Topic - Analysis and Process
Objective : Performing Processes , Managing and Viewing Output
Objective : Performing Processes , Managing and Viewing Output
Wednesday, October 28, 2015
Data Analysis using SAS Enterprise Guide Vol. 1
Topic - SAS Enterprise Guide Projects
Objective : Introduction , Project Placement , Navigation and Storage
SAS EG is one of the newest and recent Click'n'Drag interface from SAS.As more and more analysis is required its better to focus on the Data Transformation Starategy rather investing time on Syntactical approach for right developed code.
Analyst Interface option from Base SAS is being replaced and presented with much easier and point to point Data Analysis approach.
A long range of Data analysis like Descriptive Statisics , Variance , Correlation and Collinearity is there to work upon using this IDE.
Objective : Introduction , Project Placement , Navigation and Storage
SAS EG is one of the newest and recent Click'n'Drag interface from SAS.As more and more analysis is required its better to focus on the Data Transformation Starategy rather investing time on Syntactical approach for right developed code.
Analyst Interface option from Base SAS is being replaced and presented with much easier and point to point Data Analysis approach.
A long range of Data analysis like Descriptive Statisics , Variance , Correlation and Collinearity is there to work upon using this IDE.
Wednesday, October 7, 2015
From Data Analyst to Data Scientist Vol. 2
Still a Analyst for now :)
But working on different aspects of Data Analysis to reach the understanding of Data Science.
1. Working on Risk Scoring for Health Insurance Sectors , preparing an insight on stepped approach on Risk Analysis of Claim information.
Project Specification : SAS / Risk Analytics
Project Link :
Project Status : Open
/*Post is in Development , Watch out this Space for more*/
But working on different aspects of Data Analysis to reach the understanding of Data Science.
1. Working on Risk Scoring for Health Insurance Sectors , preparing an insight on stepped approach on Risk Analysis of Claim information.
Project Specification : SAS / Risk Analytics
Project Link :
Project Status : Open
/*Post is in Development , Watch out this Space for more*/
Risk Scoring for Health Insurance Sector - Vol. 3
Exploratory Data Analysis (EDA)
What do we understand out of Exploratory Data Analysis.
Its the basic step which needs to be done on the Data on which we want to begin our analysis.
As a Part of EDA , we will be processing our data on below step based approach
1. Finding Missing Data and its Rectification
2. Finding Outliers
/*Post is under development, Please watch this space for more*/
What do we understand out of Exploratory Data Analysis.
Its the basic step which needs to be done on the Data on which we want to begin our analysis.
As a Part of EDA , we will be processing our data on below step based approach
1. Finding Missing Data and its Rectification
2. Finding Outliers
/*Post is under development, Please watch this space for more*/
Risk Scoring for Health Insurance Sector - Vol. 2
Lets Start up with the ScoreCard Development Process , as we have covered the basic attributes of Data Segmentation, Clustering and other artifacts related to an unscreened data.
Starting with Medical Health Insurace Sector, Its better to converge all our insight toward understanding the Medical Claim Data.
Related to this Claim Data , We have a pool of information related to Correlate and Analyse:
1. Types of Claims
2. The Amount that is being Billed under a Category or a Plan (Groups).
3. The Member Information
4. Information pertaining to different Category of Plan and Product.
5. Information on Cluster of Policy data based on Policy Year.
6. Correlation on Risk factor between Claimed Amount and Member information.
Note : For a different domain , the terminologies will be changing but the idea of analysing the data will be continued in the same manner.
Meanwhile , when we have our gathered data ready. We can proceed our analysis on a step based approach.
Please read the forward link to continue Risk Scoring for Health Insurance Vol. 3
Starting with Medical Health Insurace Sector, Its better to converge all our insight toward understanding the Medical Claim Data.
Related to this Claim Data , We have a pool of information related to Correlate and Analyse:
1. Types of Claims
2. The Amount that is being Billed under a Category or a Plan (Groups).
3. The Member Information
4. Information pertaining to different Category of Plan and Product.
5. Information on Cluster of Policy data based on Policy Year.
6. Correlation on Risk factor between Claimed Amount and Member information.
Note : For a different domain , the terminologies will be changing but the idea of analysing the data will be continued in the same manner.
Meanwhile , when we have our gathered data ready. We can proceed our analysis on a step based approach.
Please read the forward link to continue Risk Scoring for Health Insurance Vol. 3
Tuesday, October 6, 2015
Risk Scoring for Health Insurance Sector - Vol. 1
Risk Scoring for Health Insurance
A little insight would be too important for you to start off with the basic risk understanding techniques in Health Insurance Domain.
This is the part where we would be learning our way to develop a Risk Scorecards in a simpler yet subtle manner.
Some of the basic questions we will be dealing with :
1. Why do we need Risk Scoring Understanding in Health Insurance Domain.
2. Is it related to Credit Risk Scoring from Banking Domains.
3. How to Start ?
I would like to mention that I am developing such a Risk Model and would be sharing all my learnings from a Beginners Phase.
/* Post is in the development Stage , Keep looking */
Read further with this link Risk Scoring for Health Insurance Sector - Vol. 2
A little insight would be too important for you to start off with the basic risk understanding techniques in Health Insurance Domain.
This is the part where we would be learning our way to develop a Risk Scorecards in a simpler yet subtle manner.
Some of the basic questions we will be dealing with :
1. Why do we need Risk Scoring Understanding in Health Insurance Domain.
2. Is it related to Credit Risk Scoring from Banking Domains.
3. How to Start ?
I would like to mention that I am developing such a Risk Model and would be sharing all my learnings from a Beginners Phase.
/* Post is in the development Stage , Keep looking */
Read further with this link Risk Scoring for Health Insurance Sector - Vol. 2
Wednesday, September 23, 2015
From Data Analyst to Data Scientist Vol. 1
Hi Folks,
Its not enough if you work with a single tool or technology to way up above to become a Data Scientist. I am an aspiring Data Analyst and to reach the work of a Data Scientist its not a single technology workout.
Starting with my way,
I have enrolled myself for online Courses available in EDX.org .
Learning advance aspects of SAS and Python for my Analytical Programming Skills.
Reaching out for Domain specific Analytical issues and stacking it on my Project Lists.
Online repository is created at GitHub where all the Project Specification and details with all relevant datasets will be shared.
Will be following Kaggle.com for all the latest Competitions and try to reach up to a level where I could easily understand and demonstrate my Analytical problem solving Skills.
Read more with this link Still a Data Analyst !!
-PVZ
Its not enough if you work with a single tool or technology to way up above to become a Data Scientist. I am an aspiring Data Analyst and to reach the work of a Data Scientist its not a single technology workout.
Starting with my way,
I have enrolled myself for online Courses available in EDX.org .
Learning advance aspects of SAS and Python for my Analytical Programming Skills.
Reaching out for Domain specific Analytical issues and stacking it on my Project Lists.
Online repository is created at GitHub where all the Project Specification and details with all relevant datasets will be shared.
Will be following Kaggle.com for all the latest Competitions and try to reach up to a level where I could easily understand and demonstrate my Analytical problem solving Skills.
Read more with this link Still a Data Analyst !!
-PVZ
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