What is Data Science, how is it used?
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Social Business vs. Social Media: Take Altimeter’s 2012 Survey

Social Business vs. Social Media: Take Altimeter’s 2012 Survey | What is Data Science, how is it used? | Scoop.it

Businesses may be seen as having a “successful” social strategy by virtue of citations in case studies and speaking at conferences. But, by far, the best metric of success is concrete examples of how the organization creates business value via social technologies across multiple departments and dimensions of their business.

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What is Data Science, how is it used?
Can I use data science to make a difference in my company (HECK YES)
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Data Science is real » Great Lists to Follow

Data Science is real » Great Lists to Follow | What is Data Science, how is it used? | Scoop.it
Carla Gentry CSPO's insight:

There are some great lists out there to follow for Data Science and Technology – Check out a few I have been honored to be listed on – Please feel free to check out everyone on these lists, some really great folks out there!

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How Predictive Technology is Changing Advertising

How Predictive Technology is Changing Advertising | What is Data Science, how is it used? | Scoop.it
Advertisers have done everything they can to find out more about their audience so they can make their ads more effective. They have used online technology like cookies to try to predict what audience members will want, such as by looking at what other websites they have visited.
Carla Gentry CSPO's insight:
Advertisers have done everything they can to find out more about their audience so they can make their ads more effective. They have used online technology like cookies to try to predict what audience members will want, such as by looking at what other websites they have visited. Read more at http://www.business2community.com/marketing/predictive-technology-changing-advertising-01773066#3ZWFEBvFpxoUW7EP.99
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» Are All Predictive Talent Acquisition Platforms Created Equally?

» Are All Predictive Talent Acquisition Platforms Created Equally? | What is Data Science, how is it used? | Scoop.it
We use predictive analytics to reduce employee attrition & increase performance for high volume roles like Call Centers, Insurance Agents, Sales Reps, Tellers, Sales Engineers, Personal Bankers and the like.
Carla Gentry CSPO's insight:
Detailed predictions require a level of interaction with your company’s data (HR data plus Line of Business Data) to determine what attributes predict a top performer for your company vs. another company. These attributes can be very different company and by company.
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Managing Big Data’s Big Risks

Managing Big Data’s Big Risks | What is Data Science, how is it used? | Scoop.it
The good news is that the hazards of Big Data can be largely avoided. But they won’t be unless we zealously protect people’s privacy, detect and correct unfairness, use algorithmic recommendations prudently, and maintain a rigorous understanding of algorithms’ inner workings and the data that informs their decisions.
Carla Gentry CSPO's insight:
The good news is that the hazards of Big Data can be largely avoided. But they won’t be unless we zealously protect people’s privacy, detect and correct unfairness, use algorithmic recommendations prudently, and maintain a rigorous understanding of algorithms’ inner workings and the data that informs their decisions.
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» The Beginner’s Guide to Predictive Workforce Analytics

» The Beginner’s Guide to Predictive Workforce Analytics | What is Data Science, how is it used? | Scoop.it
We use predictive analytics to reduce employee attrition & increase performance for high volume roles like Call Centers, Insurance Agents, Sales Reps, Tellers, Sales Engineers, Personal Bankers and the like.
Carla Gentry CSPO's insight:
Human Resources Feels Pressure to Begin Using Predictive Analytics
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SAPVoice: Make Sure Your Hiring Algorithms Are Legal: Four Machine Learning Questions To Ask

SAPVoice: Make Sure Your Hiring Algorithms Are Legal: Four Machine Learning Questions To Ask | What is Data Science, how is it used? | Scoop.it
“We’re seeing machine learning going outside HR into the line-of-business targeting higher-volume transaction areas, such as finding out what kind of field reps generate more sales or which drivers have more accidents or call center performance,” said Roberts. “The machine learns when you feed the outcomes back into it over time.”
Carla Gentry CSPO's insight:
“We’re seeing machine learning going outside HR into the line-of-business targeting higher-volume transaction areas, such as finding out what kind of field reps generate more sales or which drivers have more accidents or call center performance,” said Roberts. “The machine learns when you feed the outcomes back into it over time.”
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» Winning Roles™ Predictions

Quotes from Industry Thought Leaders On Talent Analytics’ Winning Roles Solution:
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Quotes from Industry Thought Leaders On Talent Analytics’ Winning Roles Solution:
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» Understanding Your Most Important Asset

We use predictive analytics to reduce employee attrition & increase performance for high volume roles like Call Centers, Insurance Agents, Sales Reps, Tellers, Sales Engineers, Personal Bankers and the like.
Carla Gentry CSPO's insight:
Business Results (not HR Results) We predict how candidates will do their job, pre-hire, like will they pass an exam, achieve sales quota, last in a role for at least a year, make devastating errors, be able to sell solutions vs. products . .
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Human Resource Management Meets Predictive Analytics -

Human Resource Management Meets Predictive Analytics - | What is Data Science, how is it used? | Scoop.it
Where do you see the biggest changes in AI in HR over the next 5 to 10 years?
Carla Gentry CSPO's insight:
Where do you see the biggest changes in AI in HR over the next 5 to 10 years?
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Be a Data Scientist in 8 steps!

Data science is the new thing! How to be a data scientist? See here. This was originally was written by the team behind DataCamp, - the online interactive lea…
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Closing the Data-Driven Enterprise Adoption Gap

Closing the Data-Driven Enterprise Adoption Gap | What is Data Science, how is it used? | Scoop.it
To be successful in today’s marketplace, champions of data within the organization must be transformed through the adoption of BI tools to derive faster insight for themselves and their teams. Decisions should be guided equally by insight, delivered at the right time and place, in context, and embedded directly inside the applications they already work with every day. It’s precisely these distinct but important technology approaches that can deliver insight wherever you are and in the time you need it, ultimately improving your bottom line and, more broadly, making the world a better place. Plus, no one wants to sift through endless amounts of data to find the “needle in the haystack” insights.
Carla Gentry CSPO's insight:

Closing the BI adoption gap marks the greatest current challenge to businesses around the world. Looking back months or years from now, you may realize that adopting a BI tool for your organization in 2014 marked the moment your organization came to life. - See more at: http://data-informed.com/closing-data-driven-enterprise-adoption-gap/#sthash.VfUxMS9E.dpuf

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Rivo's Thought Leader Programme Strengthens Big Data and Sustainability Expertise on Environmental XPRT

Rivo's Thought Leader Programme Strengthens Big Data and Sustainability Expertise on Environmental XPRT | What is Data Science, how is it used? | Scoop.it
Helping businesses leverage and understand Big Data and Analytics
Carla Gentry is one of the most respected names in data mining and analytics, named one of Information Week’s 10 IT Leaders to follow on Twitter and Business Insider’s 25th Most Influential Tech Woman of 2014.  Most recently she spoke for the IBM Insight 2014 event in Las Vegas. Behind the scenes Carla is working closely with the Rivo Lab on their Analytics solution helping to provide Advanced Analytical capabilities to Rivo’s customer base by bridging the chasm between technology and business needs.
Carla Gentry CSPO's insight:

Rivo, the market leading cloud risk management platform for leading brands around the world has announced the recruitment of three world renowned experts in Data Analytics and Sustainability Reporting to an elite panel of Rivo Thought Leaders. The move by Rivo demonstrates how the global software player is offering value-added content and expertise to its customers.

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How fit is that Fitbit? - The Berkeley Science Review

How fit is that Fitbit? - The Berkeley Science Review | What is Data Science, how is it used? | Scoop.it
Technology used to be something external, we traveled to the office to use it – you sat  at your computer. Then technology became something we carried around – our cellphones, our laptops. Wearable tech used to be something of sci-fi and comic books – but now it is the norm. Among the most popular form …

Via JP DOUMENG
Carla Gentry CSPO's insight:

Fitbit’s mantra is to make fitness part of your daily routine, allowing you to track your own data and use social media to “challenge” friends to meet their exercise goals. Fitbit has tapped into our need to be constantly connected by giving you live data – on your wrist – of how much you have walked each day. When you meet your daily goal, the Fitbit lets you know with a strong vibrating buzz. Not knowing exactly when that buzz is coming is like the variable reinforcement schedule that makes gambling so powerful.

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The one critical skill many data scientists are missing

The one critical skill many data scientists are missing | What is Data Science, how is it used? | Scoop.it
Data science is a new career for the age of Big Data (whatever that means this week), but you can see that it’s at the intersection of qualities many people have been developing for years. As a graduate of the Science to Data Science (S2DS) summer school, I know people who have come to data science from a wide variety of backgrounds and found a new niche for themselves.
Carla Gentry CSPO's insight:
When I started to learn about data science and consider it as a career choice, there was a diagram that I came across regularly and still come across today, in articles and even text books aimed at introducing and educating the world about the “sexiest job of the 21st century.” First created by Drew Conway, it illustrates the three broad skill groups you need to be a data scientist.
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Employee Life Time Value and Cost Modeling - Predictive Analytics Times - predictive analytics & data science news

Employee Life Time Value and Cost Modeling - Predictive Analytics Times - predictive analytics & data science news | What is Data Science, how is it used? | Scoop.it
Understanding the Most Expensive Asset Practically every business shares the same biggest cost – employees. This makes sense – even in this age of robots and computers, human talent is behind everything that a company does. People are the source of innovation, growth, and competitive edge for every company. Given this importance, it’s a bit …
Carla Gentry CSPO's insight:
We address employee cost, performance, attrition and lifetime value to bring the practice of Human Resources into the information age. Only with these metrics will the actual value and dynamics of our "Human Resources" be known.
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» How Do Algorithms Reduce Bias During the Talent Acquisition Process?

» How Do Algorithms Reduce Bias During the Talent Acquisition Process? | What is Data Science, how is it used? | Scoop.it
First we need to remember that the hiring process is a process of discrimination – though not in the way we normally think of discrimination. The single goal during the interview process is to discriminate between someone who can do the job vs. someone who can’t.  We should only be paying attention to fulfilling this mandate for our companies.The problem is that we are human and we can’t avoid many other distracting factors even if we try desperately to remind ourselves.Unless they’ve been told otherwise, algorithms don’t care about gender or color or disability. Algorithms are focused on finding candidates that are proven to deliver performance for the company (which is the only reason to hire an employee anyway)
Carla Gentry CSPO's insight:
So – one way analytics can help to humanize the process is to scrub bias, be transparent and remove mystery factors from the interview process.
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Data science is creating a tidal wave of opportunity for women to get into executive leadership

Data science is creating a tidal wave of opportunity for women to get into executive leadership | What is Data Science, how is it used? | Scoop.it
Women now make up 40 percent of graduates with degrees in statistics — that’s a good indicator for women in an environment increasingly obsessed with data. As we’ve seen with most technologies, the code is eventually abstracted away from the user and the dirty work of putting the tech to use in real business situations begins. Women no longer need to be expert coders to get in on the data science game.
Carla Gentry CSPO's insight:
Women now make up 40 percent of graduates with degrees in statistics — that’s a good indicator for women in an environment increasingly obsessed with data. As we’ve seen with most technologies, the code is eventually abstracted away from the user and the dirty work of putting the tech to use in real business situations begins. Women no longer need to be expert coders to get in on the data science game.
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Black Duck Software's curator insight, February 6, 10:35 AM
Interesting developments in #datascience here for women in executive leadership.
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Will You Graduate? Ask Big Data

Will You Graduate? Ask Big Data | What is Data Science, how is it used? | Scoop.it
The analysis showed that fewer than 10 percent of nursing students with a C in math graduated, compared with about 80 percent of students with at least a B+. Algebra and statistics, it seems, were providing an essential foundation for later classes in biology, microbiology, physiology and pharmacology.
Carla Gentry CSPO's insight:
The analysis showed that fewer than 10 percent of nursing students with a C in math graduated, compared with about 80 percent of students with at least a B+. Algebra and statistics, it seems, were providing an essential foundation for later classes in biology, microbiology, physiology and pharmacology.
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» Why Talent Analytics?

» Why Talent Analytics? | What is Data Science, how is it used? | Scoop.it
We predict how candidates will do their job, pre-hire, like will they pass an exam, achieve sales quota, last in a role for at least a year, make devastating errors, be able to sell solutions vs. products . .
Carla Gentry CSPO's insight:
We predict how candidates will do their job, pre-hire, like will they pass an exam, achieve sales quota, last in a role for at least a year, make devastating errors, be able to sell solutions vs. products . .
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Don’t trust that algorithm

Don’t trust that algorithm | What is Data Science, how is it used? | Scoop.it
Cathy O'Neil, Ph.D. '99, talks about her new book "Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy” and the quiet dangers of big data.
Carla Gentry CSPO's insight:
Interesting read!
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» Case Study: Solving Call Center Employee Attrition

» Case Study: Solving Call Center Employee Attrition | What is Data Science, how is it used? | Scoop.it
We use predictive analytics to reduce employee attrition & increase performance for high volume roles like Call Centers, Insurance Agents, Sales Reps, Tellers, Sales Engineers, Personal Bankers and the like.
Carla Gentry CSPO's insight:
Data Science Meets the WorkForce
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» What is HR’s Best Predictive Project?

» What is HR’s Best Predictive Project? | What is Data Science, how is it used? | Scoop.it
We use predictive analytics to reduce employee attrition & increase performance for high volume roles like Call Centers, Insurance Agents, Sales Reps, Tellers, Sales Engineers, Personal Bankers and the like.
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@data_nerd: A Badge of Courage

@data_nerd: A Badge of Courage | What is Data Science, how is it used? | Scoop.it
A good data scientist is also inquisitive – explore, ask questions, question existing assumptions and processes, and always approach data with “what if” analysis. With an inquisitive approach, armed with data and analytic results, a top-tier data scientist can inform and recommend techniques across a company’s leadership.
Carla Gentry CSPO's insight:

For more on what it means to be a great data scientist, as well as tips on best management style for data scientists, check out my article “Being a Data Scientist.”

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Best solution to a problem: data science versus statistical paradigm

Best solution to a problem: data science versus statistical paradigm | What is Data Science, how is it used? | Scoop.it
In the end, there is no such thing as a real data scientist or statistician. It's all about a personal feeling reflecting your career. Some statisticians are more data scientist than me. You can say the same thing about any profession.
Carla Gentry CSPO's insight:

The definition of 'best' depends on which school you follow. Data science and classic statistical science are at the opposite ends of the spectrum. So let's clarify what 'best solution' means in these two opposite contexts:

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Big Data, IOT and Security - OH MY!

Big Data, IOT and Security - OH MY! | What is Data Science, how is it used? | Scoop.it
While we aren’t exactly “following the yellow brick road” these days, you may be feeling a bit like Dorothy from the “Wizard of Oz” when it comes to these topics. No my friend, you aren’t in Kansas anymore!
Carla Gentry CSPO's insight:
Let’s talk about security and data breaches – Now you may be thinking I’m in analytics or data science why should I be concerned with security? Let’s take a look at several breaches that have made the headlines lately.
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Dealing with Supply Chain Big Data

Dealing with Supply Chain Big Data | What is Data Science, how is it used? | Scoop.it
Many supply chain applications based on relational databases will chug along just fine for some time to come.  However, as supply chains get bigger, more complex, and demand faster responses times, expect to see NoSQL databases and complex event processing gaining more than a foothold too.
Carla Gentry CSPO's insight:

With the three V’s stretching conventional data management approaches to the limit, a number of alternatives have emerged – including Hadoop.  Two categories that are likely to find their way into supply chain applications include:

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