The Big Data Recruiting PlaybookThe 9 Things You Need to Know to Be Successful

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Contents

Introduction

Question 1: What is Big Data? The Three V’s of Big Data .................................................5

How Does Big Data Create Value? ....................................6

Question 2: What Is Big Data Recruiting? The Three V’s of Big Data Recruiting ................................9

Question 3: Why Use Big Data Recruiting?It’s All About The Moneyball ...........................................13

Question 4: How Does Big Data Find Candidates?

Examples of Sources Big Data Evaluates .......................16

Question 5: How Does Big Data Bring More Context To Resumes?

Bringing Value .................................................................18

Question 6: How Does Big Data Help You Engage With Candidates?

Find Better Candidates ...................................................20

Engage More Personally .................................................21

Question 7: What Industries Should Use Big Data Recruiting?

The War For Tech Talent .................................................24

Keeping Costs Down ......................................................25

Question 8: Is Big Data Recruiting A Fad or Here To Stay?

Big Data Recruiting is More Than a Passing Fad ............27

Question 9: What Is The Future of Big Data?

Conclusion

Glossary

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Introduction

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Big data is having a tremendous impact on how modern businesses use and interpret data. It’s currently used for everything from financial services, to gauging productivity, to even monitoring the weather. Companies across the spectrum — and from every industry — are looking to big data for solutions on how to leverage available data in meaningful ways. In fact, 42 percent of companies have already invested in big data or plan to within the next year.

So, it should come as no surprise that the recruiting industry has integrated big data recruiting into its hiring efforts. Big data recruiting helps companies sort through a wealth of information to ultimately see a more complete picture of candidates.

Unfortunately, at first glance, big data can also be confusing. What exactly is big data, and how can it help recruiters and HR managers find the right candidates? Can more information really help you find the right person for your open position, or is big data just the newest trendy buzzword?

We know you have questions about big data recruiting — and we’re not going to pretend that understanding big data is easy. But the way the recruitment process stands now is fundamentally flawed, and big data can be a useful tool to help streamline and improve your process.

After all, the average time to hire for small organizations is 29 days according to the Society for Human Resource Management. For big companies, this number balloons to as many as 43 days.

Despite the weak economy flooding the marketplace with people seeking jobs, the skills gap is becoming an ever larger problem for companies looking for individuals with hard-to-find skills, such as developers. According to a Silicon Valley Bank survey, nine out of 10 companies found it challenging to find candidates with the right skill set for the job.

Since big data recruiting is relatively new, HR managers and employers have plenty of questions about what it is and how it works. This ebook will serve as a resource, answering all your biggest big data recruiting questions. Read the whole ebook from start to finish, or just skip to your most pressing question.

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Question 1: What is Big Data?

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Before we dive into big data recruiting and how it can help you recruit top talent, we need to start with a solid foundation. It’s important to understand big data and what it is before we can talk about how to use it as a tool for recruitment.

In their book Big Data: A Revolution That Will Transform How We Live, Work, and Think, authors Viktor Mayer-Schönberger and Kenneth Cukier state that big data “refers to the things one can do at a large scale that cannot be done at a smaller one, to extract new insights or create new forms of value in ways that change markets.”

But this is a fairly broad overview of big data and what it can do. In fact, many people routinely confuse it with more common analytics. While both involve numbers in order to transform data into something meaningful, there are a few things that set big data apart from the pack.

The Three V’s of Big DataWhat sets big data apart from analytics involves three v’s: variety, velocity, and volume. To be defined as “big data,” it must adhere to each of these three criteria. Let’s take a closer look at each aspect of big data.

Volume: This is the most obvious example of big data. Frankly, it’s what puts the “big” in “big data” and is likely the least confusing aspect for most people. Big data deals with extremely large data sets, ranging from terabytes to petabytes. Since a terabyte is approximately one trillion bytes, this is a staggeringly large amount of information to process. For instance, there are about 175 million tweets sent out daily and LinkedIn processes petabytes of data just to offer users other people they might know using the site.

“Big data is any amount of data that requires special data management, database solutions (e.g. Mongo). If you had a huge amount of data, it simply wouldn’t work in a traditional database format.

Few companies or institutions have true big data. You really need specialized solutions, like Hadoop, for example to make it work. However, the technologies built around big data are useful outside of their traditional uses.”

~Dr. Vivienne Ming, Chief Scientist, Gild, Inc.

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Variety: Variety means big data can read a wide spectrum of different kinds of information. Since big data includes a mix of data types, this could mean anything from text, to audio and video information, to log files. This could also mean structured or unstructured data. Structured data is identifiable because it is organized in a way that can be easily slotted into a database. Structured data gives names to each field in a database and defines the relationships between the fields. Unstructured data, however, has no identifiable structure. This form of data is on the rise and by 2015 it’s predicted to grow by more than 1,600 exabytes.

Velocity: Big data doesn’t just look at a variety of information; it also does so very fast. Big data is used for information that occurs rapidly and needs to be addressed rapidly. For instance, you don’t want to wait when catching fraud on a customer’s account or analyzing real-time Twitter streams for valuable information.

According to Dr. Vivienne Ming, Chief Scientist at Gild, “Velocity can be anything - like tweets, Google searches, Facebook posts, or even transactions at Walmart stores. By nature, they’re also high volume.” Big data might be large, but its size doesn’t slow it down.

How Does Big Data Create Value? Since you now know what sets big data apart from analytics, you might wonder how it can present value. (We’ll talk about its usage for recruiting later in the ebook.) McKinsey & Company studied big data and discovered it creates value in the following five ways:

1. Transparency: The study found big data can present significant value by making a large amount of data easier to view and evaluate. This transparency makes data much more usable by organizations. Using recruiting for developers as an example, big data can find a candidate’s publically offered code from all over the web and make it transparent for companies to evaluate.

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2. More Accurate Information: In today’s technology-focused age, organizations are creating and storing more digital information than ever before. Big data can help companies collect more accurate and detailed performance information in order to make more informed decisions.

3. Segmentation: Big data allows users to segment audiences, data, and information into ever narrower niches.

4. Analytics: Analytics and big data aren’t interchangeable. Instead, by amassing and analyzing large volumes of information (something traditional analytics can’t do), big data gives companies the capability of having more meaningful analytics. With better analytics comes smarter and more informed decisions about everything from worker productivity to recruiting.

5. Improved Development: Because big data gives companies access to more insights — more meaningful information that other technologies miss and traditional analytics fall short of — organizations can use big data to make more intelligent decisions across the board.

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Question 2: What Is Big Data Recruiting?

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So how does big data apply to the recruiting process? Once again, we need to look at the three v’s of big data. After all, sometimes it’s easy to mistake big data recruiting with more general recruiting analytics. For instance, regular recruiting analytics can help you see which candidates are likely to become top performers or the social channels that provide the best people. Meanwhile, big data recruiting can predictively indicate candidates’ likely skills and abilities, or their likelihood to switch jobs, for example. Thanks to the three v’s, big data can give you a serious advantage over the competition that standard analytics just can’t provide.

Let’s take a look at how the three v’s of big data apply to the recruiting process:

The Three V’s of Big Data Recruiting

Volume

In big data recruiting, a lot of variables are considered when it comes to finding the perfect candidate. Thousands upon thousands of bytes of data are crunched when recruiters look for someone with the right skill set.

For example, big data applied to recruiting for tech positions would look at a candidate’s publicly offered source code, their LinkedIn profile and other social media channels, the websites they frequent, and even the way they talk about technology.

All of these data points — way more than the average recruiter can look up in a Google search — would make up the information presented about a particular candidate. By evaluating a large volume of material, recruiters and HR managers can receive a clearer picture of the best candidates for their open positions.

Velocity

As we mentioned in the introduction, the traditional hiring process can take anywhere from 29 to 43 days. And this is only the average — clearly some hiring processes to fill certain positions can take months.

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Big data recruiting makes the hiring process faster because of the velocity at which it recognizes and evaluates information. Big data recruiting can jump between a candidate’s Twitter stream and work portfolio, and quickly present a comprehensive picture of the candidate.

This helps recruiters and HR managers cut down on the time it takes to research top candidates, because suddenly all the relevant information is right at hand. This means spending more time personally connecting with candidates and less time wasted pursuing the wrong people.

Variety

One of the best reasons to use big data recruiting actually relates to variety. When it comes to big data, one of the attributes that sets it apart from traditional analytics is the ability to combine information from a variety of different sources.

For instance, big data can look at text and video files and combine the information together. When recruiting for technical positions, big data can look at a candidate’s open source code and their social media channels and combine this information into a meaningful whole.

What this ultimately equals, however, is a larger variety of talented candidates making it into your talent pipeline. For instance, many companies put too much stock on the traditional markers of success. Companies that feel like they should only consider a candidate coming from an Ivy League school or a brand-name company are needlessly discriminating against great candidates.

Education and work history can be highly valuable information, but those attributes are not the only signposts of success, and many candidates who don’t fit into these neat little boxes would actually make fantastic hires for your company.

Dr. Vivienne Ming, Chief Scientist of Gild, has conducted research on just such biases using big data techniques, and found little evidence that school and previous company affiliation were primary correlates to candidate success. “When you look at top performers at companies it really comes down to intrinsic versus extrinsic motivators,” explains Ming. “Intrinsic motivators include - passion, ownership, and a kinship for colleagues. These are the predictors of success.”

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Question 3: Why Use Big Data Recruiting?

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One of the quickest ways to answer this question is to point to the amount of information constantly proliferating online. It’s impossible to use the same methods of recruiting you did 10 or even just five years ago. But more and more information to sift through means more and more time wasted during the hiring process, especially if the candidate you’re researching turns out to be a dud.

It’s become a real pain point for recruiters who just ten years ago were constantly searching for candidates and are now inundated with too many prospects. There are more than 238 million members of LinkedIn alone, meaning recruiters literally have access to hundreds of millions of resumes at their fingertips. It’s easy to feel crushed by the weight of all this data.

Here’s a staggering example of the information overload in cyberspace: Back in 2010, then Google CEO Eric Schmidt was speaking at the Techonomy Conference in Lake Tahoe. While speaking, he dropped an amazing statistic that gives insight into why big data recruiting is needed now more than ever. According to Schmidt, we’re now creating as much information every two days as we did from the dawn of civilization until 2003: approximately five exabytes of data every other day.

Big data recruiting is needed to sort through all this information to help recruiters and hiring managers make more informed decisions. Plus, it’s not like the traditional hiring processes are very effective or cost-saving.

Payroll is actually the largest expense for most companies, which should come as little surprise when you realize there are more than 160 million workers in the U.S. alone. In fact, payroll comprises 40 percent or more of revenue for most businesses. This might explain why making a bad hire can set the average company back $50,000 or more.

Few companies, even large enterprises, can afford the cost of employee turnover and bad cultural fit. Imagine, however, that by using big data recruiting you could spend the same amount on hiring, but cut down on the rate of bad hires by 50 percent.

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According to Beth Axelrod, co-author of the book The War For Talent and Senior Vice President of Human Resources at eBay, big data will help companies address problems with the traditional recruiting process. “What we’ll find is a reinvention of some very traditional processes in companies and a rethinking of how HR gets done,” Axelrod told Forbes.

It’s All About The MoneyballWhether you’re a fan of sports, baseball, or Brad Pitt, the odds are high you’ve heard the phrase “moneyball” before. The term originated in the book Moneyball: The Art of Winning an Unfair Game, a nonfiction bestseller by author Michael Lewis about the Oakland Athletics baseball team and their unique way of winning.

Thanks to general manager Billy Beane and assistant Paul DePodesta, the team threw out the old recruiting rules of baseball and still managed to find outstanding players. They did so by looking outside the common wisdom in baseball circles and looking closely at the numbers instead. For instance, they found on-base percentage and slugging percentage was a better indicator of offensive success than batting average, long held as the gold standard when recruiting players.

What does this have to do with recruiting the best talent for your organization? The reason the Oakland A’s embraced the moneyball concept is, unlike giant teams like the New York Yankees, Oakland had a limited budget. They needed to find wonderful players, but they couldn’t afford the highest priced talent.

Moneyball helped the Oakland A’s get creative about finding talent by using data to redefine what players would be the most successful. This is similar to the way big data recruiting works. Instead of just looking at a candidate’s work history or university, big data recruiting spiders through heaps of data to give you a more complete picture of the candidate.

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The result is that, like the Oakland A’s, you can target talent with a lower price tag. For instance, a Harvard educated candidate just leaving a job at Google is going to be a highly sought after commodity, like a star pitcher for a big market baseball team.

This candidate is going to be chased by dozens, if not hundreds, of companies. They see the credentials on this person’s resume and automatically assume the candidate will be a great addition to the company, regardless of personality or actual skills.

Big data recruiting follows the moneyball principle by helping you look beyond these markers and focus in on the actual skills and abilities a candidate possesses.

For instance, the candidate right for your position might have attended a community college or no college at all. They might not have a brand name former employer. However, this person has the same skills and abilities as the Harvard superstar without being chased by a pack of hungry recruiters. This means you don’t have to offer a sky-high salary and excessive perks just to stand out from the pack.

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Question 4: How Does Big Data Find Candidates?

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Now that you know what big data is and why more companies are embracing the big data revolution, just how exactly can big data help you find the best candidates?

Using the three v’s previously discussed (variety, velocity, and volume), big data recruiting looks at candidates from several angles. Instead of just evaluating the information on a candidate’s resume, big data recruiting goes out into the Internet wilderness on an exploratory hunt and brings back a wealth of information on the candidate.

Examples of Sources Big Data Evaluates Using a developer as an example, here are just a couple of the things big data recruiting evaluates when searching for information on a candidate:

● A candidate’s social media profiles. Special emphasis is put on candidates who demonstrate their expertise on social media channels like Facebook and Twitter by sharing advice, thought leadership, and interesting industry insights.

Candidates’ contributions to question-and-answer sites like Quora and Stack Overflow are evaluated alongside more traditional social media recruiting destinations. This gives employers a better idea of how a candidate thinks about and uses technology, along with their social IQ.

● A candidate’s resume information. Obviously the traditional resume still exists for a reason. In addition to tech-heavy evaluations, big data recruiting can look at a candidate’s more traditional credentials.

We know the traditional markers for success — like a top university degree or sterling work history — don’t always translate into a first-rate employee. However, it’s still necessary for employers to know and understand a candidate’s background before engaging with them in the hiring process.

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Question 5: How Does Big Data Bring More Context To Resumes?

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By analyzing candidate data and interpreting the information uncovered to understand the true skills and interests of an individual, big data recruiting can actually help your organization find the best undercover talent.

Through big data recruiting you might find a candidate who skipped college, but who performs at a higher level than even an Ivy-League grad. Even if a candidate doesn’t have a flashy employer company brand-name college on his or her resume, the person may still be a great hire.

That’s not to say that MIT and Stanford engineers that worked at Google aren’t desirable professionals. They’re most likely highly skilled. But, what happens when the 12 people that fit those criteria are happily employed?

Big data can help companies avoid the cookie-cutter and ridiculously, almost unattainable in-demand candidates in order to find someone who took a different path to success.

It’s not that big data recruiting encourages ignoring the traditional resume, but it can help companies look beyond those static words on a page. Big data looks for real-world examples of a candidate’s concrete skills, presenting employers with a better view of what a candidate can actually do.

Bringing ValueThis ability to bring more context to a traditional resume creates value in two distinct ways:

1. The first way ties, once again, into the Moneyball principle. Instead of competing with giant companies with large budgets, you pursue talent that may be more affordable by looking beyond the traditional markers of candidate quality (e.g. where they went to school or worked).

2. The second way is by allowing companies to find candidates who are uniquely qualified for a given role. Big data will allow you to pinpoint the skills and interests of someone, so you know they’re an especially good match for your open role.

It’s not that the resume is broken, it’s that big data recruiting can help you see the traditional resume in new ways.

“People that go to top schools, but are extrinsically motivated, are predicted to be poor employees. They may have attended a top school and got the job they wanted, but they don’t have a sense of passion for the work they’re doing. Their goals tend to be to get promotions, engage in politics, and work the system. These are the things they care about, which is why they cared enough to work incredibly hard to get into a school like Harvard even though they didn’t care about the work they were doing.”

~Dr. Vivienne Ming, Chief Scientist, Gild, Inc.

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Question 6: How Does Big Data Help You Engage With Candidates?

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Big data recruiting isn’t just a smart tactic for finding excellent candidates before your competitors, it also can help you engage more personally and more fruitfully with top talent.

Big data recruiting can help with candidate engagement in two ways:1. Using big data and analytics can help you better understand the kind of candidates you need. It can help you break down barriers and better understand which candidates will be high performers and which candidates just look good on paper.

2. By providing a multitude of information, big data recruiting can help employers get a more personal feel for candidates earlier in the hiring process. With the proliferation of social media and personal blogs, you can get to know a candidate’s personality before the interview. This can allow you to skip right to candidates who are good fit for your organizational culture.

Now let’s take a closer look at these two ways big data recruiting can help you connect and engage with top talent.

Find Better CandidatesRecruiters often make the mistake of falling back on conventional wisdom when it comes to hiring. There are no fingers to point or blame to be assigned because, just like in baseball, this common sense wisdom has helped recruiters find excellent candidates for years. Unfortunately, a lot what we believe makes up the ideal candidate is often wrong.

For example, many recruiters and hiring managers will shy away from a candidate who has job hopped in the past. But data shows job hopping does not necessarily add up to a pattern, and job hopping candidates are actually no more likely to take off for greener pastures than candidates with longer stays in former positions.

Bottom line: using big data in the recruiting process illuminates the true measures of success.

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A first-rate developer might not have gone to a top-tier school, graduated with honors, or previously worked for an impressive employer. But if this person has the skills, personality and motivators necessary to add real value to your organization, he or she is certainly worth more than a less skilled candidate with highly impressive credentials.

By focusing on skills instead of traditional markers for success, big data recruiting can help you drop your preconceived notions and hire the best candidates.

Engage More PersonallyCompany culture fit might actually be the most essential ingredient to hiring someone who is high-potential for your organization. In fact, 46 percent of small business new hires fail within the first 18 months, and 89 percent of the time this is because of a poor company culture fit. Clearly, you ignore company culture fit at your own peril when looking for candidates.

Big data can help by making it easier to get a more personal and complete view of a candidate before the individual ever interviews. This helps you save time in the hiring process, and weed out candidates who aren’t a good fit for the company.

How does big data recruiting allow more personal engagement? Once again, it comes down to volume, variety, and velocity. In today’s social media-obsessed world, there are more social channels than ever before where your candidate spends time. These social media networks are being updated at a breakneck speed, making it hard for any individual recruiter to discover and read a candidate’s output.

For instance, since the dawn of Twitter back in 2009 there have been approximately 163 billion tweets sent out on the microblogging service. In 2012 625,000 people people joined the Google + network every day. On Facebook, users posts an average of 36 times per month and 23 percent check their account five times a day or more, exposing them to over 1500 pieces of content on each login.

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It would be impossible to manually sort through all this data, yet the contributions your candidate makes to these social spheres might just tell you a tremendous amount about whether this person would sink or swim in your organization.

This is why most recruiters are looking at social media profiles and digital footprints before ever meeting a candidate for a face-to-face interview. One-fifth of HR managers said a candidate’s social media profile helped them land a position — while another 43 percent found negative information and passed on a candidate entirely, saving them from hiring someone who might not have the discretion necessary for their organization.

Thanks to the three v’s, big data recruiting can do the work for recruiters and present a more fully-rounded picture of a candidate. This way recruiters can get a feel for the candidate’s personality, professionalism, and concrete skills before ever picking up the phone to connect.

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Question 7: What Industries Should Use Big Data Recruiting?

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Big data recruiting can work across a wide spectrum of companies, positions, and industries. Obviously, however, some industries need the power of big data recruiting a little bit more than others. This is especially true of the technology and startup sectors currently waging an all-out war in order to find the best talent.

The War For Tech TalentIn the tech industry, whether you’re running an established company or a fledgling startup, the one reality you share is that finding talent is a battlefield. The competition to find the top tech talent is fierce, and only a few will manage to be victorious.

This is mostly due to the demand for tech talent vastly outpacing the supply. According to the U.S. Bureau of Labor Statistics, technical hiring will more than double the job growth of every other industry by 2016.

A study by Bersin & Associates showed that more than 50 percent of the business leaders surveyed named talent shortages as a key business challenge facing their organization. Not hard to believe when you consider the unemployment rate for IT professionals remains in the low single digits, even while overall unemployment remains high.

Big data recruiting can help companies look for talent in new places, helping you undercut your competitors and still end up with superior tech talent. You can win the war for talent by forging your own path.

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Keeping Costs DownFighting a war for talent can come with a hefty price tag. Because talent in the tech and startup spaces is highly sought after, hiring the best people can break the bank. For small companies, startups, and even big businesses on a budget this can be a tough pill to swallow. According to information from Gartner, IT spending is estimated to run about $3.7 trillion in 2013 alone.

By using big data recruiting, however, you might just find a diamond in the rough no one else has noticed yet and for a fraction of the cost. Perhaps the candidate who skipped college but learned to code on their own, actually has a much better skill set, along with the right personality to thrive at your company.

By looking at candidates who aren’t being aggressively recruited by industry giants, you can find hidden talent with salary requirements that fit your budget.

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Question 8: Is Big Data Recruiting A Fad or Here To Stay?

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Right now “big data” is a buzzword being thrown around in many offices around the world. But will big data become a dated trend, like mailing in a paper resume or advertising your jobs in the newspaper “help wanted” section? Should your company really invest in a new technology that could be here today but gone tomorrow? How do you know big data recruiting is here to stay?

One reason is that big data just keeps getting bigger. According to the Gartner Group, the market for big data and big data technology will continue to grow over time. By 2015, big data is expected to generate $3.7 trillion in products and services. And the need for employees who can analyze and work with big data techniques will also grow by leaps and bounds. Big data is expected to add 4.4 million jobs into the market by 2015, as well.

Big Data Recruiting is More Than a Passing Fad “Ok, I’m convinced big data is here to stay,” you might be saying. “But what about big data recruiting. That could still be a fad.”

Sure, it could be, but certainly with the overall growth of big data in our economy, businesses, and everyday life, this seems unlikely. Still, let’s look at a few reasons why big data recruiting isn’t going the way of the bedazzled jean jacket:

● The Economy: With high unemployment, the candidate pool is deeper than ever. This means more people applying for open positions and more resumes for overworked recruiters and HR managers to sort through. Big data recruiting can help ease the burden of a heavy workload and still allow recruiters to find the best people.

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● Data Proliferation: As mentioned there are more data available now than ever before, and most of it is available to public consumption. For instance, if you were looking to recruit a researcher you might soon be suffering from information overload, because more research is being published and placed publically online.

Big data recruiting can help index and predict the skills of these researchers by looking through thousands or millions of bytes of research data and delivering only the best research candidates based on the wealth of information it finds.

Don’t forget that social media is also everywhere, and it seems like every day a new social media platform debuts. Just look at the shocking success of visual social network Pinterest and you’ll see it’s impossible to tell what social channel will be the next big thing.

With 92 percent of recruiters using social media to source candidates, it makes sense to turn to big data recruiting for help. It can analyze dozens of social media channels and present you with a more complete picture of your candidate, without the need to spend hours scrolling through a Twitter feed.

● The War For Talent: We’ve mentioned this before, but the battle rages on for the best talent. The skills gap means even though the candidate pool is large, when it comes to the skills you need, it’s still far too shallow to make finding the right person a snap. Big data recruiting helps smart companies and recruiters get a leg up on the competition when it comes to talent selection.

● Innovation: When an innovative new technology comes along with the potential to deliver ROI to companies, it’s rarely tossed aside. The technology soon fading into the trendy past is the same tech that can’t deliver real, sustaining value to companies. If big data recruiting can present real value and innovation for the companies using it to find great talent, the market will only grow, not shrink.

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Question 9: What Is The Future of Big Data?

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Social media. Business analytics. Mobile technology. According to IBM, 90 percent of the data in the world was created in just the last two years or so. With technology moving forward every second of every day, the future of big data looks bright.

Will your company be able to beat the war for talent using big data? Will you be able to cut down on hiring process inefficiencies and save your company’s bottom line? This all depends on how you deploy big data recruiting and what goals you set for yourself at the beginning of your hiring process.

Big data recruiting is a tool like any other without any guarantee of success. Still, there are success stories to be had when it comes to big data recruiting. One example actually involves a position we hired for at Gild. When our company was looking for a developer, we came across Jade Dominguez.

Mr. Dominguez might not have popped up if we hadn’t been searching and analyzing public data. After all, he had skipped college and hadn’t previously been employed by a big-name employer. He didn’t meet the markers of success most companies use when recruiting top talent. Yet, he did have something all companies need: exceptional skills and abilities.

Thanks to his high score provided by our tech recruiting software, Gild Source, we didn’t miss a diamond in the rough like Jade just because he didn’t fit into our preconceived notions of what a “good” candidate looks like on paper. Because of this, we were able to find a top developer other companies were ignoring.

Success using big data follows if you put in time and effort to use this new recruiting advancement. With more companies in need of next-gen hiring solutions, however, it’s likely the future of big data recruiting looks bright.

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Conclusion

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On the surface, big data recruiting appears complicated and without a clear path to success. But with a little knowledge of how it works, any company can use big data recruiting to its advantage.

There’s a battle for talent out there, and you can’t afford to get left behind. The best and brightest candidates are being scooped up left and right by your competitors. So what’s the solution? Throw more time and money into the traditional hiring process, hoping you’ll get the results you need?

No, the answer is to use the information that’s available to you, so you can be smarter in your recruiting efforts. Don’t fight with your competitors over same shallow candidate pool. Expand your definition of who the ‘right’ candidate is and, use big data recruiting to find the talent you need to keep your company growing and innovating.

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Glossary

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Byte A byte is the basic unit of information storage size. A single character in text is a byte. Kilo, mega, giga, tera, exa, petabyte etc. are all 1,000 fold more bytes than the previous number.

Hadoop Software library framework by Apache that allows for the distributed processing of large data sets across clusters of computers using simple programming models.

Mongo Mongo is an open source, document-oriented database that is part of the NoSQL family of databases. It is written in C++. It makes the integration of data in certain types of applications easier and faster.

Structured Data Structured data refers to data that is identifiable because it is organized in a structure. An example this is an excel spreadsheet. With its columns and rows, a spreadsheet is organized in a specific way and is considered structured.

Unstructured Data The term unstructured data refers to any data that has no identifiable structure. For example, a book would be considered unstructured data because to a machine, there’s no organization to the data (i.e. the words). You would need to create an algorithm that explicitly tells the machine how to read the book’s text.

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To Learn Moreemail info@gild.com call (800) 664-2366 visit www.gild.com

Tech recruiting has been begging for innovation. That’s why Gild is here.Bringing meritocracy to tech hiring, Gild’s recruiting solutions harness the power of data to liberate you from the challenges of finding developers.

About Gild Source Gild Source can dramatically improve how you hire developers. Gild Source is an advanced recruiting platform that helps you solve the challenge of how to effectively recruit developers, by enabling you to easily find and target candidates you know are good.

Using patent-pending technology to analyze programmers’ actual code and professional contributions from open source communities and Q&A sites, Gild has profiled, scored, and ranked millions of developers. Gild’s scores and rankings provide you with an instant assessment of a developer’s skills and experience.

With Gild Source:

• Search for developers using multiple criteria like coding skills, title, or location

• Access comprehensive profiles of developers

• Email candidates directly

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