Data Nerd's Corner
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Master Data Management or Data Governance? Yes, Please

Master Data Management or Data Governance? Yes, Please | Data Nerd's Corner | Scoop.it
The focused effort to manage master data coupled with an organization s ability to leverage sources of big data, especially social networks, will result in optimized business processes and measurable business performance improvements...
Carla Gentry CSPO's insight:

An organization’s ability to identify, access, integrate and synchronize data from multiple internal and external sources and then effectively govern that data over time using processes and policies is crucial. Collectively, the focused effort to manage master data coupled with an organization’s ability to leverage sources of big data, especially social networks, will result in optimized business processes and measurable business performance improvements.

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Data Nerd's Corner
Everything you wanted to know about predictive analytics
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Women in Data

Women in Data | Data Nerd's Corner | Scoop.it
The gender gap in tech is shrinking. Women are still an underrepresented minority in the disciplines of science, technology, engineering, and math (STEM), but women in data and technology are no longer outliers or anomalies. For this book, author and data warrior Cornelia Lévy-Bencheton interviewed 15 women in data to learn how they achieved their current level of success, what motivated them to get there, and their views about opportunities for women.
Carla Gentry CSPO's insight:

Introducing women to STEM is now a nationwide crusade, but advancing the idea that gender diversity fuels creativity, innovation, and economic growth is still a challenge. The stories in this book are inspiring, revealing insights that will widen the path for even more women in tech.

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The Talent Analytics Workflow Needs Non-Analytical Talent Too

The Talent Analytics Workflow Needs Non-Analytical Talent Too | Data Nerd's Corner | Scoop.it

The good news is that the skills, competencies, and experiences that make many people successful in traditional, nonanalytic HR roles are often of great value to the success of talent analytics projects. HR business partners have insight into the talent challenges of the business and are often good brokers between the needs of the line and HR’s ability to meet those needs. Many could expertly fill the liaison role of a predictive analytics project. Analytics Center of Excellence staff are experts in their respective domains, often knowing both where data is that could support talent analytics projects and how to interpret it, thus they can offer help in presenting data to internal clients.

Carla Gentry CSPO's insight:
When building analytics capabilities, HR departments should take advantage of the skills they already possess, even if the connection to analytics isn’t always obvious rather than trying to force all current HR employees into predictive analytics even if they have no interest.
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What's next in Business Analytics?

What's next in Business Analytics? | Data Nerd's Corner | Scoop.it

What's next in Business Analytics? By Rich Clayton, VP of Business Analytics & Big Data Product Group, Oracle -

Carla Gentry CSPO's insight:
We’re at an interesting moment of technological advancement today. It feels like there is barely time to digest before something new is upon us!
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Employee Life Time Value and Cost Modeling - Part 2 - Predictive Analytics Times - predictive analytics & data science news

Employee Life Time Value and Cost Modeling - Part 2 - Predictive Analytics Times - predictive analytics & data science news | Data Nerd's Corner | Scoop.it

These costs are surprisingly consistent. Some items, like drug tests, have fixed costs. HR works hard to keep the hiring funnel efficient and full. There is usually a fixed set of job fairs, advertising and job board usage per year.


Carla Gentry CSPO's insight:
All of these costs get aggregated and averaged for the role, and applied to the first day of a new hire’s job. It is not unusual for this acquisition cost to be quite high.
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» Data Science Shows the Business Impact of Training and Development Over Time

» Data Science Shows the Business Impact of Training and Development Over Time | Data Nerd's Corner | Scoop.it

Data Science Studies: Do Development Programs Help Increase Performance Over Time?

We recently completed two analytics studies quantitatively analyzing sales rep. performance. Among other goals, we analyzed sales rep. performance over time – both before and after training is completed. We documented their sales performance as new hires, during training, and finally after they reached full self-sufficiency in their role."

Carla Gentry CSPO's insight:
Each business measured real sales performance (not performance ratings) over time, during and beyond formal and informal training. Both companies had made a significant, long term financial investment in formal training and coaching development programs, to help sales reps to optimize their sales performance Results: 
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Celebrating Women's Day: 33 Women in Data Science from around the World & AV Community

Celebrating Women's Day: 33 Women in Data Science from around the World & AV Community | Data Nerd's Corner | Scoop.it
This article features 33 women from data science, machine learning & analytics.Here we have women leaders from Google, Linkedin,MapR,Stanford

Via Carla Gentry CSPO
Carla Gentry CSPO's insight:
WOW, what an HONOR! I am so thrilled to be mentioned with such terrific ladies in tech and science #STEM! 
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Carla Gentry CSPO's curator insight, March 8, 10:20 AM
#10 SO HONORED!  Carla Gentry is a Data Scientist at Talent Analytics, Corps. She carries an invaluable experience of over 20 years which includes working for Fortune 500 companies like Hershey, Kraft, Johnson & Johnson, Kellogg’s and Firestone. She is one of the most popular personalities in Big Data community to follow on Twitter.
Carla Gentry CSPO's curator insight, March 8, 10:21 AM
I am so honored to be included with such WONDERFUL women in tech #WIT
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How to “Get Good at R” | Open Data Science

How to “Get Good at R” | Open Data Science | Data Nerd's Corner | Scoop.it
Editor's note: post modified from original How can I get good at R? This has come up enough times for me to outline my thoughts on the subject. That way
Carla Gentry CSPO's insight:
Ignore R My advice is to stop thinking about your aptitude with R at all. Instead just view it as a tool – a means to an end. This will allow you to shift your focus to Picking a project that you care about Publishing your results from that research Communicating directly with people who value your results
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» What if HR Was Paid to Reduce Employee Turnover?

» What if HR Was Paid to Reduce Employee Turnover? | Data Nerd's Corner | 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:
HR often isn’t given data back about how long their candidates lasted in their roles. What if this changed? What if HR was paid not only to hire quickly but to also be responsible for reducing turnover in roles that have a lot of volume? What would need to change to make this happen? How would this affect day to day operations?
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Being Engaged at Work Is Not the Same as Being Productive

Being Engaged at Work Is Not the Same as Being Productive | Data Nerd's Corner | Scoop.it

Most people agree that a highly engaged workforce is a good thing, but companies need to be thoughtful about what their engagement scores are actually measuring — which can be quite variable, as shown above. Because of this ambiguity, if you are relying on engagement scores alone to understand the health of the organization, you may be missing the bigger picture of what is really happening and end up trading productivity for loosely defined “engagement.”


Carla Gentry CSPO's insight:
For example, engagement as measured by the statement “Company X is a great place to work” could be more of a reflection of the match of individuals to corporate culture. If the culture is plodding and comfortable, then an “engaged” employee who fits the mold will be happy there, but may not be more productive. On the flip side, someone who’s on a mission to change the world could be incredibly productive, but be disengaged because the culture doesn’t resonate with them.
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Predictive analytics can help beat the opponent on the other side of the net

Predictive analytics can help beat the opponent on the other side of the net | Data Nerd's Corner | Scoop.it
Combining, collating and understanding data is a real challenge, that is not just unique to sport. In all industry sectors though, the principles are essentially the same. Context and timing are key. For organisations struggling to understand or manage data, engineering could provide a solution.
Carla Gentry CSPO's insight:
Combining, collating and understanding data is a real challenge, that is not just unique to sport. In all industry sectors though, the principles are essentially the same. Context and timing are key. For organisations struggling to understand or manage data, engineering could provide a solution.
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How to create a more effective talent analytics strategy with proven data

How to create a more effective talent analytics strategy with proven data | Data Nerd's Corner | Scoop.it
Making people analytics work in recruitment

No matter where an organization may be in exploring the use of data, there are some steps that can be taken to improve the way in which data is used to make hiring decisions. It will take some time, but the payoff is worth the effort.
Carla Gentry CSPO's insight:
Making people analytics work in recruitment No matter where an organization may be in exploring the use of data, there are some steps that can be taken to improve the way in which data is used to make hiring decisions. It will take some time, but the payoff is worth the effort.
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Another NHS crisis looms – an inability to analyse data

Another NHS crisis looms – an inability to analyse data | Data Nerd's Corner | Scoop.it
Beth Simone Noveck: The opportunity to use data to improve health and social care is being hampered by a lack of personnel with skills in data science
Carla Gentry CSPO's insight:
However, the goal of using data to improve the NHS and social care is hampered by a talent gap – a lack of personnel with data analytical skills – that stands in the way of uncovering the rich insights that reside in the NHS’ own data. The NHS is not unique among institutions that are struggling to identify, hire and retain people with data science skills and the ability to apply these.
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Machine learning in the evolution of data science

Machine learning in the evolution of data science | Data Nerd's Corner | Scoop.it
In this podcast, Steven Astorino discusses how machine learning is driving the evolution of data science in strategic business initiatives.
Carla Gentry CSPO's insight:
Steven Astorino is Vice President, Development, IBM Private Cloud Analytics Platform. In this podcast, he discusses how machine learning is driving the evolution of data science in strategic business initiatives.
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» How Do Algorithms Reduce Bias During the Talent Acquisition Process?

» How Do Algorithms Reduce Bias During the Talent Acquisition Process? | Data Nerd's Corner | Scoop.it

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:
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.
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» Greta Roberts talks Predictive Analytics ROI & previews PAW for Workforce

» Greta Roberts talks Predictive Analytics ROI & previews PAW for Workforce | Data Nerd's Corner | Scoop.it

Our predictive work focuses on what we call “high volume roles”. That is: Roles that have a lot of employees in the same role, performing exactly the same tasks. Examples are: Sales Reps., Insurance Agents, Call Center Reps, Customer Service Reps, Bank Tellers and the like. We focus on this area because high volume roles give us a lot of data to work with – with employees who have the same goals, etc. This is a very high value area for the organization when we can solve a specific attrition or performance challenge.

Carla Gentry CSPO's insight:
In your work with predictive analytics, what areas of the workforce are you focused on? (i.e., optimizing workforce productivity, using big data to solve workforce challenges, building a workforce analytics driven culture, etc.)?
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» The Beginner’s Guide to Predictive Workforce Analytics

» The Beginner’s Guide to Predictive Workforce Analytics | Data Nerd's Corner | Scoop.it
Human Resources Feels Pressure to Begin Using Predictive Analytics
Today’s business executives are increasingly applying pressure to their Human Resources departments to “use predictive analytics”.  
Carla Gentry CSPO's insight:
Human Resources Departments have a Different, and Somewhat Unique, Challenge not Faced By Most Other Lines of Business
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5 ways to improve a data strategy - Information Age

5 ways to improve a data strategy - Information Age | Data Nerd's Corner | Scoop.it
Big data and analytics initiative is about creating a shared set of knowledge – a shared set of facts, insights and correlations that helps employees and departments develop a singular view of the organisation.These insights can empower organisations to serve their customers better and outperform competitors by driving innovation, finding new revenue streams and streamlining day-to-day operations.
Carla Gentry CSPO's insight:
5 ways to improve a data strategy
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Celebrating Women's Day: 33 Women in Data Science from around the World & AV Community

Celebrating Women's Day: 33 Women in Data Science from around the World & AV Community | Data Nerd's Corner | Scoop.it
Grace Hopper is an American Computer Scientist and US Navy rear admiral. She was the first one to invent a compiler for a computer programming language. She believed programs should be written in a simplified language like English and popularized the term machine independent programming language. She developed COBOL one of the widely programming languages in every business till date. She developed validation software for COBOL and its compiler.
Carla Gentry CSPO's insight:
She Believed, she could. So, she did
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How is Deep Learning Changing Data Science Paradigms? - Schibsted Bytes

How is Deep Learning Changing Data Science Paradigms? - Schibsted Bytes | Data Nerd's Corner | Scoop.it
Carla Gentry CSPO's insight:
Interesting red for Data Scientist!
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The Most Popular Language For Machine Learning and Data Science Is …

The Most Popular Language For Machine Learning and Data Science Is … | Data Nerd's Corner | Scoop.it

The Most Popular Language For #MachineLearning and Data Science Is … http://www.kdnuggets.stfi.re/2017/01/most-popular-language-machine-learning-data-science.html

Carla Gentry CSPO's insight:
Enough speaking, let’s get data. I searched for skills used in conjunction with “machine learning” and “data science”, where skills are one of the prominent programming language Java, C, C++, and Javascript. I also included Python and R which we know are popular for machine learning and data science, as well as Scala given its link to Spark, and Julia that some think is the next big thing here.
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» From Human Screen to Machine: Predictive Analytics Helps Avoid a Major Point of Hiring Failure

» From Human Screen to Machine: Predictive Analytics Helps Avoid a Major Point of Hiring Failure | Data Nerd's Corner | Scoop.it

But how is initial candidate screening handled at your organization? Many employers take an approach that isn’t at all what we expected.

Talent Analytics uses predictive modeling to help organizations reduce attrition and increase on the job performance with in high volume job roles. Our projects give us insight into the entire hiring process."


Carla Gentry CSPO's insight:
We’ve discovered that a surprising number of companies, typically midsize and large enterprises who screen a large volume of candidates, often relegate this single most critical task to individuals far removed from the line of business. At times this task is given to contractors, interns, temps or external part-time employees. What a huge point of failure leading to massive hiring errors and missed opportunities.
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How To Pitch Right: Tips from Shark Tank Survivors

How To Pitch Right: Tips from Shark Tank Survivors | Data Nerd's Corner | Scoop.it
Entrepreneurs are perpetual idea machines with the next innovative vision just around the corner. However, turning that vision into reality takes funding, and without the perfect pitch, investors simply lose interest.
Carla Gentry CSPO's insight:
Entrepreneurs are perpetual idea machines with the next innovative vision just around the corner. However, turning that vision into reality takes funding, and without the perfect pitch, investors simply lose interest.
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The Mathematics of Machine Learning

The Mathematics of Machine Learning | Data Nerd's Corner | Scoop.it
Bridging the gap between technology and business
Carla Gentry CSPO's insight:
The main question when trying to understand an interdisciplinary field such as Machine Learning is the amount of maths necessary and the level of maths needed to understand these techniques. The answer to this question is multidimensional and depends on the level and interest of the individual. Research in mathematical formulations and theoretical advancement of Machine Learning is ongoing and some researchers are working on more advance techniques. I’ll state what I believe to be the minimum level of mathematics needed to be a Machine Learning Scientist/Engineer and the importance of each mathematical concept.
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» Understanding Your Most Important Asset

» Understanding Your Most Important Asset | Data Nerd's Corner | 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:
Excerpts: "People Analytics in the Era of #BigData: Changing the Way You Attract, Acquire, Develop, & Retain Talent"
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Disney InstituteVoice: Why Your Fellow Employees Might Be Your Most Important Customers

Disney InstituteVoice: Why Your Fellow Employees Might Be Your Most Important Customers | Data Nerd's Corner | Scoop.it
Below, eight successful human resources executives from Forbes Human Resources Council discuss the different ways human resources teams can benefit from using workforce analytics.
Carla Gentry CSPO's insight:
Below, eight successful human resources executives from Forbes Human Resources Council discuss the different ways human resources teams can benefit from using workforce analytics.
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The Beginner’s Guide to Writing a Data-Driven Post

The Beginner’s Guide to Writing a Data-Driven Post | Data Nerd's Corner | Scoop.it
The Beginner’s Guide to Writing a Data-Driven Post. https://t.co/xM1UFwCIkH via neil patel #blog https://t.co/yAgbQPW0O8
Carla Gentry CSPO's insight:
Here are five simple steps to creating data-driven blog content. These are the exact strategies that I use to write all of the content on NeilPatel.com and they’ll work for you, too.
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