance program includes long-recognized best practices, such as standardizing definitions for data fields and ensuring clean data.

It assigns ownership for each of its approximately 2,600 enterprise data elements; ownership goes either to the business area where the data field first originated or the business area where the particular data field is integral to its processes.

The company also has a data quality program that actively monitors the quality of fields to ensure high standards are constantly met. The company also launched a Data Governance Council (in 2006) and an Analytics Data Governance Council (in 2017) to address ongoing questions or concerns, make decisions across the enterprise, and continually improve data operations and how data feeds the company’s analytics work.

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Article Credit: CIO

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Thursday 26 April 2018

SAP launches manufacturing cloud

In an effort to help companies optimise performance, elevate production quality and efficiency and ensure worker safety, SAP has announced a new solution called SAP Digital Manufacturing Cloud.

The company’s new solution draws on its expertise in the Industrial Internet of Things (IIoT), predictive analytics and supply networks to allow manufacturers to deploy Industry 4.0 technologies in the cloud.

SAP Digital Manufacturing Cloud complements SAP’s manufacturing portfolio of on-premise solutions to serve both large and small manufacturers in discrete and process industries.

Customers can choose either the SAP Digital Manufacturing Cloud solution for execution to provide all solutions in the manufacturing cloud portfolio or the SAP Digital Manufacturing Cloud solution for insights which focuses on performance management and predictive quality.

SAP Digital Manufacturing Cloud for execution offers businesses an Industry 4.0-enabled shop floor solution that features “lot size one” and paperless production capabilities.  By integrating business systems with the shop floor, this solution allows for complete component and material-level visibility for both single and global installations.

SAP Digital Manufacturing Cloud for Insights provides centralised, data-driven performance management which enables key stakeholders to achieve best-in-class manufacturing performance and operations.

Member of the Executive Board of SAP SE, Products & Innovation, Bernd Leukert provided further details on the reasoning behind the firm’s new offering, saying:

“Manufacturers in the era of Industry 4.0 require solutions that are intelligent, networked and predictive. Our manufacturing cloud solutions help customers take advantage of the Industrial Internet of Things by connecting equipment, people and operations across the extended digital supply chain and tightly integrating manufacturing with business operations.”

SAP Digital Manufacturing Cloud is expected to be available by the end of Q2 2018.

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Article Credit: ITProPortal

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SAP Ariba and the digital Manufacturing Network

SAP Ariba and SAP have launched the Manufacturing Network. This is a cloud-based platform to connect enterprises with manufacturing service providers so they can collaborate on multiple stages, from initial design through to procurement execution.

By collaborating on design, manufacturing and procurement in a coordinated way, enterprises can improve production and costs as well as facilitate innovations and new operating models. In this context, 3D printing and manufacturing as a service can fuel business growth.

Manufacturing today is more distributed and global than ever before” said Vasee Rayan, Vice President, Solutions Management, Ariba Network. “To do it well, companies must connect people, processes, things and information, and that’s what networks are all about.”

The relevance of the Ariba Network

More than 3M buyers and suppliers connect to the Ariba Network. They already use this to transact over $1.6T in commerce (on a yearly basis). With the Manufacturing Network, enterprises will be able to combine the advantages of network effects (from all those ‘members’) with their own knowledge ‘held’ within an enterprise’s existing SAP applications with their domain depth. The intention is that collaboration can occur in new ways and help manufacturing.

Interested customers will find the Manufacturing Network:

  • delivered as part of the SAP Digital Manufacturing Cloud Suite
  • integrated with SAP Ariba Sourcing and the Ariba Network.

This will make it simpler for manufacturers and service providers – including suppliers of 3D and computer numerical control (CNC) printing services and materials, original equipment manufacturers (OEM), and technical certification companies – to connect and collaborate. This can start with design, incorporate quality objectives, develop production and enable procurement execution.

The platform and its implications

Using what is in effect a platform, manufacturers (buyers) will be able to integrate design, sourcing, manufacturing,  procurement processes and manage of these to:

  • collaborate on design, highlight changes and suggest alternatives
  • link design discussions and data to requests for quotations (RFQs)
  • obtain pricing –  from one or multiple suppliers – for part(s)
  • initiate buying processes
  • embed the data and processes required for production part approval into the sourcing process (make this visible across all downstream procurement)
  • share data and key performance indicators (for example with relevant parties)
  • co-ordinate with suppliers on manufacturing changes.

At the same time, suppliers will be able to develop new ways to work with, and deepen the interactions, with manufacturing buyers. For example they might expand their business by leveraging the platform to:

  • differentiate themselves through technical skills and capabilities
  • gain clearer understanding of the buyers’ needs for engineered and production parts
  • collaborate on and perfect early designs
  • provide manufacturing capabilities as a service.

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Article Credit: Enterprise Times

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SAP addresses the questions on its licensing and auditing news – an influencer event analysis

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What To Watch For In SAP’s Q1 Earnings

European software giant SAP SE (NYSE: SAP) is scheduled to announce its first quarter earnings on April 24.We expect over 6% revenue growth in 2018, and believe that the fiscal first quarter growth will be along similar lines. We expect growth across business segments, as the company has maintained leading positions in the Enterprise Resource Planning and Supply Chain Management software markets, as well as a solid position in the CRM software market. The recent addition of multiple Internet of Things (IoT) solutions to the SAP Leonardo digital innovation system highlights SAP’s renewed focus on bolstering its foothold in the IoT domain, which could drive the company’s top line in the future. The company’s cloud and software gross margins saw a marginal decline, but a substantial improvement in its services gross margin led to a slight improvement in overall margins. We expect cloud margins to continue declining in the near term, as SAP faces tough competition from software behemoths like Microsoft, Oracle, and Salesforce. You can modify our forecasts for the company in our interactive dashboard to assess their impact on revenues and come up with your own forecast.

Cloud Business Stands Out

SAP’s Cloud business, aided by an impressive increase in new bookings, was the standout performer over the past few quarters. The company continued its dominance in the Enterprise Resource Planning software market, with customers continuing to adopt its S/4HANA platform. Moreover, with around 80% of its customers still using the earlier platform and expected to shift to the newer one in the near future, we believe the customer count will see further improvement. We forecast around 5% growth in SAP’s ERP revenue for the full year and expect the Q1 results to reflect similar growth.

SAP is also rapidly expanding its presence in the IoT space with new products and acquisitions. This space could drive substantial growth for SAP over the long run. Combined with its ongoing efforts to strengthen its offerings in the machine learning space, the company is expected to do well in the competitive software industry.

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Article Credit: Forbes

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