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According to the Analytics &amp; <keyword id="774829" type="ORGANIZATION" weightage="60" keywordseo="Big-Data">Big Data</keyword> Salary Report 2016 by Jigsaw Academy &amp; <keyword id="3350451" type="UNKNOWN" weightage="80" keywordseo="Analytics-Vidhya">Analytics Vidhya</keyword>, Mumbai pays the highest for <a href="http://www.businessinsider.in/searchresult.cms?query=Big+Data&amp;sortorder=effectivedate">Big Data</a> and <a href="http://www.businessinsider.in/searchresult.cms?query=Data+Analytics&amp;sortorder=effectivedate">Data Analytics</a> jobs among all Indian cities. In absolute numbers, the figure stands at 12.19 lakhs p.a. For the survey, data points were collected from over 60,000 people who contacted the team. 
 
According to the report, <a href="http://www.businessinsider.in/searchresult.cms?query=Big+Data&amp;sortorder=effectivedate">Big Data</a> professionals earn 8% more than the data scientists. However, one’s salary can go up 26% with knowledge of both data science and Big Data technologies. 
 
R skills pay the most and are used the most. However, data shows the highest salaries are paid to analysts who know more than just R or Python. Combinations that include R and Python are best paid with the highest recorded salary for 2015 - 2016 being 12.75 lakhs p.a. for analysts with knowledge of SPSS, SAS, R and Python. 
 
The biggest jump in salaries is seen after the 5-year mark, where analysts can expect up to a 70% raise with an average pay of 12.3 lakhs p.a. A decade of experience can boost this figure by more than 250%. 
 
Image credit: Indiatimes

Mumbai
pays highest to Analytics and Big Data Professionals: Report

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

Automation is spelling doom for IT services professionals in India with the recent flurry of layoffs by major IT players, a recent report suggests that adding analytics skills to your skill set can save careers for IT professionals, and maybe also help them get a bump in their pay. The Indian IT industry has for the better part been services focused. While that worked a decade ago, it is no longer the need of the industry. The IT industry can transform itself into IT 2.0 by riding on the big data wave but the need of the hour is to move fast if they have to stay relevant. Jigsaw Academy has launched the <keyword id="4596836" type="UNKNOWN" weightage="20" keywordseo="analytics-india-industry">Analytics India Industry</keyword> Report 2017 – Salaries &amp; Trends which has interesting insights on the kind of salaries currently being offered to professionals with analytics skills. <div type="embedgroup"> <div type="Article" hostid="261" msid="58894102" title="Ditch Sodas This Summer, Opt For This New Flavoured Green Tea Instead" rank="1.0" kind="RELATED" publishDate="May 29, 2017, 3:30 PM" mstype="2" mssubtype="0"></div></div>






<keyword id="294572" type="TECHNOLOGY" weightage="20" keywordseo="machine-learning">Machine Learning</keyword> is a Good Bet The bet on Machine Learning is finally paying off and it is the best paying analytics skill in the market currently, with an average pay of Rs. 10.43 LPA, even beating Big Data to the top spot, which comes in close with an average pay of Rs. 9.93 LPA. However, what companies seem to cherish are professionals with both these skill sets, a combination which fetches a cool Rs. 13.94 LPA on an average. A huge change, as per the report, is the industry wide adoption and use of open source tools. In fact, for the first time this year, top tools that can help professionals get into analytics are R and Python, both of which are wildly popular open source tools. This points to the fact that popularity of expensive analytics computing software is on a steady decline. 

 

 

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 The salaries based on tools too seems to reflect this. R and Python skills alone pay better than SAS, with average pay of Rs. 10.40 LPA and Rs. 10.12 LPA respectively. But here too, it is the combination of multiple skillsets seems to pay the best. The best paid professionals are the ones with SAS + R + Python proficiency, with an average pay of Rs. 12.91 LPA. The report also includes more salary insights based on city, company size, experience, and domain. Machine Learning algorithms are dominating the business projects landscape with regression as the lone crusader fighting the battle for traditional statistical techniques. In fact, the top algorithms that organizations want people to pick up are Machine Learning ones. 

 

 

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Big Data is Still Big This is not to say Big Data has lost any steam. <keyword id="1255918" type="UNKNOWN" weightage="20" keywordseo="Big-Data-analytics">Big Data Analytics</keyword> roles have evolved and the last 18 months has seen some level of consolidation in terms of techniques and tool knowledge needed. As per the report, Hadoop skills, in combination with Spark and Tableau, and along with knowledge of popular databases like Mongo and Cassandra, makes for that rare big data unicorn. The analytics industry has always favoured people with knowledge of multiple tools and that still stands true. The industry is on the lookout for specialists in different areas of analytics who can work on a project end-to-end. The annual report by <keyword id="3257179" type="UNKNOWN" weightage="20" keywordseo="Jigsaw-Academy-and-Analytics-Vidhya">Jigsaw Academy and Analytics Vidhya</keyword> is compiled to cater to the needs of aspirants, analytics professionals, and employers. Based on information collected from 65,000 + analytics professionals with advanced analytics/data science skills, the report explains in detail the industry and salary trends for the upcoming year.

Up-skilling with Analytics Can Save your Career in the IT Sector

<table class="image-container float_right" width="200"><tr><td><div class="image"></div>Business InsiderFacebook's Ken Rudin</td></tr></table><keyword id="6354576" type="CITY" weightage="60" keywordseo="Facebook">Facebook</keyword> <a href="https://www.facebook.com/careers/teams/data">has 41 job openings</a> on its data and <keyword id="6359249" type="COMPANY" weightage="60" keywordseo="analytics">analytics</keyword> team. That's a large chunk of its 240-some tech positions to fill.
If you toss your resume into the bucket and get called for an interview, know this: The skill your potential future boss really wants is "understanding people," explained Ken Rudin, head of analytics at Facebook.
So he said last night at "<keyword id="774829" type="ORGANIZATION" weightage="60" keywordseo="Big-Data">Big Data</keyword> Date Night," a one-evening event held in Mountain View, Calif.
"We're looking for people who are interested in understanding human nature and social behavior and who find it really appealing to be able to work with the largest data set ever amassed of a slice of human life on a daily basis," he said. "So the people who make good analysts are the ones who are really passionate about understanding people."
Facebook CEO Mark Zuckerberg, you may recall, <a href="http://www.andykessler.com/andy_kessler/2007/03/wsj_weekend_int.html">double-majored in both psychology and computer science</a> before he dropped out of Harvard.
That's not to say that the tech part is unimportant. Facebook stores 100+ petabytes of data, he says. (That's equivalent to the entire written works of mankind, in every language <a href="http://mozy.com/blog/misc/how-much-is-a-petabyte/">from all of recorded history, times two</a>.) It takes technical chops to manage that.
But it's less about using technology than about having a "data-driven" mindset, he said.
At Facebook, that mindset is so important that every new employee goes through a two-week immersive program called "Data Camp."
In week one, new recruits are introduced to the tech tools and walked through the "life of a user click" which is what happens as people share their status or upload photos.
The second week covers creative problem solving. Employees are given actual tasks relating to "whatever is going on with the business." Then "they have to present the results," he said.
Data camp is difficult even for the highly experienced. In a famous incident <a href="http://www.businessweek.com/articles/2012-10-04/facebook-the-making-of-1-billion-users">reported in BusinessWeek,</a> Jocelyn Goldfein came to Facebook from VMware and she still had to attend camp. At the end she turned on her project. Much to her horror, it broke the company's email system, taking it down for most of the day. (She's <a href="http://www.businessinsider.com/facebook-guilt-2012-10">had a stellar career since</a>.)
Here's another tip to help you land a job on Facebook's tech team: one of Rudin's favorite books is <a href="http://www.amazon.com/How-Measure-Anything-Intangibles-Business/dp/0470539399">"How to Measure Anything"</a> by Douglas Hubbard.

Want To Work At Facebook? Here's The Skill They REALLY Want

<div class="image-container float_right" style="width:400px"><div class="image"></div><a href="http://statigr.am/p/287706813096290931_2786049">statigr.am/membonifacio</a></div><keyword id="6355629" type="CITY" weightage="60" keywordseo="Google">Google</keyword>, in the end, is a company that's all about <keyword id="6355729" type="ORGANIZATION" weightage="60" keywordseo="data">data</keyword>. Its wildly profitable search-ad business depends on input from people to target ads. So it shouldn't be much of a surprise that Google applies some of those lessons to its employees. 
Farhad Manjoo at Slate <a href="http://www.slate.com/articles/technology/technology/2013/01/google_people_operations_the_secrets_of_the_world_s_most_scientific_human.single.html">takes a deep look at Google's HR</a> and finds a rigorously pragmatic, data obsessive organization. The division, called People Operations (POPS for short) works constantly towards efficiency and cost effectiveness.
He writes:
"At the heart of POPS is a sophisticated employee-data tracking program, an effort to gain empirical certainty about every aspect of Google’s workers’ lives — not just the right level of pay and benefits but also such trivial-sounding details as the optimal size and shape of the cafeteria tables and the length of the lunch lines."
That data goes into things like optimizing the impact and cost effectiveness of Google's legendary perks. For example, the 5 month leave for mothers came after they realized they were losing too many women, and that the losses came primarily from new mothers. The data-based extra 2 months of leave decreased attrition by 50 percent, and ended up costing nothing extra because recruiting in Silicon Valley is so expensive.
That rigorous data collection also goes into <keyword id="6357342" type="PERSON" weightage="60" keywordseo="Hiring">hiring</keyword> and management. "[We want to] bring the same level of rigor to people-decisions that we do to engineering decisions," <a href="http://www.slate.com/articles/technology/technology/2013/01/google_people_operations_the_secrets_of_the_world_s_most_scientific_human.single.html">according to people analytics head Prasad Setty.</a> 
Google's famous for promoting a flat hierarchy. But after extensive data analysis, they found that middle managers are extremely important, and found out ways to improve bad ones.
Google's using <keyword id="6357280" type="PERSON" weightage="60" keywordseo="workplace">workplace</keyword> <keyword id="6359249" type="COMPANY" weightage="60" keywordseo="analytics">analytics</keyword> in a fascinating way. The first thought upon hearing that term is the image of draconian targets and productivity measures; of someone watching over your shoulder to make sure you aren't wasting company time or dollars.
But workplace analytics can also be used to determine the optimum lunch line, which is three or four minutes, or to figure out that something that seems lavish, like an extra two months of leave for new mothers, isn't costly, and is probably even a good investment in terms of happiness. 
It's something more companies will probably look to emulate in the future.
Find the full piece <a href="http://www.slate.com/articles/technology/technology/2013/01/google_people_operations_the_secrets_of_the_world_s_most_scientific_human.single.html">here</a>
NOW READ: <a href="http://www.businessinsider.com/larry-page-management-secrets-2013-1">Google's Larry Page Talks About His Management Philosophy</a>

Google Tracks Its Own Employees As Closely As It Tracks You On The Internet

<keyword id="43217" type="CITY" weightage="100" keywordseo="Tech-Mahindra">Tech Mahindra</keyword>, in a period of four years is leading the pack through strategic acquisitions that complement its inherent strengths and capabilities. As a result, at a time when the IT industry is suffering from tapering growth, Tech Mahindra has adapted to the changing times and developed skills in digital technologies to not just survive the competition but also grow consistently even amidst controversial layoffs. Business Insider caught up with Jagdish <keyword id="2481" type="PERSON" weightage="20" keywordseo="Mitra">Mitra</keyword>, Chief Strategy &amp; Marketing Officer, Tech Mahindra, to understand the journey of the company and how it ensures hiring and retaining the best people, “One of the ways we stay relevant is by working closely with start-ups through a subsidiary, Tech Mahindra Growth Factories. The objective of Growth Factories is to incubate disruptive and futuristic internal and external innovative ideas apart from funding those.” Two out of the four start-ups incubated by Growth Factories are from an Edtech background. UpX Academy is an online training institution that provides a robust and advanced curriculum through its Big Data, Data Analytics &amp; Machine Learning courses. Designed by industry experts, these courses are aimed at integrating real-world applications through case studies, exercises and real-world datasets enabling professionals at work to enhance their skill sets in the mentioned trending technological verticals. 

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Both these start-ups have been supporting and strengthening the employees’ in-house to upskill and reskill for growth in their respective jobs. With a workforce of over 117,000 employees who are looking to transition to the next generation technologies, these training provisions have made TechM a great choice of workplace for employees. 

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 “Cost advantage had been one of the biggest factors that drove the growth of India’s IT outsourcing services industry, but since then the client requirements have been changing due to advancement in technology and digitisation. Professionals are realising the need to upgrade their skills in order to cater to the evolving requirements of the clients and with the correct skill sets, they are able to perform better at their roles and are able to fast-track their careers and get better opportunities on the professional front,” says Mitra who said that with changes in the technology over the past few years, there has been a lot of interest to understand and learn about <keyword id="4822054" type="UNKNOWN" weightage="20" keywordseo="data-analytics-and-data-sciences">Data Analytics and Data Sciences</keyword> and they remain the most sought-after courses for IT professionals.

Here’s how Tech Mahindra is using start-ups to ensure retention of their best IT employees

<div class="image-container float_right" style="width:400px"><div class="image"></div><a href="http://www.flickr.com/photos/poopface/2527944420/">man with face via Flickr</a></div>A glass of <keyword id="21038" type="COMPANY" weightage="60" keywordseo="Orange">orange</keyword> juice seems like one of the simplest things in the world. That might be true if you squeeze it yourself, but when you try to make it for millions of consumers, it turns out to be incredibly complex.
Duane Stanford <a href="http://www.businessweek.com/articles/2013-01-31/coke-engineers-its-orange-juice-with-an-algorithm">at Bloomberg Businessweek</a> takes a close look at how Coke manages to make every glass of orange juice the same. The company has to fight the changeable moods of nature, and plan a whole year based on a 3 month growing season. 
They use an incredibly complex algorithm <a href="http://www.businessweek.com/articles/2013-01-31/coke-engineers-its-orange-juice-with-an-algorithm">known as the "Black Book"</a> to control everything from picking schedule to the way the juice tastes:
Revenue <keyword id="6359249" type="COMPANY" weightage="60" keywordseo="analytics">Analytics</keyword> consultant Bob Cross, architect of Coke’s juice model, also built the model Delta Air Lines uses to maximize its revenue per mile flown. Orange juice, says Cross, “is definitely one of the most complex applications of business analytics. It requires analyzing up to 1 quintillion decision variables to consistently deliver the optimal blend, despite the whims of Mother Nature.”
The Black Book model includes detailed <keyword id="6355729" type="ORGANIZATION" weightage="60" keywordseo="data">data</keyword> about the myriad flavors — more than 600 in all— that make up an orange, and consumer preferences. Those data are matched to a profile detailing acidity, sweetness, and other attributes of each batch of raw juice. The algorithm then tells Coke how to blend batches to replicate a certain taste and consistency, right down to pulp content.
It's not just taste. The model also has to be able to account for weather patterns, potential supply and cost pressures, and transportation.
Why bother?
<ul>
<li>Consumers pay a high premium for fresh juice</li>
<li>It's an increasingly important business as people move away from <keyword id="6442118" type="ORGANIZATION" weightage="60" keywordseo="soda">soda</keyword></li>
<li>Pepsi (which owns Tropicana) is a huge competitor, so everything the company can do to increase quality and keep costs down takes on outsize importance</li>
<li>Coca Cola's major juice brand in Asia (Minute Maid Pulpy) became a billion dollar plus brand within three years of launching</li>
</ul>
It sounds like an incredible amount of effort and data for something that takes seconds to drink, but billions of dollars are at stake. 
NOW READ: <a href="http://www.businessinsider.com/why-the-future-is-outside-the-us-2012-10">Coke CEO Muhtar Kent Perfectly Sums Up Why The Future Is Outside Of The US</a>

Making Orange Juice Involves Up To A Quintillion Variables

(Photo Source: wikipedia.org) <ul><li>The demand for <keyword id="1993669" type="COMPANY" weightage="20" keywordseo="Big-Data-and-Analytics">big data and analytics</keyword> experts as India’s Information Technology (IT) services push for a digital edge has never been greater. But, the country reportedly has fewer than 10% of <keyword id="1096926" type="PERSON" weightage="20" keywordseo="Data-scientists">data scientists</keyword> available globally, according to a recent report. </li><li>With the need of faster decision-makers in the IT industry, the demand for big data professionals is expected to rise by 40% in next two years. </li><li>Over 20%-30% of the total revenue for major <keyword id="6357647" type="UNKNOWN" weightage="20" keywordseo="it-companies">IT companies</keyword> – Tata Consultancy Services, Infosys, Wipro, HCL -- now comes from digital services including big data and analytics.</li></ul>Big data and analytics is one of hottest sectors, particularly for Indian information technology services (IT) companies as they aim to capitalise on the technologies’ potential for simplifying business processes, and helping companies become more competitive. However, it appears that India severely lacks data scientists. India <a href="https://www.business-standard.com/article/current-affairs/india-has-less-than-10-of-the-data-scientists-available-globally-report-118112900077_1.html">reportedly</a> has less than 10% of data scientists available globally, according to the professional network LinkedIn. While the US has over 40% skilled professionals in the big data and analytics domain. These numbers show that India may be challenged to effectively serve the growing data servicing market. With the need for fast decision-makers, the demand for big data professionals is expected to rise by 40% in the next two years, Business Standard <a href="https://www.business-standard.com/article/current-affairs/india-has-less-than-10-of-the-data-scientists-available-globally-report-118112900077_1.html">reported </a>stating a US Department of Statistics report. The gap is likely to be a big worry for India’s competitive IT services companies that have begun efforts towards training staff in data science. About 75% companies in India have invested or planning to invest in data science, according to Gartner. Wipro is reportedly offering training under its ‘School of Decision Sciences’ programme to skill staff on analytics and business insights. Pareekh Jain, an independent IT outsourcing advisor, reportedly said that data scientists form the backbone of industries that rely on technologies such as Internet of Things (IoT), <keyword id="107950" type="TECHNOLOGY" weightage="20" keywordseo="artificial-intelligence">Artificial Intelligence</keyword> and <keyword id="294572" type="TECHNOLOGY" weightage="20" keywordseo="machine-learning">Machine Learning</keyword>. <a href="https://www.financialexpress.com/opinion/the-rise-of-flexible-employment-can-automation-governed-it-flexi-staffing-industry-boost-the-economy/1397292/">According to</a> ‘Future of Jobs 2018’ report, with advances in machines and growing technologies like artificial intelligence can potentially replace 75 million jobs by 2020. With inputs from IANS SEE ALSO: <a href="https://www.businessinsider.in/engineering-graduates-in-india-are-far-more-employable-than-mbas-survey/articleshow/66730589.cms">Engineering graduates in India are far more employable than MBAs: survey</a> <a href="https://www.businessinsider.in/amid-unemployment-tensions-70-of-indian-youth-lack-awareness-of-governments-much-touted-skill-development-programme/articleshow/66600178.cms">Amid unemployment tensions, 70% of Indian youth lack awareness of government’s much-touted skill development programme</a> <a href="https://www.businessinsider.in/india-records-the-highest-unemployment-rate-in-two-years-says-study/articleshow/66555760.cms">India records the highest unemployment rate in two years, says study</a>

Big data and analytics may be the hottest sector, but India has a serious dearth of data scientists

<div class="image-container float_right" style="width:400px"><div class="image"></div><a href="http://www.youtube.com/watch?v=iYKoAKXeLdk&amp;hd=1">Mashable/YouTube</a></div>As a Business Insider reader, you may have noticed a window pop up at the bottom of your page after reading an article, suggesting another piece you might find interesting. There's more to those suggestions than you think.
They're the creation of <a href="https://www.sailthru.com/">Sailthru</a>, a New York based startup which announced today that it's receiving $19 million in Series B funding from <keyword id="274436" type="COMPANY" weightage="60" keywordseo="Benchmark-Capital">Benchmark Capital</keyword>. The company distinguished itself and increased revenue by 270 percent in a very crowded field by making decisions in real time and respecting users and their data. 
Benchmark's Bill Gurley has joined the board. 
"People have been talking about <keyword id="774829" type="ORGANIZATION" weightage="60" keywordseo="Big-Data">big data</keyword> for a long time," <keyword id="1769931" type="UNKNOWN" weightage="60" keywordseo="Sailthru">Sailthru</keyword> CEO Neil Capel told Business Insider, "but they're only sort of collecting the data and there are a lot of sort of flashy kind of graphics to show that big data, but really what it's about is how you make real time decisions on those users so you can make their experience more relevant."
The approach is something they call smart data, making automated decisions in real time that present content and options that are relevant and useful, actually reacting to behavior and preferences. 
"It's not just putting people into buckets. It's customizing and personalizing those experience to actual individuals, Capel says. "Now a lot of other companies out there will say something along those lines, but normally they're just looking at a cookie full of data and trying distinguish from that kind of data set. But what we're really trying to do is create an end-user experience where that user keeps coming back, that user builds up more and more of a profile dataset with us and is getting something out of the relationship as well."
The second thing that sets the company apart is an focus on respecting the user. "What we try to do is use data to try and really improve the end user experience, I think that a lot of companies out there do other things with data that should not be done," Capel says. 
That includes custom content and, for example, throttling back emails if a customer reaches a certain disengagement score. 
The idea and focus come from Capels own frustrations on the web. I wanted to be treated that way by websites, which is where they idea comes from, really," Capel revealed. "I wanted to be respected, I wanted to have that kind of guidance so I could find information."
Sailthru has grown its business by growing its clients. "We want to create the most sustainable businesses for our clients, Capel says, "we're really educating the entire team that the way that you create that, the way you create that maximum lifetime value is to respect the user, so we talk about it an awful lot."
The company already has clients on five continents and is expanding into Europe in Q2. Capel plans to use the funding to grow the company aggressively, to double the sales team and hire more engineering talent. 
"It's really about expansion for us in the next 3 years," Capel says. "We're growing at a tremendous rate, in 3 years we should be in IPO range and that's kind of what we're focusing on."

Sailthru Raises $19 Million For Using Big Data Respectfully

<div class="image-container float_right click-to-enlarge" style="width:355px"><div class="image"><a title_source="Justin Sullivan / Getty Images" title_caption="Mark Zuckerberg" class="zoomin" href="http://static5.businessinsider.com/image/505374d1eab8ea8e30000007-960/mark-zuckerberg-8.jpg"></a></div>Justin Sullivan / Getty ImagesMark Zuckerberg</div>When <keyword id="6354576" type="CITY" weightage="60" keywordseo="Facebook">Facebook</keyword> CEO <a href="http://seekingalpha.com/article/1392101-facebook-s-ceo-discusses-q1-2013-results-earnings-call-transcript?part=single">Mark Zuckerberg took Wall Street analysts' questions about his Q1 2013 earnings</a> last week, there was one theme he kept returning to: Facebook's new Big Data capabilities. Most people think Facebook is a straightforward <keyword id="35666" type="COMPANY" weightage="100" keywordseo="advertising">advertising</keyword> play: It has a massive audience of 1 billion users, and advertisers can buy ads targeting slices of that audience. What could be simpler? But in the earnings release, three of the six highlights of the quarter were about "Big Data," the trendy notion that the future of marketing lies in super-deep, super-complex data analytics rather than the raw power to deliver lots of eyeballs.
Measurement, measurement, measurement
Here are Facebook's Big Data moves in Q1:
<ul>
<li>Launched new advertising products such as Lookalike Audiences, Managed Custom Audiences, and Partner Categories, which help marketers improve their targeting capabilities on Facebook.</li>
<li>Partnered with Datalogix, Epsilon, Acxiom, and BlueKai to enable marketers to incorporate off Facebook purchasing data in order to deliver more relevant ads to users.</li>
<li>Enhanced ability to measure advertiser ROI on digital media across the internet through our acquisition of the Atlas Advertising Suite.</li>
</ul>
The first two points underplay what Facebook is up to. Most people have no idea what Datalogix, Epsilon, Acxiom and Bluekai actually do. Insiders, however, know that Facebook alliances with these companies give it one of the most powerful consumer databases on the planet.
<ul>
<li>Epsilon <a href="http://www.epsilon.com/about-us/our-story">has data on 300 million company loyalty card members</a> worldwide, and a databank on 250 million consumers in the U.S.</li>
<li>Acxiom has "<a href="http://acxiom.com/marketing-services/data-and-database-management/#Buying%20and%20Renting%20Data">a comprehensive national database covering more than 126 million households and 190 million individuals</a>."</li>
<li>Datalogix says, "<a href="http://www.datalogix.com/audiences/online/">Our database contains more than $1 trillion in offline purchase-based data</a> and we’re able to covert this data, and any CRM data, into an online universe."</li>
<li>Bluekai <a href="http://www.bluekai.com/marketers.php#bluekai_exchange">is a data management platform</a> — marketers bring their own data to those companies, and Bluekai will crunch it and turn it into a strategy for making marketing more effective.</li>
</ul>
The data stored in these companies tends to be anonymized or "hashed." They are not able to identify Jane Smith, shoe-shopper from Montclair, N.J., as an individual. But they are able to identify thousands of Janes who shop for shoes in any zip code you want, in aggregate. All this is now paired with Facebook's own data — profiles of 1 billion-plus users who are all happily documenting the minutiae of their lives, and their shopping, on Facebook.
Second only to Google It's dramatic stuff, in terms of its scale. But Zuckerberg hinted that Facebook is still in the baby steps phase of its big data plan, because the last part of the plan — Atlas — isn't even fully plugged in yet. Atlas is a gigantic internet ad server, previously owned by Microsoft. It's like the plumbing of the web: It serves up ads all over the web and takes a cut from any advertiser using its services. Atlas carries between 10% and 15% of all ads for buyers on the web, <a href="http://www.leadledger.com/tech/category/AdServer_DCO">according to LeadLedger</a>. It is second in size only to Google's DoubleClick ad server. Most people have yet to digest that fact: Facebook is now the second biggest web ad server to Google. The deal closed recently, and Facebook has yet to report the revenue impact, if any, of Atlas in its own numbers.
Atlas has yet to shrug
A lot of people assumed that Facebook bought Atlas because it wanted to create an off-Facebook ad network, maybe one in which Facebook data could be used to enhance targeting through Atlas. But that's not the primary goal for Atlas. Facebook has been quite clear about why it acquired Atlas from Microsoft: <a href="http://techcrunch.com/2013/02/28/facebook-acquires-atlas/">It wants the data Atlas can provide</a>. <a href="http://seekingalpha.com/article/1392101-facebook-s-ceo-discusses-q1-2013-results-earnings-call-transcript?part=single">Zuckerberg said on his Q1 call</a> that "Atlas is a really important part of continuing to develop our measurement capabilities": He wants Facebook to be able to tell advertisers how their ads perform even when consumers are offline, and haven't been anywhere near Facebook prior to going shopping:
We believe the Atlas platform will help us demonstrate even more clearly the connection between ad impressions and purchases. We could help marketers measure the effectiveness of their ad impressions better not just on Facebook, but across the entire internet. This means we can take the advancements we have made in measurements on Facebook, including our integrations with Nielsen and Datalogix, and expand them to a much larger audience and to many more purchases.
… Our focus with Atlas is on impression based ads. And the idea is that, you know historically a lot of ads online which were more based on search, the attribution was always that last click. And as people have looked more holistically at all the ad spending they are doing, what they find is that it's not just the last click that matters but it's all the impressions leading up to that click. Importantly, we also drive sales offline. And offline people aren’t clicking through the purchase at all but they are actually walking into a store. So in some sense there is no last click.
And so our focus with Atlas is to take that technology and enable us to improve our ability to connect ad impressions to purchase behavior both offline and online, and not just on clicks but across different ad purchases people do. So that’s exactly why we made that purchase.
Most ordinary Facebook users don't realize how ambitious these plans are. If you bought something with a credit or debit card in the last couple of years, you're probably in Facebook's data pool right now. Disclosure: The author owns Facebook stock.

Facebook Is About To Launch A Huge Play In 'Big Data' Analytics

While there is a lot of talk around ‘digital transformation’, what it really boils down to is predicting the customer’s intent and act on it. This can help traverse channels smoothly without ever having to start over the conversation from the scratch. 
 
Personalized and intent driven interactions across any channel helps companies come up with quick solutions to a customer’s problems. [24]7 is a <a href="http://www.businessinsider.in/searchresult.cms?query=big+data&amp;sortorder=effectivedate">big data</a> and <a href="http://www.businessinsider.in/searchresult.cms?query=machine+learning&amp;sortorder=effectivedate">machine learning</a> firm that does just that. The platform uses predictive models tuned by 1.5B+ annual interactions. Its technology spans across <keyword id="294572" type="TECHNOLOGY" weightage="80" keywordseo="machine-learning">machine learning</keyword>, <a href="http://www.businessinsider.in/searchresult.cms?query=predictive+analytics&amp;sortorder=effectivedate">predictive analytics</a> and natural language. 
 [24]7’s <keyword id="774829" type="ORGANIZATION" weightage="60" keywordseo="Big-Data">Big Data</keyword> and machine learning technologies power self-service ( e.g. <keyword id="3415311" type="UNKNOWN" weightage="80" keywordseo="Virtual-Agent">Virtual Agent</keyword>) as well as assisted service channels (e.g. <keyword id="3415312" type="UNKNOWN" weightage="60" keywordseo="Digital-Chat-Agents">Digital Chat Agents</keyword>). The Virtual Agent has been trained on real conversations and therefore far better at responding to a customer’s queries. The company claims that in the first 9 months of the <a href="http://www.businessinsider.in/searchresult.cms?query=Virtual+Agent&amp;sortorder=effectivedate">Virtual Agent</a> being deployed on a client‘s website, over 720k questions were answered with an industry leading response accuracy rate of 92%. 
 
[24]7’s pool of 5000+ digital chat agents is the largest in the world. These can help with a purchase decision or to address a service issue, to deliver successful outcomes in the moments that matter most. 
 
So the next time you type into the chat tab on a website, remember, it might not be a human at the other end. 
 
(Image for representation purposes only) 
 
<a href="http://img.scoop.it/gyc-vnePuQ6kWlphYLtMwzl72eJkfbmt4t8yenImKBVvK0kTmF0xjctABnaLJIm9">Image Source</a>

This Indian startup has the largest pool of digital chat agents in the world

The Income Tax department has become tech-savvy and is using analytical tools to assess personal bank deposits to crackdown on <keyword id="6356023" type="UNKNOWN" weightage="20" keywordseo="Black-Money">black money</keyword>. The tax officials are using <keyword id="774829" type="ORGANIZATION" weightage="20" keywordseo="Big-Data">big data</keyword> analytical tools for the first time to keep an eagle’s eye on personal accounts. 
 
Earlier, such tools were used only for corporate tax. 
 
"It's practically impossible for tax officials to go through all the data obtained from banks and compare it with other tax-related data. Analytics is being used to look at discrepancies. This would then be scrutinised by experienced tax officials,” a person close to the development told ET. 
 
Through this big data analytical tool, the tax officials can scan through tax returns filed by individuals, companies, etc. In case of irregularities, these analytical tools raise red flags. Tax officers could then issue notices to individuals based on this after December 31. 
 
Talking to ET, another person close to the development, said, "What the analytics tool can throw up is not just the cash deposited in banks by an individual, but details of the income tax paid over the years, corporate tax paid by his company, number of employees he has and whether they too have deposited money recently. Every detail of the individual's tax history can be known.” 
 
Under the bill to amend Section 115BBE of the Income Tax Act, deals with unexplained deposits in banks will be taxed. According to the amendment, tax officers can now tax such deposits at 60% (plus cess) as against 30% earlier. The new tax law is applicable from April 1, this year.

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