Discover how to achieve business goals by relying on high-quality, robust data
In Data Quality: Empowering Businesses with Analytics and AI, veteran data and analytics professional delivers a practical and hands-on discussion on how to accelerate business results using high-quality data. In the book, you'll learn techniques to define and assess data quality, discover how to ensure that your firm's data collection practices avoid common pitfalls and deficiencies, improve the level of data quality in the business, and guarantee that the resulting data is useful for powering high-level analytics and AI applications.
The author shows you how to:
An essential resource for data scientists, data analysts, business intelligence professionals, chief technology and data officers, and anyone else with a stake in collecting and using high-quality data, Data Quality: Empowering Businesses with Analytics and AI will also earn a place on the bookshelves of business leaders interested in learning more about what sets robust data apart from the rest.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
PRASHANTH SOUTHEKAL, PHD, is a data, analytics, and AI consultant, author, and professor. He has worked and consulted for over 80 organizations including P&G, GE, Shell, Apple, FedEx, and SAP. Dr. Southekal is the author of Data for Business Performance and Analytics Best Practices (ranked #1 analytics books of all time by BookAuthority) and writes regularly on data, analytics, and AI in Forbes and CFO.University. He serves on the Editorial Board of MIT CDOIQ Symposium and is an advisory board member at BGV (Benhamou Global Ventures) a Silicon Valley-based venture capital firm. Apart from his consulting and advisory pursuits, he has trained over 3,000 professionals worldwide in data and analytics. Dr. Southekal is also an adjunct professor of data and analytics at IE Business School (Madrid, Spain). CDO Magazine included him in the top 75 global academic data leaders of 2022. He holds a PhD from ESC Lille (FR), an MBA from the Kellogg School of Management (US), and holds the ICD.D designation from the Institute of Corporate Directors (Canada).
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Hardback. Etat : New. Discover how to achieve business goals by relying on high-quality, robust data In Data Quality: Empowering Businesses with Analytics and AI, veteran data and analytics professional delivers a practical and hands-on discussion on how to accelerate business results using high-quality data. In the book, you'll learn techniques to define and assess data quality, discover how to ensure that your firm's data collection practices avoid common pitfalls and deficiencies, improve the level of data quality in the business, and guarantee that the resulting data is useful for powering high-level analytics and AI applications. The author shows you how to: Profile for data quality, including the appropriate techniques, criteria, and KPIs Identify the root causes of data quality issues in the business apart from discussing the 16 common root causes that degrade data quality in the organization.Formulate the reference architecture for data quality, including practical design patterns for remediating data qualityImplement the 10 best data quality practices and the required capabilities for improving operations, compliance, and decision-making capabilities in the businessAn essential resource for data scientists, data analysts, business intelligence professionals, chief technology and data officers, and anyone else with a stake in collecting and using high-quality data, Data Quality: Empowering Businesses with Analytics and AI will also earn a place on the bookshelves of business leaders interested in learning more about what sets robust data apart from the rest. N° de réf. du vendeur LU-9781394165230
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Hardcover. Etat : new. Hardcover. Discover how to achieve business goals by relying on high-quality, robust data In Data Quality: Empowering Businesses with Analytics and AI, veteran data and analytics professional delivers a practical and hands-on discussion on how to accelerate business results using high-quality data. In the book, youll learn techniques to define and assess data quality, discover how to ensure that your firms data collection practices avoid common pitfalls and deficiencies, improve the level of data quality in the business, and guarantee that the resulting data is useful for powering high-level analytics and AI applications. The author shows you how to: Profile for data quality, including the appropriate techniques, criteria, and KPIs Identify the root causes of data quality issues in the business apart from discussing the 16 common root causes that degrade data quality in the organization.Formulate the reference architecture for data quality, including practical design patterns for remediating data qualityImplement the 10 best data quality practices and the required capabilities for improving operations, compliance, and decision-making capabilities in the businessAn essential resource for data scientists, data analysts, business intelligence professionals, chief technology and data officers, and anyone else with a stake in collecting and using high-quality data, Data Quality: Empowering Businesses with Analytics and AI will also earn a place on the bookshelves of business leaders interested in learning more about what sets robust data apart from the rest. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9781394165230
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Hardback. Etat : New. Discover how to achieve business goals by relying on high-quality, robust data In Data Quality: Empowering Businesses with Analytics and AI, veteran data and analytics professional delivers a practical and hands-on discussion on how to accelerate business results using high-quality data. In the book, you'll learn techniques to define and assess data quality, discover how to ensure that your firm's data collection practices avoid common pitfalls and deficiencies, improve the level of data quality in the business, and guarantee that the resulting data is useful for powering high-level analytics and AI applications. The author shows you how to: Profile for data quality, including the appropriate techniques, criteria, and KPIs Identify the root causes of data quality issues in the business apart from discussing the 16 common root causes that degrade data quality in the organization.Formulate the reference architecture for data quality, including practical design patterns for remediating data qualityImplement the 10 best data quality practices and the required capabilities for improving operations, compliance, and decision-making capabilities in the businessAn essential resource for data scientists, data analysts, business intelligence professionals, chief technology and data officers, and anyone else with a stake in collecting and using high-quality data, Data Quality: Empowering Businesses with Analytics and AI will also earn a place on the bookshelves of business leaders interested in learning more about what sets robust data apart from the rest. N° de réf. du vendeur LU-9781394165230
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Hardcover. Etat : Fine. Abnutzung / Risse - leicht; Vergilbt / ausgeblichen. Kvalitni data jsou klicem pro podniky, aby dosahovaly lepsiho vykonu v operacich, dodrzovani predpisu a rozhodovani. Vetsina spolecnosti vsak trpi spatnou kvalitou dat. Studie HBR zjistila, ze pouze 3 % dat v podnikovych organizacich splnuje standardy kvality. Podle Gartneru je 27 % dat ve svetovych prednich spolecnostech vadnych, a proto spolecnosti hledaji prakticke pokyny pro zlepseni kvality dat. Tato kniha zkouma ctyrfazovy pristup DARS (Definovat-Hodnotit-Uvedomit si-Udrzet) pro spravu kvalitnich dat v organizacich. Tento pristup poskytuje kombinaci strategickych a taktickych prvku, aby prinesl co nejvetsi hodnotu z dat pro podnik. Je to prirucka, ktera nabizi preskriptivni doporuceni na zaklade osvedcenych praktik pro realizaci a udrzeni kvality dat. N° de réf. du vendeur ee1ad396-2a61-49fe-a924-ccbbccabc06b
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