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Gurao_Adityavikram_Tutorial_Two.docx

Gurao_Adityavikram_Tutorial_Two

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Worcester Polytechnic Institute *

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584

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Information Systems

Date

Feb 20, 2024

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docx

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16

Uploaded by DrTitaniumRhinoceros

MIS - 502 Tutorial Two By Adityavikram Rajendra Gurao Column Profiling: Attribute: Lead_Key.LEADS.HMIS Type: INTEGER CONSTANT Domain: Numeric { 1 to 20539 } Pattern: Unique Increasing Numbers. # Records: 20,539 unique (none null) Dependencies: None Redundancies: None

Attribute: Entity_No.LEADS.HMIS Type: INTEGER Domain: Numeric { 2 to 100063557 } Pattern: Unique Increasing Numbers. # Records: 20,539 (none Null) 4003 Unique Values Median - 20,297 Mode - 2619 2621 22161 42056

Max - 100055263 Dependencies: Lead_Key, Name Redundancies: None

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Attribute: Name.LEADS.HMIS Type: Text, Alphabetic (10 to 89), VARCHAR (50) Domain: { Hospital Names } Pattern: Repeats across hospitals similarly named in different cities across states; 3,699 hospitals have unique names # Records: 20,539 (none Null) 3,743 Unique Values Dependencies: Lead_Key, Entity_No Redundancies Entity_No

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Attribute: City.LEADS.HMIS Type: Text, Alphabetic (3 to 22), VCHAR(22) Domain: { City Names } Pattern: Repeats where a city has multiple hospitals. Repeats across similarly named cities in different states; 1.965 cities have unique names across all states. # Records: 20,539 (none Null) 2,255 Unique Values Dependencies: Lead_Key, Entity_No, Name Redundancies: Zip

Attribute: State.LEADS.HMIS

Type: Character, CHAR (2) Domain: {AK, AL, AR, AZ, CA, CN, CO, CT, DC, DE, FL, GA, HI, IA, ID, IL, IN, KS, KY, LA, MA, MD, ME, MI, MN, MO, MS, MT, NC, ND, NE, NH, NJ, NM, NV, NY, OH, OK, OR, PA, PR, RI, SC, SD, TN, TX, UT, VA, VT, WA, WI, WV, WY } Pattern: Repeats when a hospital has multiple HMIS (5<=n<=11); Repeats when a state has multiple cities with multiple hospitals. # Records: 53 (none Null) Dependencies: Lead_Key, Entity_No, Na me, City Redundancies: Zip

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Attribute: Zip.LEADS.HMIS Type: Character, CHAR (5) Domain: { Zip Codes of Cities } Pattern: Repeats when multiple hospitals with HMISs are located in the same postal zip code. Repeats when a hospital has multiple HMIS (5<=n<=11). # Records: 20,539 (none Null) 3556 Unique Values Median = 53209 Dependencies: Lead_Key, Entity_No, Name Redundancies: City, State

Attribute: Application.LEADS.HMIS Type: Text, Alphabetic (14 to 57), VARCHAR(40) Domain: { Computerized Practitioner Order Entry (CPOE), Electronic Data Interchange (EDI) – Clearing House Vendor, Enterprise EMR, Enterprise Resource Planning, Executive Information System } Pattern: Repeats when multiple hospitals have the same application # Records: 20,539 (none Null) 4,036 - Electronic Data Interchange (EDI) - Clearing House Vendor, 4,051 - Enterprise Resource Planning 4,106 - Executive Information System 4,159 - Computerized Practitioner Order Entry (CPOE) 4,187 - Enterprise EMR (Mode) (Median) Dependencies: Lead_Key, Entity_No, Name, Redundancies: None

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8)

Attribute: Status.LEADS.HMIS Type: Text, Alphabetic (12 to 28), VARCHAR(40) Domain: { Live and Operational, Not Automated, Contracted/Not Yet Installed, To be replaced, Not Reported, Not Yet Contracted, Installation in Progress } Pattern: Repeats when multiple hospitals have the same application status # Records: 20,539 193 - Not Yet Contracted 229 - Installation in Process 311 - To be Replaced 724 - Not Reported 1118 - Contracted/Not Yet Installed 6923 - Live and Operational 11041 - Not Automated (Median) (Mode) Dependencies: Application Redundancies: None

This additional information may be useful to salesmen –

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1. The table with Entity_no as the main key and the status of all working and non-automated applications in only one place may be useful to salespeople. 2. Total amount of applications working as opposed to applications reporting faults. 3. Live and operational application status for automated applications. In this situation, Class 3 ODS is necessary in my opinion. Daily information on the number of problems resolved and installations finished may be helpful in guiding decisions. Additionally, Not Automated is a big data set, and in order to convert or update it, a salesman needs to be proficient in it. It will also help him in his sales pitch if he knows everything there is to know about Already Automated Applications.

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