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29 August 2016

How To Solve Excel problems with best SAS utility

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Reading an Excel file into SAS

Suppose that you have an Excel spreadsheet called auto.xlsx. The data for this spreadsheet are shown below.

MAKE MPG WEIGHT PRICE
AMC Concord 22 2930 4099
AMC Pacer 17 3350 4749
AMC Spirit 22 2640 3799
Buick Century 20 3250 4816
Buick Electra 15 4080 7827
Using the Import Wizard is an easy way to import data into SAS.  The Import Wizard can be found on the drop down file menu.  Although the Import Wizard is easy it can be time consuming if used repeatedly.  The very last screen of the Import Wizard gives you the option to save the statements SAS uses to import the data so that they can be used again.  The following is an example that uses common options and also shows that the file was imported correctly.

PROC IMPORT OUT= WORK.auto1 DATAFILE= "C:\auto.xl"
DBMS=xlsx REPLACE
SHEET="auto"; 
GETNAMES=YES;
RUN;
  • The out= option in the proc import tells SAS what the name should be for the newly-created SAS data file and where to store the data set once it is imported. 
  • Next the datafile= option tells SAS where to find the file we want to import. 
  • The dbms= option is used to identify the type of file being imported. 
  • The replace option will overwrite an existing file.
  • To specify which sheet SAS should import use the sheet="sheetname" statement.  The default is for SAS to read the first sheet.  Note that sheet names can only be 31 characters long.
  • The getnames=yes is the default setting and SAS will automatically use the first row of data as variable names.  If the first row of your sheet does not contain variable names use the getnames=no

Writing Excel files out from SAS

It is very easy to write out an Excel file using proc export in SAS.
Here is a sample program that writes out SAS data called mydata to an Excel file called mydata.xlsx into the directory "c:\dissertation".

proc export data=mydata outfile='c:\dissertation\mydata.xlsx' 
dbms = xlsx replace;
run;

28 August 2016

10 Excel topics for an excellent data career

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The below listed topics help you get solid footing in Excel Analytics. Just practice these 10 topics step by step and by completing all, you will be an expert in Excel.

  1.  Tables in Excel
  2. Grabbing data from external sources
  3. Cleaning data with functions
  4. Working with Pivot tables
  5. Writing Formulae for Pivot tables
  6. Pivot Charts
  7. How to use data base functions
  8. How to use statistics
  9. Inferential Statistics
  10. Descriptive statistics

21 August 2016

Best Article on IOT how implemented in Auto insurance

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Mile-based insurance an application of IoT
Mile-based insurance an application of IoT
IoT in the connected car is transforming how insurance premiums can be calculated. With the help of a small wireless device that plugs into the diagnostic port, Metromile offers a “per-mile” usage-based insurance. Often, low-mileage drivers overpay for insurance because they’re subsidizing those who drive the most. But since the the number one risk indicator for drivers is time on the road, Metromile can offer insurance pro-rata by tracking the miles driven.

According to wiki:

Usage-based insurance (UBI) -also known as pay as you drive (PAYD) and pay how you drive (PHYD) and mile-based auto insurance is a type of vehicle insurance whereby the costs are dependent upon type of vehicle used, measured against time, distance, behavior and place. This differs from traditional insurance, which attempts to differentiate and reward "safe" drivers, giving them lower premiums and/or a no-claims bonus. However, conventional differentiation is a reflection of history rather than present patterns of behaviour. This means that it may take a long time before safer (or more reckless) patterns of driving and changes in lifestyle feed through into premiums.

Usage of IoT technique

Pay as you drive (PAYD) means that the insurance premium is calculated dynamically, typically according to the amount driven. There are three types of usage-based insurance:
  • Coverage is based on the odometer reading of the vehicle.
  • Coverage is based on mileage aggregated from GPS data, or the number of minutes the vehicle is being used as recorded by a vehicle-independent module transmitting data via cellphone or RF technology.
  • Coverage is based on other data collected from the vehicle, including speed and time-of-day information, historic riskiness of the road, driving actions in addition to distance or time travelled.
The formula can be a simple function of the number of miles driven, or can vary according to the type of driving or the identity of the driver. Once the basic scheme is in place, it is possible to add further details, such as an extra risk premium if someone drives too long without a break, uses their mobile phone while driving, or travels at an excessive speed.

Telematic usage-based insurance (i.e. the latter two types, in which vehicle information is automatically transmitted to the system) provides a much more immediate feedback loop to the driver,by changing the cost of insurance dynamically with a change of risk. This means drivers have a stronger incentive to adopt safer practices. For example, if a commuter switches to public transport or to working at home, this immediately reduces the risk of rush hour accidents. With usage-based insurance, this reduction would be immediately reflected in the cost of car insurance for that month.

The smartphone as measurement probe for insurance telematics has been surveyed

09 August 2016

Quick Steps: IoT in Healthcare and IT skills you need

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IOT in HealthCare
IoT and multimedia technologies have made their entrance in the healthcare field thanks to ambient-assisted living and telemedicine. Smart devices, mobile Internet, and Cloud services contribute to the continuous and systematic innovation of Healthcare and enable cost effective, efficient, timely, and high-quality ubiquitous medical services.

Pervasive healthcare applications generate a vast amount of sensor data that have to be managed properly for further analysis and processing. The adoption of Cloud in this scenario leads to the abstraction of technical details, eliminating the need for expertise in, or control over, the technology infrastructure, and it represents a promising solution for managing healthcare sensor data efficiently.

It further makes mobile devices suited for health information delivery, access and communication, also on the go, enhancing medical data security, availability, and redundancy. Moreover, it enables the execution (in the Cloud) of secure multimedia-based health services, overcoming the issue of running heavy multimedia & security algorithms on devices with limited computational capacity and small batteries. In this field, common issues related to management, technology, security,and law have been investigated: interoperability, system security, streaming Quality of Service (QoS), and dynamically increasing storage are commonly considered obstacles.