Open data is a thing, an idea, and an ideal. Open data is one of those "superhero words" alongside its cousins the Cloud and Big Data. I like to call them superhero words because they are supernatural forces that seemingly defy definition and can't be seen. Yet…Continue
Impact craters are distributed randomly on Mars and many other celestial bodies. Their radius most likely follow an exponential distribution. By estimating the mean of the exponential distribution in question, selecting 100 random locations, and determining how many lie in (at least) one crater, you can determine the age of the celestial body.
If you work in the software industry, it’s likely that you have heard about the divide and conquer design paradigm, which basically consists of recursively splitting a problem into two or more sub-problems (divide), until these become simple enough to be solved directly (conquer).
What you might not know is that this paradigm originates from an old political strategy (the name is derived from the Latin saying divide et impera) that suggests it is…Continue
Added by Irina Papuc on March 17, 2016 at 4:30am — No Comments
Organizations empty a considerable measure of exertion into the Business Intelligence and Analytics (BI/A). In late 2013, Gartner anticipated that the significance of BI/An activities for CIOs will keep on developing great into 2017 and past. Notwithstanding all the exertion and consideration on investigation however, organizations are as yet attempting to succeed with Big Data. In a late 2014 review, it was found that just 27% of Big Data ventures succeed, while just 13%…Continue
Added by Rai Mirrow on March 17, 2016 at 4:30am — No Comments
This series is written for you the business user, CXO, business owner, who does not care for complex jargon but believes in seeing tangible impact on business. It is to introduce this novel concept of cognitive data-products that are set to storm the business world. I have lost count of the number of times where customer conversations veer towards “Yes; the algorithm sounds good but what decision can I take on the basis of this?”
Added by Adurthi Ashwin Swarup on March 17, 2016 at 4:00am — No Comments
I know you are an examiner and all you think about is numbers. However, what separates a wonderful business expert from normal information examiner? It's their capability to comprehend business. You ought to attempt to comprehend business even before you take up your first venture. Here are a couple of things you should investigate:
Added by Rai Mirrow on March 17, 2016 at 4:00am — No Comments
Starred articles are new additions or updated content, posted between Thursday and Sunday. The weekly digest has six sections: (1) Featured Resources and Technical Contributions, (2) Featured Articles and Case Studies, (3) From our Sponsors, (4) News, Events, Books, Training, Forum Questions, (5) Picture of the Week, and (6) Syndicated Content.
The full version is always published Monday.…Continue
Added by Vincent Granville on March 16, 2016 at 3:00pm — No Comments
In the years that MIT Sloan Management Review has been studying the effects of data analytics in companies, we’ve noticed the reality of its value and staying power—and how best to use it—has started to come into sharp focus. In a new research study we conducted with SAS, we determined that most companies are not prepared for the strategic changes required to achieve success with analytics. In fact, the key failing among…Continue
Added by Deb Gallagher on March 16, 2016 at 11:30am — No Comments
This Tutorial talks about basics of Linear regression by discussing in depth about the concept of Linearity and Which type of linearity is desirable.
In Linear Regression the term linear is understood in 2 ways -
Added by Shantanu Deo on March 16, 2016 at 4:30am — No Comments
Predictive analysis is a journey of refinement of data over time using a predictive model. Right from choosing the right model to refine your data to the amount of time and effort invested, there are many thing which may go wrong in your way.
Predictive analytics is also the enabler of Big Data; businesses collect vast amounts of real-time customer data and predictive analytics uses this historical data, combined with customer…Continue
Added by Abhishek Srivastava on March 16, 2016 at 12:00am — No Comments
The aviation industry is a sector involving high cost and security concerns. Analytics in this sector has huge potential, as varied data can be collected at each touch point showcasing customer interests. Crucial factors such as weather forecast should be critically analyzed using sophisticated tools to ensure passenger safety. A lot of logistics complexity also lies straight from building an aircraft to safe take–off and landing. Also, since customers pay the highest prices in this form of…Continue
Added by Tanmay Bhandari on March 15, 2016 at 7:30pm — No Comments
When I first got a Fitbit, it was amazing.
My daily dashboard, focusing mostly on a 10,000-step target, was incredibly motivating. Was I hitting the target? Answer: sometimes. Connecting with friends added great gamification. I began making different choices in my daily routine to take more steps. When I lost my first tracker, Fitbit sent me a free replacement. Wow! What more could I ask from this dream company?
Over time, however, I…Continue
Summary: The premise of this new Key Object architecture is that search is broken, at least as it applies to complex merchandise like computers, printers, and cameras. An innovative and workable solution is described. The question remains, is the pain sufficient to justify a switch?
Added by William Vorhies on March 15, 2016 at 9:39am — No Comments
European communication and technology industry presently observes strategic business activities in its favor. The adoption of Accenture’s IT services by insurance intermediary Towergate is a recent example of enterprises’ action plan for integration of their services. “To ensure we pave the way for growth, we are transforming our entire IT infrastructure to positively change how we run our business and serve our diverse client base,” said Gordon Walters, CIO,…
Added by Kirti Autade on March 15, 2016 at 2:00am — No Comments
Starred articles are candidates for the picture of the week. A comprehensive list of all past resources is found here. We are in the process of automatically categorizing them using indexation and automated tagging…Continue
In the world of data analysis, one tool is often left unused. While being a very powerful analytics tool, cohorts are often…Continue
Added by Vincent Granville on March 13, 2016 at 8:40pm — No Comments
This long article with a lot of source code was posted by Suraj V Vidyadaran. Suraj is pursuing a Master in Computer Science at Temple university primarily focused in Data Science specialization. His areas of interests are in sentiment analysis, data visualization, big data and machine learning.
This data is obtained from UCI Machine learning repository. The purpose of the…Continue
Added by L.V. on March 13, 2016 at 9:30am — No Comments
Machine learning (ML) is the motor that drives data science. Each ML method (also called an algorithm) takes in data, turns it over, and spits out an answer. ML…Continue
Guest blog post by Dalila Benachenhou, originally posted here. Dalila is Professor at George Washington University. In this article, benchmarks were computed on a specific data set, for Geico Calls Prediction, comparing Random Forests, Neural Networks, SVM, FDA, K Nearest Neighbors, C5.0…Continue
Summary: It’s become almost part of our culture to believe that more data, particularly Big Data quantities of data will result in better models and therefore better business value. The problem is it’s just not always true. Here are 7 cases that make the point.