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Telecom major <keyword id="1553175" type="COMPANY" weightage="20" keywordseo="Vodafone-Idea">Vodafone Idea</keyword> Limited (VIL) on Tuesday announced that it has selected <keyword id="10875" type="CITY" weightage="20" keywordseo="IBM">IBM</keyword> Services to help it embrace open source at scale across the enterprise by implementing the <keyword id="10099317" type="UNKNOWN" weightage="20" keywordseo="big-data-platform">big data platform</keyword> on open source Hadoop framework. The <keyword id="10099318" type="UNKNOWN" weightage="20" keywordseo="ibm-big-data">IBM big data</keyword> platform helps businesses address the "full spectrum" of big data business challenges. BM Services implements data transformation with open technologies to propel Vodafone Idea's hybrid cloud strategy. Vodafone Idea has a need for large scale data transformation with a focus on architecture modernisation, open-source adoption and using predictive analytics for data modernisation. By partnering on this implementation, IBM is helping VIL transform the way data is optimised and delivered to partners, employees and internal systems. Fragmented, siloed data can now be streamlined for seamless data availability, the tech giant said. VIL will also be able to combine insights from the Big Data Platform and better leverage cloud native technologies and artificial intelligence (AI) to enhance revenues, reduce costs and elevate customer experiences, IBM said. "The modernised and future-ready data platform is helping VIL get daily actionable insights to make strategic and operational level decisions effectively," Sandip Patel, Managing Director, IBM India/South Asia, said in a statement. "IBM and VIL team worked together in challenging times of COVID-19 lockdown to seamlessly execute a complex and enterprise-wide deployment remotely," he said. Currently, insights derived from the data are leveraged for management dashboards, campaign management, network analytics, usage traffic analysis, product analysis, amongst others. Vodafone Idea said that the deployment will help millions of its customers with customised and faster service launches. "Along with IBM we have implemented many first-of-kind projects and the big data and analytics engagement is one such initiative," said Vishant Vora, Chief Technology Officer, Vodafone Idea Limited. "The open source approach has helped us in modernising infrastructure and network experience, helping our people and partners in quicker business decision making." IBM last week announced that it will separate its managed infrastructure services unit of its global technology services division into a new public company. The yet to be named new company is currently codenamed "NewCo". SEE ALSO: <a href="https://www.businessinsider.in/tech/news/oneplus-chinese-company-co-founder-carl-pei-exits-company-one-day-ahead-of-flagship-mobile-launch/articleshow/78634270.cms">OnePlus co-founder Carl Pei reportedly exits company one day ahead of flagship smartphone launch</a> <a href="https://www.businessinsider.in/stock-market/news/banking-stocks-like-sbi-hdfc-axis-icici-and-other-share-price-in-the-stock-market-ahead-of-the-moratorium-verdict/articleshow/78633357.cms">SBI, HDFC Bank, Axis Bank and other bank stocks tread caution as they wait with bated breath for Supreme Court verdict on moratorium</a> <a href="https://www.businessinsider.in/defense/news/india-china-disengagement-looks-unlikely-with-more-chinese-troops-reportedly-being-deployed-at-the-border/articleshow/78632960.cms">Chinese PLA is reportedly rotating troops despite India's insistence on disengagement from friction points along the border</a> <a href="https://www.businessinsider.in/science/space/news/mars-will-appear-bigger-redder-and-brighter-on-october-13-and-wont-get-this-close-to-earth-again-until-2035/articleshow/78556539.cms">Mars will appear bigger, redder, and brighter on October 13 — and won’t get this close to Earth again until 2035</a>

Vodafone Idea inks pact with IBM to implement a big data platform

<div style="padding: 15px; border: 1px solid #999999; margin-bottom: 10px; font-size: 15px!important; line-height: 25px; overflow: auto; vertical-align: middle;">This post is part of the <a href="http://www.businessinsider.com/category/future-of-business">"Future of Business"</a> series, which examines how cutting-edge technologies are rapidly reshaping our world, from how businesses run to how we live. "The <keyword id="1737939" type="UNKNOWN" weightage="60" keywordseo="Future-Of-Business">Future of Business</keyword>" is sponsored by SAP. <a href="http://www.businessinsider.com/category/future-of-business">More in the series »</a></div><div class="KonaFilter image-container float_right"><div class="image"><a href="http://www.flickr.com/photos/mr_fujisawa/8169394062/in/photolist-drUheL-n2MoZ-47NKRE-47JH8M-47NKUf-6mHpDg-6mHpCF-5nwzVG-4KAwJ5-8KQhmA-7nhXAQ-4nTcN5-4KwAEP-4KwAzZ-4KwAyg-61TNjW-6YJFq6-5hJ2yU-8fGPfX-8fGPkc-8fL4sb-8fGPj8-8fGPne-8fL4rs-8fL4uY-9oFLjb-91cuUP-7T34No-KxhMm-2mwq2H-2juArn-2mwq2p-KxoFH-7UCtxT-2jyZfq-2jyZuq-aa67D9-iK4GY-iK4Hb-iK4J1-iK4Gy-iK4JJ-iK4Js-iK4JV-86aG2Y-hmEV1-dtqERh-VzjXR-6ZFRF7-7E9ryq-7Jehwj/">Flickr/Paul J Coles</a></div></div>By now, chances are you've heard the term "<keyword id="774829" type="ORGANIZATION" weightage="60" keywordseo="Big-Data">big data</keyword>."
It refers to the gobs of information being collected about us and our world through things like Twitter, Facebook, Google, smartphones, GPS locations, and tiny sensors built into everything.
But the question for most people is...so what? Why are techies and scientists so excited about this thing? After all, it's not like data didn't exist before, even in large quantities.
The short answer: big data is a new tech that can help us understand, and then predict, things like never before. Things like what we'll buy and when, when the prices of airline tickets and electronics are cheapest, which New York manholes are most likely to explode, or which tenement buildings most likely to catch fire.
Who wouldn't want to know stuff like that?
Big data can do this because it uses all information on a topic, instead of a smaller more manageable subset. Then it finds correlations, or things that tend to happen at the same time.
Correlations allow us to discover patterns and patterns allow us to predict the future, explains the authors of the book <a href="http://www.amazon.com/Big-Data-Revolution-Transform-Think/dp/0544002695">"Big Data: A Revolution that Will Transform How We Live, Work and Think,</a>" written by Oxford professor Viktor Mayer-Schonberger and big data journalist for the Economist, Kenneth Cukier.
The more data you have, the more correlations you can find and the more accurate the pattern and the prediction become.
Correlations are different from the classic method of making predictions: trying to find out "why" or "what caused something." That's known as "causation."
A correlation does not mean that one thing caused the other. For instance, earlier this year, <a href="http://www.businessinsider.com/mastercard-big-data-for-shopping-habits-2013-2">MasterCard created its own big data division</a>. After analyzing billions of records, it learned that when someone buys gas at around 4 p.m., the person will likely then spend $35-$50 on groceries or at a restaurant. The gas purchase didn't cause the food purchase.
"Predictions based on correlation lie at the heart of big data," the authors write.
Google is the biggest examples of a "big data" company that knows how to use correlations. It keeps records of everything we do with its online services and finds new ways to use that data. For instance, Google <a href="http://www.businessinsider.com/the-cdc-is-using-big-data-to-combat-flu-2012-12">created a realtime flu tracker</a> by watching where people searched for terms relating to illness and mapping that data from the Center for Disease Control.
A lot more of this is on its way. Here are some examples from the book of Google-like companies doing interesting things with big data.
<ul>
<li>Oren Etzioni, creator of one of the first search engines, MetaCrawler, scraped data from a travel website to build a tool called Farecast that predicted when an airfare price was likely to go down. Microsoft bought Farecast for $115 million in 2008. Today, it's <a href="http://www.bing.com/travel/">part of Bing</a>.</li>
<li>Then Etzioni turned around and created <a href="https://www.decide.com/">Decide.com</a> to help people predict when prices will drop on electronics.</li>
<li><a href="http://www.pricestats.com/">PriceStats</a> tracks the prices of millions of products in over 70 countries to keep tabs on inflation and the economy.</li>
<li><a href="http://www.airsage.com/">AirSage</a> gathers 15 billion geolocation records daily from multiple cell phone carriers. It uses this for traffic analysis to help city planners.</li>
<li>Similarly, <a href="http://www.inrix.com/">Inrix</a> collects traffic data from the sensors in the cars themselves via BMW, Ford, Toyota, and others and uses that to help city planners model traffic flow.</li>
<li><a href="http://www.kaggle.com/">Kaggle</a> crowdsources the process of writing a big data algorithm by running contests.</li>
<li><a href="http://www.the-numbers.com/market/">TheNumbers.com</a> collects detailed records on Hollywood films, from box office sales to who worked together on which films. Producers use it to predict how much money a film is likely to make.</li>
</ul>

Big Data Is About To Produce A Whole Bunch Of Google-like Companies - Here's How

<div style="padding: 15px; border: 1px solid #999999; margin-bottom: 10px; font-size: 15px!important; line-height: 25px; overflow: auto; vertical-align: middle;">This post is part of the <a href="http://www.businessinsider.com/category/future-of-business">"Future of Business"</a> series, which examines how cutting-edge technologies are rapidly reshaping our world, from how businesses run to how we live. "The <keyword id="1737939" type="UNKNOWN" weightage="60" keywordseo="Future-Of-Business">Future of Business</keyword>" is sponsored by SAP. <a href="http://www.businessinsider.com/category/future-of-business">More in the series »</a></div><div class="KonaFilter image-container float_right"><div class="image"><a href="http://zh.m.wikipedia.org/wiki/File:Kenneth_Cukier,_Data_Editor,_The_Economist_%288590351576%29.jpg">Wikipedia</a>Kenneth Cukier, Data Editor, The Economist.</div></div><keyword id="774829" type="ORGANIZATION" weightage="60" keywordseo="Big-Data">Big data</keyword> is a new technology that will ultimately allow us to predict the future. It can tell us things like what we'll buy and when, when the price of a new gadget will drop, and which people are most likely to commit a crime.
So say the authors of a new book <a href="http://www.amazon.com/Big-Data-Revolution-Transform-Think/dp/0544002695">"Big Data: A Revolution that Will Transform How We Live, Work and Think,</a>" written by Oxford professor Viktor Mayer-Schonberger and big data journalist for the Economist Kenneth Cukier.
We caught up with the authors and asked a few questions:
Business Insider: Your book makes big data technology sound like something out of the movie "Minority Report." Can it really identify criminals before they've committed a crime?
Kenneth Cukier: Yes. Many cities in America (like New York, LA, Richmond, VA) and other countries use software that looks at past crime data and other things like weather, big concerts or sporting events, and more to predict where crimes activity will be high, to send patrols to those areas.
The results are in some cases impressive: sharp reductions in crime compared to nearby areas that don't use the software. But this isn't conclusive that it works: there may be other factors involved. For instance, the sort of police force willing to use big data might also be the sort of organization that would work hard to make any change in their processes yield good results.
What's critical, however, is that this is the direction of the future - and the idea is not to just identify where a crime may be committed, but who might be the criminal, down to the specific individual.
BI: How will small businesses be impacted by big data tech?
KC: First and most importantly, they can do big data now, which they couldn't in the past since it was too expensive and difficult.
Second, they can benefit by tailoring their processes around big data. For example, there are lots of things that big companies know and which give them a competitive edge that little firm's don't know because they don't have the scale or money to collect a lot of data and find out. For instance, what backgrounds make the best employees or what sort of content works best on a website, and where to place it?
BI: Privacy concerns are the big downside of big data. What's your vision for how we can balance the benefits of big data without giving up reasonable privacy?
<div class="KonaFilter image-container display-table float_right"><div><div class="image"><a href="http://www.oii.ox.ac.uk/people/?id=174">Oxford</a>Viktor Mayer-Schönberger, Professor of Internet Governance and Regulation, Oxford</div></div></div>Viktor Mayer-Schönberger: What we need are new ways to protect privacy and to balance privacy with the benefits of big data. For instance, rather than relying on notice and consent at the time of collection for privacy protection, in the big data age we could require data users [companies like Google and Facebook] to be accountable and responsible for how they employ personal data.
We could require them to assess potential risks and harms to individuals before they commence their big data analysis, and to put effective safeguards in place to limit that harm.

How Big Data Could Stop Criminals Before They Strike

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<td style="color: #000000; text-decoration: none; font-size: 16px; line-height: 20px; font-family: Georgia, Times New Roman, serif;" width="700">This post is part of the <a href="http://www.businessinsider.com/category/future-of-business">"Future of Business"</a> series, which examines how cutting-edge technologies are rapidly reshaping our world, from how businesses run to how we live. "The Future of Business" is sponsored by SAP. <a href="http://www.businessinsider.com/category/future-of-business">See more posts in the series »</a></td>
</tr>
</tbody>
</table><div class="image-container float_right" style="width:480px"><div class="image"><a href="http://www.flickr.com/photos/mr_fujisawa/8169394062/in/photolist-drUheL-n2MoZ-47NKRE-47JH8M-47NKUf-6mHpDg-6mHpCF-5nwzVG-4KAwJ5-8KQhmA-7nhXAQ-4nTcN5-4KwAEP-4KwAzZ-4KwAyg-61TNjW-6YJFq6-5hJ2yU-8fGPfX-8fGPkc-8fL4sb-8fGPj8-8fGPne-8fL4rs-8fL4uY-9oFLjb-91cuUP-7T34No-KxhMm-2mwq2H-2juArn-2mwq2p-KxoFH-7UCtxT-2jyZfq-2jyZuq-aa67D9-iK4GY-iK4Hb-iK4J1-iK4Gy-iK4JJ-iK4Js-iK4JV-86aG2Y-hmEV1-dtqERh-VzjXR-6ZFRF7-7E9ryq-7Jehwj/">Flickr/Paul J Coles</a></div></div>By now, chances are you've heard the term "<keyword id="774829" type="ORGANIZATION" weightage="60" keywordseo="Big-Data">big data</keyword>."
It refers to the gobs of information being collected about us and our world through things like Twitter, Facebook, Google, smartphones, GPS locations, and tiny sensors built into everything.
But the question for most people is...so what? Why are techies and scientists so excited about this thing? After all, it's not like data didn't exist before, even in large quantities.
The short answer: big data is a new tech that can help us understand, and then predict, things like never before. Things like what we'll buy and when, when the prices of airline tickets and electronics are cheapest, which New York manholes are most likely to explode, or which tenement buildings most likely to catch fire.
Who wouldn't want to know stuff like that?
Big data can do this because it uses all information on a topic, instead of a smaller more manageable subset. Then it finds correlations, or things that tend to happen at the same time.
Correlations allow us to discover patterns and patterns allow us to predict the future, explains the authors of the book <a href="http://www.amazon.com/Big-Data-Revolution-Transform-Think/dp/0544002695">"Big Data: A Revolution that Will Transform How We Live, Work and Think,</a>" written by Oxford professor Viktor Mayer-Schonberger and big data journalist for the Economist, Kenneth Cukier.
The more data you have, the more correlations you can find and the more accurate the pattern and the prediction become.
Correlations are different from the classic method of making predictions: trying to find out "why" or "what caused something." That's known as "causation."
A correlation does not mean that one thing caused the other. For instance, earlier this year, <a href="http://www.businessinsider.com/mastercard-big-data-for-shopping-habits-2013-2">MasterCard created its own big data division</a>. After analyzing billions of records, it learned that when someone buys gas at around 4 p.m., the person will likely then spend $35-$50 on groceries or at a restaurant. The gas purchase didn't cause the food purchase.
"Predictions based on correlation lie at the heart of big data," the authors write.
Google is the biggest examples of a "big data" company that knows how to use correlations. It keeps records of everything we do with its online services and finds new ways to use that data. For instance, Google <a href="http://www.businessinsider.com/the-cdc-is-using-big-data-to-combat-flu-2012-12">created a realtime flu tracker</a> by watching where people searched for terms relating to illness and mapping that data from the Center for Disease Control.
A lot more of this is on its way. Here are some examples from the book of Google-like companies doing interesting things with big data.
<ul>
<li>Oren Etzioni, creator of one of the first search engines, MetaCrawler, scraped data from a travel website to build a tool called Farecast that predicted when an airfare price was likely to go down. Microsoft bought Farecast for $115 million in 2008. Today, it's <a href="http://www.bing.com/travel/">part of Bing</a>.</li>
<li>Then Etzioni turned around and created <a href="https://www.decide.com/">Decide.com</a> to help people predict when prices will drop on electronics.</li>
<li><a href="http://www.pricestats.com/">PriceStats</a> tracks the prices of millions of products in over 70 countries to keep tabs on inflation and the economy.</li>
<li><a href="http://www.airsage.com/">AirSage</a> gathers 15 billion geolocation records daily from multiple cell phone carriers. It uses this for traffic analysis to help city planners.</li>
<li>Similarly, <a href="http://www.inrix.com/">Inrix</a> collects traffic data from the sensors in the cars themselves via BMW, Ford, Toyota, and others and uses that to help city planners model traffic flow.</li>
<li><a href="http://www.kaggle.com/">Kaggle</a> crowdsources the process of writing a big data algorithm by running contests.</li>
<li><a href="http://www.the-numbers.com/market/">TheNumbers.com</a> collects detailed records on Hollywood films, from box office sales to who worked together on which films. Producers use it to predict how much money a film is likely to make.</li>
</ul>

In today’s digital world when a user makes an online purchase be it goods or service or does any activity on the social media, the data is captured. So, just imagine the gigantic volumes of data that is being generated each hour across the globe by the billions of digital users. The dawn of <keyword id="73524" type="UNKNOWN" weightage="20" keywordseo="Digitization">digitization</keyword>, social media adoption and <keyword id="970768" type="UNKNOWN" weightage="20" keywordseo="internet-of-things">Internet of Things</keyword> (IOT) has led to Data Explosion. 
 
According to an IDC report, the 2.8 ZB (zettabytes) of data created in 2012 is expected to grow up to 40 ZB by 2020. Most of the recent data is on account of user generated content such as blogs, wikis, discussion forums, images, videos etc. This analysis indicates that enterprises are processing and analyzing an increasing amount of data. 
 
It is impossible to consume Big Data directly. To consume this data, you need sophisticated and robust algorithms supported via advanced analytics. The essence of making informed decision on big data is through analytics. Looking at the current trend, you can safely assume that in future, analytics will be embedded in everything i.e. devices, appliances, software, apps etc. You can use these data to help consumers get Personalized Experience. 
 
 
As business users are quite comfortable accessing mainstream BI software and data visualization tools, for example, Excel being most commonly used software, which plays a vital role in the analysis process, it will be easier for them to understand the advanced analytic concepts. 
 
The following three phases explain the entire cycle of transforming big data to an actionable decision making insights: 
 
Descriptive Analysis: This is the most often used at the Enterprise Reporting level (sales, marketing, finance) for post-mortem analysis. It mines the historical data and helps you summarize consumable bites of information. For example, in social media analytics, there are many variables such as number of posts, mentions, fans, followers, page view and so on. It is redundant to list them all, but you can view them as event counter, thus reducing your big data into much smaller data units. 
 
Predictive Analytics: The purpose of predictive analytics is to analyze the available data and predict what might happen in the future. It uses a variety of statistical, modeling, data mining, and machine learning techniques to build a Predictive Model that studies historical data, and thereby making predictions about the data we do not currently have. 
 
 
The real advantage of having this model is to extrapolate the model to regimes where data does not exist and make predictions. Predictive analytics answers the question what will happen, tries to determine the probabilistic future outcome of an event or the likelihood of a situation occurring. Examples of predictive analytics include trend lines, influence scoring, sentiment analysis, etc. 
 
Prescriptive Analytics: The purpose of prescriptive analytics is to prescribe an actionable insight to the decision-maker. The prescriptive analytics model must have a feedback mechanism so that it can continually take in new data based on business user’s actions, and use this data to re-predict and re-prescribe. Hence improving prediction accuracy and prescribing better decision option. 
 
 
Prescriptive Model cannot only predict the possible consequences based on different choice of action, it can also recommend the best course of action for any pre-specified outcome. Thus, the goal of most prescriptive analytics is to guide the decision maker, so that the decisions will ultimately lead to the target outcome. 
 
Big Data is here to stay and grow exponentially. Also, with the improvements in the predictive and prescriptive analytical models, the outcome of data driven decision making will be a dominant factor to achieve and surpass expected business results. 
 
(The author of this article is Vishal Mour, Principal Software Engineer, SAP Labs India) 
 
(Image: Thinkstock)

This is how you can turn ideas into decisions using Big Data

<div style="padding: 15px; border: 1px solid #999999; margin-bottom: 10px; font-size: 15px!important; line-height: 25px; overflow: auto; vertical-align: middle;">This post is part of the <a href="http://www.businessinsider.com/category/future-of-business">"Future of Business"</a> series, which examines how cutting-edge technologies are rapidly reshaping our world, from how businesses run to how we live. "The <keyword id="1737939" type="UNKNOWN" weightage="60" keywordseo="Future-Of-Business">Future of Business</keyword>" is sponsored by SAP. <a href="http://www.businessinsider.com/category/future-of-business">More in the series »</a></div><div class="KonaFilter image-container float_right"><div class="image">KrossoverKrossover cofounder James Piette</div></div>The story of <keyword id="774829" type="ORGANIZATION" weightage="60" keywordseo="Big-Data">big data</keyword> startup Krossover is the stuff of Disney movies.
In 2010, a 20-year veteran high school basketball coach, Sean McInnis, took a job at King Philip Regional High School in Massachusetts. The varsity team hadn't won a single game in more than three seasons - some 60 painful losses in a row. McInnis went to a trade show and saw a demo of a new technology from Krossover that turns raw video footage of a game or practice session into searchable insights and analysis. He became the company's first customer, Krossover cofounder and statistics guru James Piette told Business Insider.
That year, the team went 14-8 and almost made it to the state championships. Today, Krossover counts thousands of coaches as customers and covers three sports: basketball, football, and Lacrosse. It works by giving high school and college teams professional-grade video analysis for a low cost. Coaches upload videos to the Krossover cloud service. One of 1,300 crowdsourced employees in the U.S., India, or Europe watches the film and documents everything.
By the next day, the searchable video and analysis is available to the coach. A coach can quickly create a play list of say, every missed shot by a particular player. Or every missed free throw. And so on. "We are sitting on mounds of data, about 20 terabytes of video, data, and analytics," Piette says. "Our service is cataloging exactly what's happening in every single play like who took a shot where, who rebounded the shot, who inbounded the ball, everything." Although Krossover doesn't tell the coach what went wrong or how to fix it, it offers a huge array of stats a coach needs to discover that stuff.
Here's an example:
<div class="KonaFilter image-container"><div class="image">Krossover</div></div>It turns out team sports is often less about the talent than it is about statistics. For instance, in basketball the Holy Grail percentage is turnover rate.
"The number one thing that determines if you win as a high school basketball team is turnovers," Piette says. "If you can keep your turnovers down, even if you're not a good shooting team, you'll have an above average basketball team." Teams that use Krossover reduce their turnovers by about 20%, says Piette.
Krossover says coaches who use the service win an average of 10% more games than they were before. Nine out of 10 teams that are in really bad shape show improvement.
The company charges between $800 and $3,000 per season and pays its crowdsourced workforce $20 to $30 per video.

This Guy's Startup Helps Down-And-Out High School Teams Win Games

<div style="padding: 15px; border: 1px solid #999999; margin-bottom: 10px; font-size: 15px!important; line-height: 25px; overflow: auto; vertical-align: middle;">This post is part of the <a href="http://www.businessinsider.com/category/future-of-business">"Future of Business"</a> series, which examines how cutting-edge technologies are rapidly reshaping our world, from how businesses run to how we live. "The <keyword id="1737939" type="UNKNOWN" weightage="60" keywordseo="Future-Of-Business">Future of Business</keyword>" is sponsored by SAP. <a href="http://www.businessinsider.com/category/future-of-business">More in the series »</a></div><div class="image-container float_right"><div class="image">KrossoverKrossover cofounder James Piette</div></div>The story of <keyword id="774829" type="ORGANIZATION" weightage="60" keywordseo="Big-Data">big data</keyword> startup Krossover is the stuff of Disney movies.
In 2010, a 20-year veteran high school basketball coach, Sean McInnis, took a job at King Philip Regional High School in Massachusetts. The varsity team hadn't won a single game in more than three seasons — some 60 painful losses in a row. McInnis went to a trade show and saw a demo of a new technology from Krossover that turns raw video footage of a game or practice session into searchable insights and analysis. He became the company's first customer, Krossover cofounder and statistics guru James Piette told Business Insider.
That year, the team went 14-8 and almost made it to the state championships. Today, Krossover counts thousands of coaches as customers and covers three sports: basketball, football, and Lacrosse. It works by giving high school and college teams professional-grade video analysis for a low cost. Coaches upload videos to the Krossover cloud service. One of 1,300 crowdsourced employees in the U.S., India, or Europe watches the film and documents everything.
By the next day, the searchable video and analysis is available to the coach. A coach can quickly create a play list of say, every missed shot by a particular player. Or every missed free throw. And so on. "We are sitting on mounds of data, about 20 terabytes of video, data, and analytics," Piette says. "Our service is cataloging exactly what's happening in every single play like who took a shot where, who rebounded the shot, who inbounded the ball, everything." Although Krossover doesn't tell the coach what went wrong or how to fix it, it offers a huge array of stats a coach needs to discover that stuff.
Here's an example:
<div class="image-container"><div class="image">Krossover</div></div>It turns out team sports is often less about the talent than it is about statistics. For instance, in basketball the Holy Grail percentage is turnover rate.
"The number one thing that determines if you win as a high school basketball team is turnovers," Piette says. "If you can keep your turnovers down, even if you're not a good shooting team, you'll have an above average basketball team." Teams that use Krossover reduce their turnovers by about 20%, says Piette.
Krossover says coaches who use the service win an average of 10% more games than they were before. Nine out of 10 teams that are in really bad shape show improvement.
The company charges between $800 and $3,000 per season and pays its crowdsourced workforce $20 to $30 per video.

<div class="KonaFilter image-container float_right"><div class="image">ShutterstockSAP HANA reveals a new way to look at San Francisco.</div></div>This post is sponsored by <a href="http://www.sap.com/index.epx#" target="_blank">SAP</a>.
As cities go, San Francisco is a safe place to live: Homicides are about half of what they were a few years ago and property crimes are declining. The tourism trade is also up, and tech startups are resurging.
But students at KIPP King High School in San Lorenzo, California, have discovered that the picture is less positive when looked at through the lens of <keyword id="774829" type="ORGANIZATION" weightage="60" keywordseo="Big-Data">big data</keyword>.
Working with <a href="http://www.saphana.com/community/learn/solutions/csr/humanity" target="_blank">HANA for Humanity</a>, a groundbreaking program that enables nonprofits to solve problems using publicly available data in the SAP HANA in-memory database platform, the students were able to analyze around <a href="https://data.sfgov.org/" target="_blank">1.5 million crime records from 2003-2012</a>.
They then overlaid additional data sets - locations of liquor stores, whether there was any graffiti in the neighborhood, the presence of police precincts, etc. - from nonprofits and other governmental agencies. Several hundred million data points were crunched, revealing some surprising facts:
<ul>
<li>One block of Bryant Street has had more than 30,000 documented instances of crime in the last 10 years, translating into one incident every three hours.</li>
<li>There are 10 liquor stores where a vast majority of crime occurs - within a mere 0.2 mile radius.</li>
<li>Crime against property continues to be an ongoing problem; and though violent crime appears to be under control, larceny/theft and vehicular theft account for 27% of the City's reported crime incidents.</li>
<li>Whenever the 49ers or the Giants have a home game, there's a 20% spike in crime. Weekend games result in much larger crime spikes than when games are held on Mondays. Additionally, crime levels vary, depending upon the opposing team and if there is a win for the home team (wins typically generated more crime than a loss or a tie).</li>
</ul>
Big Data technologies like SAP HANA can have a meaningful impact on society. Knowing which neighborhoods to police at what time of day, determining the optimal route for the police patrol car, ensuring that broken street lamps are promptly fixed and graffiti cleaned up before it begins to fester ... these are small actions that City Hall can take to ensure that San Francisco remains not just an iconic landmark but also a safe place to live for its 800,000 residents. The <a href="http://blogs.sap.com/innovation/big-data/students-use-big-data-to-analyze-crime-in-san-francisco-036558" target="_blank">original version of this article</a> was written by Manju Bansal and published on SAP. Find out <a href="http://www.businessinsider.com/sponsor-posts">more about Sponsor Posts.</a>

How Students Used Big Data To Analyze Crime In San Francisco

<div style="padding: 15px; border: 1px solid #999999; margin-bottom: 10px; font-size: 15px!important; line-height: 25px; overflow: auto; vertical-align: middle;">This post is part of the <a href="http://www.businessinsider.com/category/future-of-business">"Future of Business"</a> series, which examines how cutting-edge technologies are rapidly reshaping our world, from how businesses run to how we live. "The <keyword id="1737939" type="UNKNOWN" weightage="60" keywordseo="Future-Of-Business">Future of Business</keyword>" is sponsored by SAP. <a href="http://www.businessinsider.com/category/future-of-business">More in the series »</a></div><div class="KonaFilter image-container float_right"><div class="image">Shutterstock</div></div>
A winery might seem like an odd place to find <keyword id="6373689" type="ORGANIZATION" weightage="60" keywordseo="Cloud-computing">cloud computing</keyword> and <keyword id="774829" type="ORGANIZATION" weightage="60" keywordseo="Big-Data">big data</keyword> tech. But in more than 50 vineyards in California's Napa Valley, sensors are continually gathering data about the health of the vines and relaying it to the cloud for analysis, giving wine makers insight that can lead to higher quality wine.
Fruition Sciences, an Oakland, Calif.-based startup <a href="http://www.wired.com/wiredscience/2012/10/mf-fruition-sciences-winemakers/all/">(sometimes called the "vine nerds")</a>, is one of the first companies to bring this tech to the wine industry.
Its solar-powered sensors, which attach directly to the vines, measure how much water is moving through the plant - known as its transpiration rate - and send this data wirelessly to Fruition's cloud-based server.
From there, customers log into Fruition's web app and get a real-time view of how their vines are doing, including how much water the vine is losing every hour and how weather conditions are affecting it.
"We are constantly assessing information on what's happening with the vine, and to help the plant to respond to the environment," Thibaut Scholasch, co-founder of Fruition Sciences, told us.
Fruition Sciences' sensors work by applying heat to a section of the vine stem and measuring the temperature before and after to determine how much water is moving through the plant.
"We can precisely measure the heat dissipation along the vine stem while the water is being displaced," Scholasch said. "The level of resolution we get with this data is fantastic."
Being able to see what's happening inside the vine replaces the guesswork that often goes into the decision of whether or not to irrigate. It's often hard to figure how if a vine needs water just from looking at it.
This is especially important in California, where most wineries irrigate their crops.
While water needs vary depending on the type of grape, irrigating too much can damage the quality of the wine. The key is to irrigate the vine just enough so the plant is slightly stressed and produces smaller grapes, which is why real-time insight is valuable here.
In addition to making better wine, Fruition's tech can help vineyards get a better yield out of their plants, which translates into better return on investment, Scholasch said.
In the wine industry, there's no shortage of widgets that are supposed to help make better wine. But Fruition's tech is different, because it's churning out hard data. Fruition's app also lets winemakers create detailed logs of the vineyard management tasks.
Daniel Baron, winemaker at Silver Oak Cellars in Oakville, Calif., who's been working with Fruition Sciences for two years, says Fruition's tech is helping him to significantly cut his water usage.
"My vineyard team is thinking now about when they irrigate and how they irrigate, which translates into us using less water," Baron said. "We can push the limits of how long we can go without water."
Because there are a large number of variables that influence the quality of each vintage, Baron says it's too early to say whether Fruition's tech always translates into better-tasting wine. But the tech has other clear benefits.
"It's hard to quantify, but we learned a lot about how to form our vineyard to be optimal," Austin Peterson, winemaker at Ovid Napa Valley, a St. Helena, Calif.-based winery told us. "As a consequence of that, we've seen improvement in our wines. Our last couple of vintages got our best scores yet."
"We're getting better fruit character, and the tannin structure has changed in experimental blocks," Baron said. "We'll need a few more years to understand the changes, but I'm convinced enough to continue to do it, even if the only benefit is the water savings."

Here's What Happens When Wine And Geeks Mix

<table style="width: 800px;" border="0" cellspacing="0" cellpadding="0">
<tbody>
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<td width="90"></td>
<td width="10"> </td>
<td style="color: #000000; text-decoration: none; font-size: 16px; line-height: 20px; font-family: Georgia, Times New Roman, serif;" width="700">This post is part of the <a href="http://www.businessinsider.com/category/future-of-business">"Future of Business"</a> series, which examines how cutting-edge technologies are rapidly reshaping our world, from how businesses run to how we live. "The Future of Business" is sponsored by SAP. <a href="http://www.businessinsider.com/category/future-of-business">See more posts in the series »</a></td>
</tr>
</tbody>
</table><div class="image-container float_right" style="width:480px"><div class="image">Shutterstock</div></div>
A winery might seem like an odd place to find <keyword id="6373689" type="ORGANIZATION" weightage="60" keywordseo="Cloud-computing">cloud computing</keyword> and <keyword id="774829" type="ORGANIZATION" weightage="60" keywordseo="Big-Data">big data</keyword> tech. But in more than 50 vineyards in California's Napa Valley, sensors are continually gathering data about the health of the vines and relaying it to the cloud for analysis, giving wine makers insight that can lead to higher quality wine.
Fruition Sciences, an Oakland, Calif.-based startup, <a href="http://www.wired.com/wiredscience/2012/10/mf-fruition-sciences-winemakers/all/">(sometimes called the "vine nerds,")</a> is one of the first companies to bring this tech to the wine industry.
Its solar-powered sensors, which attach directly to the vines, measure how much water is moving through the plant — known as its transpiration rate — and send this data wirelessly to Fruition's cloud-based server.
From there, customers log into Fruition's web app and get a real time view of how their vines are doing including how much water the vine is losing every hour and how weather conditions are affecting it.
"We are constantly assessing information on what’s happening with the vine, and to help the plant to respond to the environment," Thibaut Scholasch, co-founder of Fruition Sciences, told us.
Fruition Sciences' sensors work by applying heat to a section of the vine stem and measuring the temperature before and after to determine how much water is moving through the plant.
"We can precisely measure the heat dissipation along the vine stem while the water is being displaced," Scholasch said. "The level of resolution we get with this data is fantastic."
Being able to see what's happening inside the vine replaces the guesswork that often goes into the decision of whether or not to irrigate. It's often hard to figure how if a vine needs water just from looking at it.
This is especially important in California, where most wineries irrigate their crops.
While water needs vary depending on the type of grape, irrigating too much can damage the quality of the wine. The key is to irrigate the vine just enough so the plant is slightly stressed and produces smaller grapes, which is why real time insight is valuable here.
In addition to making better wine, Fruition's tech can help vineyards get a better yield out of their plants, which translates into better return on investment, Scholasch said.
In the wine industry, there's no shortage of widgets that are supposed to help make better wine. But Fruition's tech is different, because it's churning out hard data. Fruition's app also lets winemakers create detailed logs of the vineyard management tasks.
Daniel Baron, winemaker at Silver Oak Cellars in Oakville, Calif., who's been working with Fruition Sciences for two years, says Fruition's tech is helping him to significantly cut his water usage.
"My vineyard team is thinking now about when they irrigate and how they irrigate, which translates into us using less water," Baron said. "We can push the limits of how long we can go without water."
Because there are a large number of variables that influence the quality of each vintage, Baron says it's too early to say whether Fruition's tech always translates into better-tasting wine. But the tech has other clear benefits.
"It's hard to quantify, but we learned a lot about how to form our vineyard to be optimal," Austin Peterson, winemaker at Ovid Napa Valley, a St. Helena, Calif.-based winery told us. "As a consequence of that, we've seen improvement in our wines. Our last couple of vintages got our best scores yet."
"We’re getting better fruit character, and the tannin structure has changed in experimental blocks," Baron said. "We’ll need a few more years to understand the changes, but I’m convinced enough to continue to do it, even if the only benefit is the water savings."

<div class="KonaFilter image-container float_right click-to-enlarge"><div class="image on-image"><a title_source="Datalogix" title_caption="Datalogix CEO Eric Roza" class="zoomin" href="http://static1.businessinsider.com/image/5245fcf269bedd115b8f0409-960/eric-roza.jpeg"></a>DatalogixDatalogix CEO Eric Roza</div></div>One of the least understood aspects of <keyword id="6354576" type="CITY" weightage="60" keywordseo="Facebook">Facebook</keyword>'s <keyword id="35666" type="COMPANY" weightage="60" keywordseo="advertising">advertising</keyword> business is its move into "<keyword id="774829" type="ORGANIZATION" weightage="60" keywordseo="Big-Data">Big Data</keyword>."
Back in Q1 2013, <a href="http://www.businessinsider.com/facebook-is-about-to-launch-a-huge-play-in-big-data-analytics-2013-5">Facebook signed deals with Datalogix, Acxiom, BlueKai, and Epsilon</a>. They are all companies that either hold or process vast troves of consumer marketing and purchase information.
The problem for many advertisers - particularly grocery advertisers - is that the vast majority of consumer purchases take place offline, in a grocery store or on a car dealer's lot, for instance. So the question becomes: "If I buy advertising on Facebook, how do I know that someone bought a can of beans in the supermarket because of it?"
Eric Roza, the CEO of Datalogix, believes he has the answer to that question, now that his partnership with Facebook is rolling. Datalogix's clients include Pepsico, Dr. Pepper Snapple Group, Mondelez and Ford. 
Basically, advertisers use their own offline data, via Datalogix, to target potential consumers with ads on Facebook. They then compare the sales results from that campaign with a control group who saw none of the advertising. The statistically significant difference can be attributed to the Facebook advertising, he says. Datalogix has run 50-plus campaigns on Facebook, Roza told Business Insider recently.
For consumer packaged goods advertisers (CPGs), "It's a large, highly targetable audience, and it's reasonably priced media."
Until Facebook's partnership with Datalogix and the other consumer database companies, Facebook had a bit of a problem with CPGs. They have huge advertising budgets - Procter &amp; Gamble is the largest advertiser on the planet - but there's nothing particularly digital or social about soap and toilet paper.
Two years ago, Facebook made moves to get more advice from big advertisers, and created a "<a href="http://www.businessinsider.com/the-17-ad-execs-who-have-the-most-influence-at-facebook-2012-8">client council</a>" to advise vp/global marketing solutions Carolyn Everson and her staff about what they wanted from Facebook. The council is "dominated" by CPGs, Roza says, and they were saying, "you need to prove to us these products work," says Roza. "CPGs have always been uneasy about lack of measurability."
Worse, "clicks have virtually no signal about who is going to buy," Roza says, referring to a truism in marketing that it takes several different interactions with a brand before a consumer gets all the way through the marketing "funnel" and actually buys something. "People who click on car ads are actually less likely to buy cars - that's my favorite stat of all time."
But the Datalogix partnership has borne fruit, Riza says. "A 3X return on adspend, or greater, is pretty typical [on Facebook]" Roza says. "It compares very favorably" to the traditional media buys, like TV, that grocery brands are comfortable with.
Disclosure: The author owns Facebook stock.

The CEO Of Datalogix Just Gave Us A Glimpse Into Facebook's 'Big Data' Strategy

<keyword id="6368201" type="CITY" weightage="60" keywordseo="MasterCard">MasterCard</keyword> knows what everyone buys. Some 1.8 billion people use its cards at 34 million stores worldwide. 
Retailers can sift through their own records to understand what their customers buy. But they can't as easily figure out the shopping habits of people who buy from other stores.
That's the kind of information that MasterCard hopes to sell to them as it moves into the <a href="http://wikibon.org/wiki/v/Big_Data_Market_Size_and_Vendor_Revenues">$5 billion</a><a href="http://wikibon.org/wiki/v/Big_Data_Market_Size_and_Vendor_Revenues"> big data analytics market</a>. 
Last week, the company's subsidiary, MasterCard Advisors, took an undisclosed stake in a <keyword id="774829" type="ORGANIZATION" weightage="60" keywordseo="Big-Data">big data</keyword> analytics company called <a href="http://www.businessinsider.com/the-2012-digital-100-the-complete-list-1-100-2012-9">Mu Sigma. </a>
The two will offer joint products together using MasterCard's databases and Mu Sigma's analytics technology. 
Mu Sigma is a Chicago- and India-based company that raised a whopping $133 million since it was founded in 2008. That includes a $108 million in 2011 lead by General Atlantic. Its customers include Walmart and Microsoft. 
We asked Gary Kearns, the MasterCard executive vice president spearheading this project to explain MasterCard's plans:
BI: What kind of data will Mastercard will be selling?
Kearns: We aggregate information across the 34 million merchants who accept MasterCard, and create analytics, reports and insights off this rich data. We do not sell the actual transaction data - we sell products like benchmarking reports (how is my business performing compared to other merchants?), and analytics (how can I better understand what my customers might want to purchase?). 
We would also sell this retailer weekly information about its sector – for example, women’s apparel sales each week – so that they could better benchmark their performance.
BI: Can a company use this to find out details about a competitior?
Kearns: We never sell a company information about a specific competitor – it is always a larger, anonymous group.
BI: What kinds of interesting things can a company learn from your reports?
Kearns: A large retailer was able to understand, at an aggregated and anonymous level, what its customers do before and after they shop there. This large retailer would then be able to offer its customers certain incentives to come there and spend more on the items that they may have purchased before and after visiting them.

MasterCard Just Took A Stake In A Hot Big Data Startup 

This post is part of the <a href="http://www.businessinsider.com/category/future-of-business">"Future of Business"</a> series, which examines how cutting-edge technologies are rapidly reshaping our world, from how businesses run to how we live. <a href="http://www.businessinsider.com/category/future-of-business">"The Future of Business"</a> is sponsored by SAP.
<a href="http://www.businessinsider.com/category/future-of-business">See more Future of Business &gt;&gt;</a><div class="image-container float_right" style="width:400px"><div class="image"></div><a href="http://blogs.esri.com/esri/esritrainingmatters/2010/09/08/mapping-time-in-arcgis-10/">Esri</a></div>Piracy is a serious problem on the world's seas.
A U.S. consultancy called Oceans Beyond Piracy estimates that <a href="http://oceansbeyondpiracy.org/">pirates caused $7 billion of damage in 2011</a>.
The good news is that, thanks to technological advances, the problem is getting solved.
The International Maritime Bureau reported a 54% drop in piracy incidents during the first half of 2012 versus the same timeframe in 2011.
The reason: Government agencies and law enforcement entities have started harnessing <keyword id="774829" type="ORGANIZATION" weightage="60" keywordseo="Big-Data">big data</keyword> to prevent piracy before it happens.
"Big data" is a a buzzy tech term that addresses the nearly boundless amounts of information generated every day on a given topic and how computers process it. Remember Watson, IBM's Jeopardy genius? It's a totally similar idea–a computer is fed more information than a person could ever handle, then processes and makes sense of it.
There is a nearly unmanageable amount of data collected as it relates to piracy on the seas. News stories about piracy incidents, interviews with captured pirates, social media posts and emails from pirates, and the like.
These all come from a variety of sources that authorities are now pulling together and processing with computers to learn how to better stop pirates.
With enough information to pull from, a computer can find patterns or trends that would normally evade humans. And when you find a pattern, you can have a good idea when or where something will happen before it actually happens.
A company called Esri runs advanced mapping software that pulls in nuggets of information <a href="http://blogs.esri.com/esri/esritrainingmatters/2010/09/08/mapping-time-in-arcgis-10/">to help visually point out when and where</a> incidents of piracy are likely to occur in the future.
Authorities are now able to turn an incomprehensible mass of information that no one would be able to sift through or organize, and forecast where they need to be to keep the seas safe.
It is, <a href="http://blogs.hbr.org/cs/2012/10/when_pirates_meet_advanced_analytics.html">as Harvard Business Review puts it</a>, a "genuine predictive model."

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