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All Blog Posts Tagged 'modeling' (89)

Prescriptive versus Predictive Analytics - A Distinction without a Difference?

Summary:  Is the addition of “Prescriptive” analytics to our nomenclature really worthwhile or are we just confusing our customers?

I admit to being annoyed when this or that industry wag tries to coin a new term to describe some portion of the discipline we are already practicing.  Some of these folks I think are…

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Added by William Vorhies on October 23, 2014 at 10:00am — 9 Comments

Lesson 3: Open Source, Distribution, or Suite

Summary:  Which to pick?  Open Source, Distribution, or Big Data Suite.  Here are the factors you should consider.

Before we get to the…

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Added by William Vorhies on September 5, 2014 at 8:30am — No Comments

9 Lessons: Picking the Right NoSQL Tools

Summary:  This blog series is designed to help you understand which NOSQL Big Data database is right for you.  It is addressed to business executives and managers who need a primer on how this decision should be made. 

Starting a Big Data Initiative is…

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Added by William Vorhies on September 3, 2014 at 8:31am — 2 Comments

Types and Uses of Predictive Analytics, What they are and Where You Can Put Them to Work

Summary: Gartner says that predictive analytics is a mature technology yet only one company in eight is currently utilizing this ability to predict the future of sales, finance, production, and virtually every other area of the…

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Added by William Vorhies on August 13, 2014 at 10:54am — No Comments

Leveraging Predictive Analytics to Avoid a Major Point of Hiring Failure

By Greta Roberts, CEO, Talent Analytics, Corp. @GretaRoberts

Program Chair, Predictive Analytics World for Workforce

What is an employer’s most business-critical corporate process? At or near the top of this list has…

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Added by Mike Kennedy on August 11, 2014 at 4:28am — 4 Comments

Beyond the 4 Ms of Manufacturing

The industrial revolution of the 1800s established the building blocks of Manufacturing as we know it today. Man, Machine, Material and Method were connected together to form an intricate system on which manufacturing processes and its operational dynamics were based. The resulting complexity of such a system however, has resulted in ineptitudes which have become difficult…

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Added by Sumit Prasad on July 23, 2014 at 1:00am — No Comments

Big Data A to ZZ – A Glossary of my Favorite Data Science Things

Here are some of my favorite things about big data and data science, from A to Z (actually, ZZ):

A – Association rule mining

B – Bayes belief networks

C – Characterization

D –…

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Added by Kirk Borne on March 16, 2014 at 4:00pm — 2 Comments

(R + Python)

Both R & Python should be measured based on their effectiveness in advanced analytics & data science. Initially, as a new comer in data science field we spend good amount of time to understand the pros and cons of these two. I too carried out this study solely for “self” to decide which tool should i pick to get in depth of data science. Eventually, i have started realizing that both (R & Python) has its space of mastery along with their broad support to data science. Here some…

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Added by Manish Bhoge on February 7, 2014 at 9:22pm — 4 Comments

10 Great Attributes of Jigsaw Academy's HR Analytics Certification Course

I have been reading about Jigsaw Academy's new HR Analytics Training Course, which starts soon (January 26, 2014). HR Analytics is a remarkably interesting new field -- or, one could say, an old field with exciting new dimensions! The application of…

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Added by Kirk Borne on January 20, 2014 at 9:30pm — No Comments

Operational Data Science: excerpt from 2 great articles

The term "Data Science" has been evolving not only as a niche skill but as a niche process as well. It is interesting to study "how" the Big data analytics/Data Science/Analytics can be efficiently implemented into the enterprise. So, along with my typical study of analytics viz. Big data analytics I have been also exploring the methodologies to bring the term "Data Science" into mainstream of existing enterprise data analysis, which we conventionally know as "Datawarehouse & BI". This…

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Added by Manish Bhoge on December 12, 2013 at 7:30am — No Comments

Banks Want More Wallet-Share? Stop Competing with Each Other.

In the late 1980s and early 1990s, the call center market was booming and it was truly the only way to give consumers access to service at their convenience while providing a vehicle for companies to up-sell and cross-sell products.  Before the Internet of things that was a very effective vehicle and to some degree, it still is.

Companies who were…

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Added by Tullio Siragusa on December 4, 2013 at 3:00am — No Comments

A Practical Introduction to Data Science from Zipfian Academy

There are plenty of discussions about what data science is, what defines a data scientist, and how to position yourself as a …

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Added by Katie Kent on November 8, 2013 at 4:12pm — 1 Comment

Warm-up exercise before data science.

Practicing Data science indeed a long term effort than a learning handful of skills.  We ought to be academically good enough to take up this challenge. However, if you think you came a long way from your academic rebuilding,  but you still have that zeal & passion to take the oil from the data and fill the skill gap of data science then here is the warm-up tips. Below points must exercised before jumping into…

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Added by Manish Bhoge on October 18, 2013 at 9:26am — No Comments

Do you want to solve real world predictive analytics case study and get ranked amongst your peers?

Statistics.com, a provider of online education in statistics and analytics, announces a partnership with CrowdANALYTIX, a predictive modeling “managed crowdsourcing” company, offering a new online course, “Applied Predictive Analytics in partnership with CrowdANALYTIX“, which will run from Oct. 11 to Nov 8, 2013.

The goal of this course is to teach users (who have basic knowledge of R programming, predictive analytics and statistics)…

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Added by Janet Dobbins on September 11, 2013 at 6:58am — No Comments

Data Scientist Core Skills

Data Science - The Process of Capturing, Analyzing and Presenting Business Intelligence with Skill DataReality

Capture

Programming and Database skills …

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Added by Mitchell A. Sanders on August 27, 2013 at 4:00pm — 25 Comments

An indispensable Python : Data sourcing to Data science.

Data analysis echo system has grown all the way from SQL's to NoSQL and from Excel analysis to Visualization. Today, we are in scarceness of the resources to process ALL (You better understand what i mean by ALL) kind of data that is coming to enterprise. Data goes through profiling, formatting, munging or cleansing, pruning, transformation steps to analytics and predictive modeling. Interestingly, there is no one tool proved to be an effective solution to run…

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Added by Manish Bhoge on August 27, 2013 at 8:00am — 4 Comments

Will Data Science Forever Change Branding Strategies? Here is a Glimpse of The Future Company

Know the numbers, know your business! 

Numbers are the fundamental language of business. The bottom-line on the income statement is a number. The business plan is expressed specifically as numbers on the operating budget, numbers that may derive largely from statistical projections of revenues and costs.…

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Added by Tullio Siragusa on August 15, 2013 at 6:18am — No Comments

Predictive Modeling is Useless!

If you’re a modeler, you might say, “who the heck is this guy telling me that my precious thing is useless?” Wait a minute. I will explain later. If you’re new to this, let me tell you what predictive modeling is: It is the power to predict the future. Like a prophecy, except its using data, lots of them. Sounds cool? Yes, but it’s useless. Sad? Me too. I’m also a modeler.



Let me tell you a story. Once upon a time, I was preaching in front of senior management on how we could get… Continue

Added by Eka Aulia on June 6, 2013 at 10:05pm — 1 Comment

Big Data, Fast Data, Smart Data

Big data needs to be fast and smart. Here’s why.

 

DAUNTING DATA

Every minute, 48 hours of video are uploaded onto Youtube. 204 million e-mail messages are sent and 600 new websites generated. 600,000 pieces of content are shared on Facebook, and more than 100,000 tweets are sent. And that does not even begin to scratch the surface of data generation, which spans to sensors, medical records, corporate databases, and…

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Added by Alissa Lorentz on April 12, 2013 at 5:18am — No Comments

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