Friday, June 28, 2013

SAP Hana as an OPEX? Yes it is true!

http://virtualizationofsap.blogspot.com/2013/06/your-sap-hana-as-opex-no-its-true.html

Thursday, June 6, 2013

NFL Player Analysis with Lumira Suite By: Drew LeBlanc

As the temperature rises and summer goes into full swing we know this signals the start of a number of things- cookouts, pool and beach time, summer camps for the kids and of course football season. While that last one may seem like the odd man out here, true football fans know that it is never too early to be talking about next season. As a New England Patriots fan, one of the biggest stories of the off season was the replacement of our longtime wide receiver Wes Welker with a relatively newer player Danny Amendola. For those that aren’t familiar with the names or situation, basically it was a case of an older, aging player (Wes Welker) who wanted a lot of money and a team deciding they would rather spend less on a younger, but more unproven player (Danny Amendola).

The debate of which way the team should have gone was a rather polarizing one, leaving diehard fans on both sides of the fence. But while most people were talking about the stats and the player’s on field performance, they were neglecting maybe the most important piece: the money. To help settle this debate I decided to turn to the numbers and compare both the performance numbers as well as the less talked about salary figures, and what better way to do it than with the brand new SAP Lumira Suite!

The first step I took was collecting the data. While I already had the player performance data like yards and touchdowns, I needed to combine this with the player’s salary so that I could see the correlation. Once I collected the salary data (from spotrac.com) I used SAP Lumira Desktop to merge it with the player performance data that was already loaded. As you can see in the picture I get a 12% match with the player ID key which would be higher but I only pulled salary data for a select few players that I wanted to compare.

NFL Blog- 1.PNG
Now that I merged my data together I was able to compare the player’s on the field numbers with how much they were being paid. In the first chart below I left the salary numbers out, using only the total touchdowns scored and how many yards each player gained as the two values (the two main factors players are measured on). I filtered on all of the Patriots running backs and receivers from last year as well as the new player, Danny Amendola, so that we could compare.  Because there are a good deal of injuries in football and players miss various amounts of games, I averaged the totals to see how many yards and touchdowns these players earned per game instead of comparing the season totals.

NFL Blog 2.png


In the chart there are really two outliers: the yellow dot which represents the tight end Rob Gronkowski whose average of over one touchdown per game is pretty astounding. The other outlier is our topic of conversation Wes Welker who is fairly high on touchdowns but stands out even more for the yards gained per game at almost 100. Based on this chart we can see why people are upset that he’s leaving. Our new player Danny Amendola is represented by the light green dot that falls in the middle, not terrible but certainly not the caliber of the other two players mentioned.

Now let’s bring the salary numbers into the comparison. In the chart below we’ve added the players 2012 salaries, which are represented by the bubble size with the largest bubbles being the biggest salaries.

NFL Blog 3.png


By adding the salaries in, it really changes the dynamic of how we look at each of these players. While in the previous chart we saw Wes Welker (represented as the dark green bubble above) as one of the best players in the grouping, it is obvious here that he is also by far the highest paid player in the group. In comparison, the next closest player Aaron Hernandez (dark blue bubble) has a salary three times less than Welker, even though his performance numbers are only incrementally smaller than Welker’s.  After looking at this chart, it starts to become clear that while Welker may have been the best player on the field, he certainly was not the best value of performance per dollar.

While this comparison alone was valuable, I wanted to compare multiple other measures at the same time as well as share my findings with the colleagues who I’ve so hotly debated the topic with, so the next step was publishing this to the Lumira Cloud.

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Once published into the cloud, I was now able to analyze the data even further, bringing in up to eight different measures and dimensions at the same time. 

One of the other parts I wanted to analyze was that the Patriots only wanted young players and Welker was too old for them.  In the chart below I took all the players we saw before and grouped them by the year they entered the league. We then plotted it by their 2012 salary (y-axis) and 2013 salary (x-axis) along with the performance data points represented by color and size.  When we analyze this it becomes clear that the Patriots are in fact investing the majority of their money in young talent and getting a great return on it. You can see Welker represented by 2004 at the top right of the chart, but the bulk of the Patriot’s money is actually going to players 6+years younger with 2010 being further right along the salary axis. The size and dark color of 2010 and 2011 also denotes the fact that this is where the bulk of the Patriot’s stats are coming from as well.

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Finally, I wanted to specifically compare Danny Amendola with Wes Welker in a week by week comparison from last year. Using the animation feature in Lumira Cloud I was able to roll through each week quickly comparing how both players performed throughout the season. While it doesn’t show up as great on paper, you can see in the example below how I can click play and stream through each week with the added animation feature and see that Amendola actually had several weeks where he out performed Welker.

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In the end, the final judgment of what player the Patriots should have signed will be made on the field in this upcoming season. But through analytics we
were able to compare not only the often talked about on the field stats but the less talked about factors like salary and age which contributes just as much if not more than the on the field stats to the decision making process. After all, this is a business and just like any other business what it ultimately comes
down to is a return on investment, and what this showed us was that maybe it’s not as simple as just taking the best player on the field

FEBRUARY 19, THE DAY THAT BIG DATA IN HEALTHCARE WENT MAINSTREAM

February 19 could mark the day in history
where big data in healthcare and disease prevention hit the mainstream. Two significant
events happened that will shape the future of big
data usage in the prevention of diseases and the
speed in which diseases can be cured.
The announcement that three of Silicon Valley's
stars were funding a life sciences prize to help
promote scientific endeavours aimed at identifying and eradicating diseases was met with widespread praise. Mark Zuckerberg (founder and
CEO of Facebook), Sergey Brin (Founder and CEO
of Google) and Yuri Milner (technology venture
capitalist) have launched the annual prize that
will see 11 scientists who are leading global initiatives to cure or prevent diseases, receive a $3
million payout.
They are hoping that with the recognition and
financial reward these awards will bring to the
winners, that more people will be willing to take
on what has traditionally been seen as an underfunded and unappreciated endeavour. The
injection of an additional $33 million to help
with this work annually will also see successful
initiatives push forward with their thinking and
experimenting. This will mean that where before
a project may see success but be hindered by budget constraints, now it will be able to push on and
make a real difference at a rapid pace.
All three founders of these awards are innovators and forward thinkers. Brin has built one of
the world's most innovative companies from the
ground up, adopting new ideas and branching
out what would have been a traditional search
engine. Zuckerberg forever changed the way the
world uses social media and interacts one another with a simple yet effective way of sharing information with one another. Although less well
known, Milner arguably has as much foresight as
the other two, as you cannot become a successful
venture capitalist without seeing the potential in
products and investing in them at the right time.
However, at first glance this kind of humanitarian work, although a fantastic idea, is not within
their traditional remit.
The second piece of news on the 19th that works
with this announcement in pushing big data
to the forefront of medical thinking is the announcement from Bina that they have launched
the first commercially viable big data product to
be used in genomics.
This may seem like it has been done before, but
in reality the cost effectiveness of this will push
forward the analysis of diseases and cures at a
vastly increased rate. With the cloud element of
“February 19 will mark the day
in history where big data in
healthcare and disease
prevention hit the
mainstream.”
FEBRUARY 19, THE
DAY THAT BIG DATA
IN HEALTHCARE WENT
MAINSTREAM
11the technology, it allows institutions to quickly,
easily and most importantly cheaply, test theories and experiment with potential new genetic
codes to eradicate certain diseases.
Before, the issue that was holding back real progress was that the only people who were really
pushing on these subjects were institutes and
universities. This meant that many of the projects were not adequately funded and given that
one traditional genome test would cost around
$1000, the number of these that could be undertaken were severely diminished. With this new
technology, the numbers that can be done are
vastly increased whilst the cost will be significantly cut.
The mixture of cheaper analysis through this
new technology and the increased investment
and recognition through the new awards will
have a significant impact on the speed of analysis. This will also offer increased hope of curing
diseases like cancer within the coming years.
Although it is not known if these two events were
orchestrated to occur on the same day, one thing
that is certain is that February 19 will go down in
history as the day that big data and disease prevention started to save lives. Whether intentional or not, the implications that this will have on
the future of healthcare will once again see these
three Silicon Valley stars innovating another major aspect of our lives.

SAP in the Cloud

Cloud computing offers SAP customers the opportunity to achieve significant decreases in total cost of ownership (TCO), while simultaneously improving the agility, performance and resiliency of their SAP deployment. Yet because SAP enables a variety of mission-critical business processes—including finance, human capital management, asset management, sales and procurement—it is important to choose a cloud service provider with extensive SAP experience.

Criteria for SAP Success in the Cloud

Due to the complex and mission-critical nature of SAP installations, enterprises looking to migrate SAP to the cloud should seek a provider able to deliver:
  • Extensive SAP Experience: SAP is complex software with stringent infrastructure requirements, numerous modules and many configuration options. To ensure a smooth transition to the cloud, it is essential to work with a provider that is intimately familiar with the SAP landscape.
  • SAP Successes: The best indicator of a provider’s SAP knowledge and experience is their ability to help similarly situated enterprises migrate their SAP instances to the cloud.
  • Assured Performance: In order to ensure a smooth SAP experience, the cloud platform must guarantee access to the compute, storage and network resources required by SAP. The cloud provider should be willing to stand behind their service by ensuring a smooth experience from the SAP user’s perspective.

Clearing the Big Data Hurdle: The Open Source Advantage

By Christopher M. Carter, Hiln
www.Hiln.com
In today’s world there is a new understanding, the emergence of a new “reality” that is much, much different than what we had even a decade ago.  This new reality of big data that exists within today’s enterprises cannot be underestimated.  Big data is becoming more important in all industries, but none more so than in the finance arena, both in enterprises and big finance in Wall Street firms.  Most businesses aren't ready to manage this flood of data, much less do anything interesting with it.
Big data will impact every industry, from finance to education and government.  In fact, the Federal government just announced a new big data research initiative, with a budget of $200 million.
Data as a whole is a catalyst for business.  According to IDC, there will be 2.7 zeta bytes of data created this year alone.  Now, if you look into the enterprise, you begin to see that in order to begin analysing and deriving value from these increasingly large data sets, organizations need to embrace the right tools that will allow for these new capabilities.  As businesses begin to better understand their existing data, they can gain competitive advantage in the process, however, that competitive advantage can only be realized if data can be processed intelligently, efficiently and results delivered in a timely manner.
How does the enterprise begin to mine its data?  Good question.  With so much data existing that firms can become overwhelmed, how can the good data be identified?   What is “needed” data and what information is not as valuable?   The old mantra of “good data in, good data out; bad data in, bad data out” can help to start answering these questions.   All firms need to be cognizant, first and foremost, of the quality of the data being entered into their systems and used in daily operations. This is especially important in industries like finance, where data is the lifeblood of the business.
Opportunities abound in big data, and an organisation can get as much potential knowledge out of this stored data as they put energy into analysing it.  With applications spanning from Business Objects from SAP and the usage of in-memory data from Hana to newer applications, members of the finance sector are looking to add new positions like a Chief Data Officer specifically to make the key decisions around information that need to be made today.   Big data is indeed big, but it's not for all purposes.  For example, it’s not for transactional or real-time in-memory processing of small and endless streams of structured data.  Think of data like a big truck vs. a small sedan - each has its purpose.  However, both Big data and fast in-memory traditional databases have a place in driving business.
Opportunities in harnessing and utilising big data become more feasible when open source frameworks come into play.  The open source world has basically created the new age of big data analytics, be it when utilising Hadoop, the most widely used and well-known solution for developers, to products like Greenplum from EMC and others.  These tools have created a rush to market to support organisations trying to compute as much data as fast as they can with a solution that will allow them to make decisions in as real time as they can.  For example, a major retailer with outlets around the globe, utilising an open source framework, has the ability to harness the data coming in from their social media sites, run it through their enterprise data analytics solution, utilising literally thousands of nodes, to make real time decisions in their stores about products and pricing.
Three to five years ago this was not possible.  But, with the large and active open source community working on the framework this computation ability now exists and is being utilised and modified by new companies daily.
Corporations are looking at their data as an asset within their walls no matter where it physically resides, but yet there is still so much to learn and to dig through.  The new Chief Data Officer and their team must stay vigilant and be concerned about many factors that will directly impact the business, including how and what data is being provided to regulators.  Enterprises need to set standards when it comes to their information, and this is more important than ever in the increasingly regulatory-focused landscape.  Firms need to insure their internal processes are in place for current government regulatory requirements, as well as taking into account regulations in many of the new laws that are being created, seemingly on the fly.
There is no doubt that bringing the power of big data and harnessing its performance is important and that it will become more strategic when considering how organisations will use the data to interact with their clients, competitors and the market through faster decision-making.  Some companies will start to shrink under the pressure of this new data analysis, while some may indeed fail completely.  But regardless of which companies falter, and which ones gain market share, one thing is for certain: database companies should see tremendous gains as the need for more and more database applications increases.
Organisations are looking to the future and deciding how important a role big data will play in the coming years.  The truth is, how firms utilize big data as a source of knowledge and power will be the largest influence.  These enterprises that find success with adopting open source tools to analyse their information will see improved profitability, provide stronger service throughout the organisation and to their customers and rise above in the land of giants.

How Enterprises Can Bend the Programmer Learning Curve

How Enterprises Can Bend the Programmer Learning Curve

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Anyone who works in a corporate environment will tell you that trying to hire developers is probably just as stressful as raising venture capital, if not more so. Why? First, there is the challenge of finding the right kind of developers. Second, once you find the best people, even the most qualified developer can cost a fortune to train; so they seek out environments that can educate them faster and focus on their skill sets and interests.
Why is this an issue? Much more is needed for an enterprise to flourish than just sufficient capital. Enterprises need access to talent in order to execute their vision. Once the talent is found and hired, the new employees can rarely hit the ground running. Often it takes months to find and hire the right developers, and then even more time to “bend their learning curve” so they can successfully contribute to the business.
Imagine a world where enterprises and their developers are able to cultivate the depth of skills that were once reserved for employees with many years of experience and apply these talents instantly to new staff members and application projects. To help speed the ramp-up process, thanks to the advent of applications such as Puppet, Chef and Brooklyn, which allow instant manipulation and modification of enterprise applications, this imagined world is becoming a reality.
With the ability for new employees to quickly get up to speed working with existing enterprise applications, the learning curve on those enterprise-grade solutions has been twiddled away to days rather the years.
In order for enterprises to take advantage of the skill sets of new developers as soon as possible, they must utilize any tools at their disposal, like the applications mentioned above, to bend the learning curve to the enterprise’s advantage.
However, getting a developer up to speed on existing work is just one step in the growth process that enterprises need to embrace. Companies must consider how they can look at each individual developer’s learning curve and bend each one to benefit both the employee and the organization as a whole. Personalization is key in this stage of learning.
For examples of successful education programs, enterprises can look to startups. Unlike many companies that desire that developers bring their own cultivated knowledge to the job, startups tend to take the time to learn about their employees’ desires and educate those who want to be proficient in one or more open source languages (e.g., PHP, Python, Ruby) and can work across the stack and strive to learn more so they are relied upon and viewed as an asset to the business.
While there seems to be a decent pool of ASP.net, C# and Java developers already in place in organizations, enterprises need to learn that it is cheaper and more efficient to utilize open source technologies (in most cases), and to find employees who want to become proficient in these languages. Typically in the past, many skilled enterprise developers didn’t adopt open source languages simply because they didn’t know any better, and they became stuck in their ways or earned enough money not to care. Instead of taking the time to learn new languages, they focused on their existing strengths.
However, a new age is dawning and the enterprise can learn from the methods of the startup and discover that shortening the developer learning curve by enticing them with new-age applications that appeal to their interests is key to achieving enterprise business success.
If you are a competent developer, you generally have no need to worry about job security because you are in such high demand. If you think about it, this situation is actually quite scary because the developer holds all of the cards. This won’t change any time soon.
Since most companies will not, or cannot, take the time to provide education on new skills, if the position where you are currently employed becomes stagnant, you simply move onto the next one. But, if the enterprise is willing to look into employees’ passions and educate them to develop based on their interests, the learning curve is forever bent in the favor of the enterprise, the “growth” of the employee and their combined future.
It’s fair to say that education for developers is continuing to improve, but there is still a ways to go. Enterprises need to offer more open source languages alongside, if not in favor of, the existing languages taught in corporate training facilities, allow employees to gravitate towards their strengths and focus on applications and needs that tie into their passions.
As more companies allow developers to drive the evolution of their education, the faster these organizations will help create an internal revolution, where the benefits to developer morale and work quality will be seen almost immediately. Once the learning curve is bent to the developer’s strengths, enterprises will see the passion and drive that startups have seen for years and the results will speak for themselves.
Christopher M. Carter is vice president of business development at Hiln Solutions. He is responsible for driving Hiln’s business development and partner relationships. Chris is a serial entrepreneur who founded two successful startups and is credited with creating the world’s first SAP cloud solution. He brings over 20 years’ sales management experience in the technology sector, most recently in a senior business development role with CCI & Hiln.

Zynga Co-founder’s Junyo Is Using Big Data To Help EdTech Companies Better Understand What Schools Really Need | TechCrunch

In 2011, Steve Schoettler left Zynga, the company he had co-founded four years earlier, to devote himself to a new project, called Junyo. With interest in education technology beginning to take hold, Shoettler and his co-founders at Junyo set out to leverage the growing capabilities Big Data tools and analytics to tackle some of the deep-seated problems in the educational system. Chief among those was using data to help schools get a more complete picture of student performance and answer the question: What should we teach students next — and how?

SAP’s Purchasing Power Play

SAP just did a big acquisition, along with a little head fake.

While the announcement by SAP, the German enterprise software company, said this was a deal about online marketing, in fact, it’s part of a broader effort by many companies to reshape retail sales.
SAP announced Wednesday that it was buying Hybris, a Swiss e-commerce software company. The price was not disclosed, but someone familiar with the deal who was not authorized to speak on the record, said SAP paid “somewhat less than $1 billion” for hybris.

The deal follows Tuesday’s announcement by Salesforce.com that it was acquiring ExactTarget, an online marketing services company, for close to $2.5 billion.

Not surprisingly, many industry analysts wanted to make a connection between the two deals.
Bill McDermott, SAP’s co-chief executive. 
Stringer/Germany/Reuters Bill McDermott, SAP’s co-chief executive.
 
That link was reinforced when Bill McDermott, SAP’s co-chief executive, took a couple of shots at Salesforce during the conference call about the Hybris deal, saying Salesforce had bought an old-fashioned e-mail marketing company (yes, that’s old-fashioned now). Gartner, an industry research firm, recently announced that Salesforce had replaced SAP as the leading vendor of customer relationship management software, giving Mr. McDermott reason to want to get even.
The Salesforce deal, however, is part of a larger plan by Salesforce to blend advertising, marketing and sales. Marc Benioff, the chief executive of Salesforce, has said that technologies like cloud computing and social media increasingly break down the distinctions between those things.
This is particularly true for customer relationship management of sales from one company to another, where complicated specs and contracts mean e-mail matters more.

SAP is going after consumers as much as businesses with Hybris and hoping to use the data from online commerce for Big Data marketing, and eventually, things like planning inventory and manufacturing. That is a much bigger goal, and ties into both SAP’s roots in enterprise resource planning software and the online data analysis of its HANA platform.

“You can read this purchase as us being serious” about customer relationship management,” said James Dever, a spokesman for SAP. “But it’s deeper than that. This touches a company’s back end transactional data,” or information about things like inventory.

One feature of Hybris’s software is that it allows customers to open an online shopping cart on one computer and then adjust an order later on another computer before closing a sale. Using its HANA platform, SAP hopes to let sellers see behaviors, then offer deals or companion offers before a sale is completed.

Eventually, companies may be able to use that overall information and data analysis to figure out faster how much of a product they need to make, store or sell quickly. The product could also help in planning what to stock in retail stores.

In some ways, the SAP deal is closer to last year’s move by NetSuite, another SAP rival, to offer online commerce services. While that business has been slow to emerge, NetSuite recently announced some significant deals involving blended online and traditional brick and mortar sales.
“The big picture is that consumers want to connect with companies on a personal, individualized basis, online and offline,” Zach Nelson, the chief executive of NetSuite, said.

In an even bigger picture, deals like this are part of the broader move to create the immediacy and data-led insight (or, if you prefer, cookie-based spying) of online retail with the high-touch experience of physical stores.

Amazon.com moved early into online skills and has edged into the physical world by offering fast delivery of goods. Apple has gone farther, designing stores that in many ways embody its online sales presence, from the minimalist look to the absence of formal checkout kiosks.
If SAP can build out Hybris, it could blur further the barriers between ads, sales and marketing. And more companies could break down barriers between things online and off.