HMIS DATA QUALITY Flashcards

1
Q

data quality has become a major concern for large companies like in the areas of;

A

Customer Relationship Management (CRM)
data integration
regulation requirements

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2
Q

overall utility of a dataset (s) as a function of its ability to be processed easily and analyzed for a database.

A

Data Quality

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3
Q

it is done to raise the quality of available data

A

Data Cleansing

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4
Q

Aspects of Data Quality

A

accuracy
completeness
update status
relevance
consistency
reliability
appropriate presentation
accessibility

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5
Q

LQAS?

A

Lot Quality Assessment Sampling

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6
Q

allows the use of small random samples to distinguish between different groups of data elements

A

LQAS

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7
Q

tool that is simplified version of the data quality audit

A

routine data quality assessment

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8
Q

it allows programs and projects to verify and assess the quality of their reported data.

A

Routine Data Quality Assessment

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9
Q

Objectives of RDQA

A

Verify Rapidly
Implement
Monitor

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10
Q

aims to strengthen their data management and reporting systems

A

RDQA

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11
Q

the potential users of RDQA

A

program managers
supervisors
M & E staff at national and subnational levels
donors and stakeholders

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12
Q

a project management tool that shows how a project will evolve at a high level. the plan validates the estimation and schedule of the project plan

A

Implementation Plan

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13
Q

It helps ensure that a development team is working to deliver and complete tasks on time. people involved in the project will not encounter any issues

A

Implementation Plan

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14
Q

Implementation Plans Key Components

A

Define Goals and Objectives
Schedule Milestones
Allocate Resources
Designate Team Member Responsibilities
Define Metrics for Success

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15
Q

It answers the question “what do you want to accomplish”

A

define goals/objectives

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16
Q

outline the high level schedule in the implementation phase

A

schedule milestones

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17
Q

determine whether you have sufficient resources and decide how you will procure what is missing

A

Allocate resources

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18
Q

Create a general team plan with overall roles that each team member will play

A

designate team member responsibilities

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19
Q

how will you determine if you have achieved your goal?

A

define metrics for success

20
Q

it analyzed information and identifies incomplete or incorrect data

A

data quality tools

21
Q

analyze the problem by parts and one by one

A

Parsing

22
Q

the decomposition of fields into component parts and formatting the values into consistent layouts based on industry standards and patterns and user-defined business rules.

A

Parsing and Standardization

23
Q

the modification of data values to meet domain restrictions, constraints on integrity, or other rules that define data quality as sufficient for the organization

A

Generalized “Cleansing”

24
Q

identification and merging related entries within or across data sets

A

Matching

25
Q

the deployment of controls to ensure conformity of data to business rules set by the organization.

A

Monitoring

26
Q

enhancing the value of the data using related attributes

A

Enrichment

27
Q

he defined data quality tools as being used to address data quality problem

A

Gartner (2017)

28
Q

designed to address normalization and de-duplication

A

first generation of data tools

29
Q

allowed the optimization of the alimentation process

A

Extract, Transform, Load (ETL) Tools

30
Q

generally integrate profiling, parsing, standardization, cleansing, and matching processes

A

Data Quality Management (DQM)

31
Q

a class of problem-solving methods . aims to identify the root cause of the problem or events. improve the quality of products by using systematic ways

A

Root Cause Analysis

32
Q

done by identifying the problem at hand and progressively unveiling the underlying causes

A

asking WHY 5 times

33
Q

it identifies modes in system failure

A

Failure Mode and Effects Analysis (FMEA)

34
Q

20% of the work creates 80% of the results.
helpful when there are multiple causes to a problem
charts are excel or another program

A

Pareto Analysis

35
Q

uses “Boolean Logic”
listed in a diagram shaped like an inverted tree
commonly used in risk analysis and safety analysis

A

Fault Tree Analysis

36
Q

algebraic where results are calculated by true or false

A

Boolean Logic

37
Q

used in risk analysis and safety analysis

A

Fault Tree Analysis

38
Q

to get to the root causes of all problems at once
If -then statements are used in charting problems

A

Current Reality Tree

39
Q

categorizes the causes into:
people
measurements
methods
materials
environment
machines

A

Fishbone-Ishikawa-Cause and Effect

40
Q

breaks down a problem to its root cause/s by identifying and appraising the situation

A

Kepner-Tregoe Technique

41
Q

the causes of recurrent problems are diagnosed in three phases

A

(Rapid Problem Resolution) RPR Problem Diagnosis

42
Q

gather data and analyze findings

A

Discover

43
Q

come up with a diagnostic plan and carefully analyze the diagnostic data

A

Investigate

44
Q

problem is fixed and continuously monitored

A

Fix

45
Q

3 Phases of RPR

A

Discover
Investigate
Fix

46
Q

affects the information outcomes
can also be shaped by cognitive and epistemic expectations influenced by the way how tasks are performed and decisions are made

A

Information Culture

47
Q

information culture are determined variables

A

Mission
History
Leadership
Employee Traits
Industry
National Culture