Gartner Research

How to Overcome the Top Four Data Quality Practice Challenges

Published: 10 March 2017

ID: G00322736

Analyst(s): Saul Judah , Mei Selvage

Summary

Poor data quality practices undermine digital initiatives, weaken organizations' competitive standing and sow customer distrust. Data and analytics leaders should strengthen their practices by measuring quality, staffing key roles, controlling tool costs and accurately estimating deployment times.

Table Of Contents
  • Key Challenges

Introduction

Analysis

  • Measure the Value of Data Quality Using the Gartner Business Value Model
  • Establish the Critical Data Quality Roles
  • Optimize the Cost of Data Quality Tools With a Bimodal and Adaptive Sourcing Approach
  • Estimate a Realistic Time Frame in Which to Deploy Data Quality Tools

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