Gartner Research

How to Overcome the Top Four Data Quality Practice Challenges

Published: 31 October 2018

ID: G00370434

Analyst(s): Saul Judah , Melody Chien

Summary

Poor data quality undermines digital initiatives and contributes to wrong decision making, weakened competitive standing and customer distrust. To strengthen their practices, data and analytics leaders must measure quality, staff key roles, establish governance and adopt flexible deployment models.

Table Of Contents
  • Key Challenges

Introduction

Analysis

  • Measure the Value of Data Quality by Using the Gartner Business Value Model and Linking to Business Performance Metrics
  • Position Key Data Quality Roles for Most Business Impact
  • Establish an Effective Data Governance Framework
  • Facilitate the Data Quality Tool Deployments With the Flexible Sourcing Approach and Cloud-Based Deployment Models

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