Data Quality

数据质量:用分析与人工智能赋能企业

计算机科学技术基础学科

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作      者
出  版 社
出版时间
2023年01月03日
装      帧
精装
ISBN
9781394165230
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页      码
304
开      本
15.24 x 22.86 cm.
语      种
英文
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图书简介
Quality data is the key for business enterprises to offer improved performance in operations, compliance, and decision making. According to McKinsey, data driven organizations provide EBITDA increases between 15 to 25% than peers. However, to be a data driven organization, data quality is very important. But most companies are plagued with poor data quality. A HBR study found that just 3% of the data in a business enterprise meets quality standards. According to Gartner, 27% of data in the worlds top companies is flawed--so companies are looking for practical guidance to improve data quality. This book examines the four-phase DARS approach (Define-Assess-Realize-Sustain) for companies to manage high quality data in organizations. This approach provides a combination of strategy and tactical elements to deliver the greatest value from data to the business. It is a playbook that offers prescriptive recommendations based on proven best practices to realize and sustain data quality.
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