Data Quality

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Last updated 4:22 AM on 12/7/23
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35 Terms

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Data quality tool

Analyzes information and edintifies incomplete or incorrect data.

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Generalized "cleansing"

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

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District Health Information System

LWAS was adopted in the context of?

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Routine Data Quality Assessment (RDQA)

it aims to strengthen their data management and reporting system

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Schedule Milestone

Key component of an implementation plan that outlines the high level schedule in the implementation phase

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Parsing and Standardization

Refers to 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

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Matching

This is the identification and merging related entries within or across data sets

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Enrichment

Enhancing the value of the data by using related attributes from external sources such as consumer demographic attributes or geographic descriptors

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Kepner-Tregoe Technique

It is also known as a rational process intended to break a problem down to its root cause.

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RPR Problem Diagnosis

It deals with diagnosing the causes of recurrent problems. This has three phases; discover, investigate, ans fix.

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Data Quality

Is the overall utility of a database as a function of its ability to be processed easily and analyzed for a database, data warehouse, or data analytics system.

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Lot Quality Assessment Sampling (LQAS)

Is a tool that allows the use of small random samples to distinguish between different groups of data elements or Lots with high and low data quality

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Routine Data Quality Assessment Tool (RDQA)

Is a simplified version of the Data Quality Audit (DQA) which allows programs and projects to verify and assess the quality of their reported data.

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Verify rapidly, implement, and monitor

What are the objectives of RDQA?

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Implementation Plan

is a project management tool that shows how a project will evolve at a high level. It helps ensure that a development team is working to deliver and complete tasks on time.

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Goals/Objectives

Key components of an Implementation plan that answers the question "What do you want to accomplish?"

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Allocate Resources

Key component of an implementation plan that determines whether you have sufficient resources and decide how you will procure what's missing

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Designate Team member responsibilities

Key component of an implementation plan that create a general team plan with overall roles that each member will play

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Define Metrics for success

Key component on an implementation plan that defines how you will determine if you have achieved your goal

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Profiling

Refers to the analysis of data to capture statistics or metadata to determine the quality of the data and identify data quality issues

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Monitoring

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

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Root cause analysis

Is a class of problem solving methods aimed at identifying the root causes of the problems or events instead of simply addressing the obvious symptoms.

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Root cause analysis

Aims to improve the quality of the products by using systematic ways in order to be effective

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Pareto anaylsis

Operates using pareto analysis principles (20% of the work creates 80% of the results). You will want to run this any time when there are multiple potential causes to a peoblem

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Fault tree analysis

Uses boolean logic to determine the root causes of an undesirable event. This technique is usually used in risk analysis and safety analysis.

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Current tree reality

This technique analyzes a system at once. It would be used when many problems exist and you want to get to the root causes of all the problems.

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Fishbone or Ishikawa or Cause-and-Effect Diagrams

This technique will group causes into categories including people, measurements, methods, materials, environment, machines.

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Fishbone or Ishikawa or Cause and effect diagrams

People, Measurements, Methods, Materials, Environment, Machines

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Parsing and standardization, generalized cleansing, matching, profiling, monitoring, enrichment

What are the data quality tools used to address the data quality problem?

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Goals/Objectives, Schedule milestone, allocate resources, designate team member respinsibilites, define metrics for success

What are the key components of an implementation plan?

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Accuracy, completeness, relevance, consistency, reliability, presentability, accessbility

What are the aspects of data quality?

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Ask why 5 times, Failure mode and effective analysis, Pareto analysis, fault tree analysis, Current reality tree, fishbone or ishikawa or cause and effect diagram, kepner-tregoe technique, rapud problem resolution

What are the techniques in root cause analysis?

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Ask why 5 times

Asking why 5 times and getting progressively deeper into the problem

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Failure mode of effects analysis

A technique which is aimed to find various modes for failure within a system

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Data quality 101

These tools starter to focus on data wuality management, which generally integrate profiling, parsing, standardization, cleansing and matching processes.