June 12, 2020
Description: Majority of AI approaches are based on the construct of training against historical data and then inferencing new data. While this is a sound and proven approach, a lot of IoT assets coming online don’t have historical data and we don’t necessarily have the time to wait.
Added by Jane Howell on June 12, 2020 at 2:30pm — No Comments
Summary: Digital Decisioning Platforms is a new segment identified by Forrester that marries Business Process Automation, Business Rules Management, and Advanced Analytics. For platform developers it’s a new way to slice the market. For users it eases integration of predictive models into the production environment.
Added by William Vorhies on October 30, 2018 at 8:30am — No Comments
Summary: If you’re still writing code to clean and prep your data you're missing big opportunities for efficiency and consistency with modern data prep platforms.
Summary: Someone had to say it. In my opinion R is not the best way to learn data science and not the best way to practice it either. More and more large employers agree.
Python, R and SAS are the three most popular languages in data science. If you are new to the world of data science and aren’t experienced in either of these languages, it makes sense to be unsure of whether to learn R, SAS or Python.
Don’t fret, by the time you’re done reading this article, you will know without a doubt which language is the right one for you.
Visual Analytics and Data Discovery allow analysis of big data sets to find insights and valuable information. This is much more than just classical Business Intelligence (BI). See this article for more details and motivation: "Using Visual Analytics to Make Better Decisions: the Death Pill Example". Let's take a look at important characteristics to choose the right tool for…Continue
Added by Kai Waehner on July 27, 2016 at 10:00pm — No Comments
Summary: Picking an analytic platform when first starting out in data science almost always means working with what we’re most comfortable. But as organizations grow larger there is a need for standardization and for selecting one, or a few analytic tools.
For many scientists and data analysts, outliers are like a ‘black box’ in conventional statistics. Many believe that these outlier observations arise due to errors or due to improper procedures in the experiment. Majority of them eliminate the outliers unscientifically by brute force. Some identify them statistically but discard them as if they are junk. Some understand importance of the outliers but they do not know how to deal with it. If you are one among them or interested in scope of…Continue
Added by Venu Perla PhD on November 1, 2015 at 4:45pm — No Comments
Life scientists collect similar type of data on daily basis. Statistical analysis of this data is often performed using SAS programming techniques. Programming for each dataset is a time consuming job. The objective of this paper is to show how SAS programs are created for systematic analysis of raw data to develop a linear regression model for prediction. Then to show how PROC SQL can be used to replace several data steps in the code. Finally to show how SAS macros are created on these…Continue
Added by Venu Perla PhD on October 10, 2015 at 9:00am — No Comments
Summary: If you’re making the decision to use NoSQL, how do you quantify the value of the investment?
If you are exploring NoSQL, once you become educated on the basics there are two questions that will rapidly move to the top of your list of considerations.
Added by William Vorhies on October 17, 2014 at 10:00am — No Comments
All of us at some point in the process of examining…Continue
Added by Aatash Shah on February 27, 2014 at 3:23am — No Comments
Bob Muenchen's very useful work on this topic, SAS Dominates Analytics Job Market; R up 42% sent me back to some 2012 work we did at Statistics.com on the subject of what employers are looking for in the way of analytics skills. First, our main results:
1. Our numbers showed a much less SAS-dominant world: 1.92 SAS jobs for every R job. Bob had found the ratio to…Continue
The ‘Bell curve’ or the ‘Gaussian bell curve’ is one of the fundamental concepts on which most of the statistical analysis is based. From social sciences to astronomy to financial services- most of the application of statistics in the real world relies on the assumption that the data being analysed is distributed in the shape of the bell curve.
Added by Gaurav Vohra on January 3, 2013 at 8:30pm — No Comments
Data Analytics is a process of summarizing data with the intent to extract predictive information and develop conclusions from the data and using it for making strategic decisions and operational policies. A huge demand for data analysis services in India generates ample earning opportunities to companies which are offering data analysis services.
Data analytics in India is extensively used in Banking and Financial sectors. Data mining and data analysis being carried out by BPO…
Added by AcademyForDecisionScience&Analyt on October 29, 2012 at 8:13pm — No Comments
Educating savvy and business-minded Indians on the importance of numbers and analytics in your business is like teaching the properties of sand to someone in the desert, but here is my effort anyway.
The simplest definition of analytics is "the science of analysis." However, a practical definition would be how an entity, e.g., a business, arrives at an optimal or realistic decision based on existing data. Business managers may choose to make decisions based on past experiences or…Continue
Added by AcademyForDecisionScience&Analyt on October 29, 2012 at 7:30pm — No Comments
Data scientists are the new astronauts. Everyone wants to become one. And it is not difficult to understand the reason for this.
In this age of “Big data”, more and more businesses are relying on people who can make sense of the vast amounts of information generated around us – people who can use sophisticated tools and complex-sounding statistical techniques to derive insights from larger and larger mounds of data.
Businesses have started to understand the power of data. They…Continue
Added by Gaurav Vohra on September 10, 2012 at 11:29pm — No Comments