Creating a data-driven enterprise with DataOps : insights from Facebook, Uber, LinkedIn, Twitter, and eBay /

Many companies are busy collecting massive amounts of data, but few are taking advantage of this treasure horde to build a truly data insights-driven organization. To do so, the data team must democratize both data and the insights in a way that provides real-time access to all employees in the orga...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autores principales: Thusoo, Ashish (Autor), Sarma, Joydeep Sen (Autor)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Sebastopol, CA : O'Reilly Media, [2017]
Edición:First edition.
Temas:
Decision making > Data processing.
Information visualization.
Big data.
Information technology > Management.
Business enterprises > Technological innovations.
Prise de décision > Informatique.
Visualisation de l'information.
Données volumineuses.
Technologie de l'information > Gestion.
Entreprises > Innovations.
Big data
Business enterprises > Technological innovations
Decision making > Data processing
Information technology > Management
Information visualization
Acceso en línea:Texto completo (Requiere registro previo con correo institucional)
Descripción
Sumario:Many companies are busy collecting massive amounts of data, but few are taking advantage of this treasure horde to build a truly data insights-driven organization. To do so, the data team must democratize both data and the insights in a way that provides real-time access to all employees in the organization. This report explores DataOps, the process, culture, tools, and people required to scale big data pervasively across the enterprise. Just as DevOps has enabled organizations to improve coordination between developers and the operations team, DataOps closely connects everyone who handles data, including engineers, data scientists, analysts, and business users. Democratizing data with this approach requires removing barriers typical of siloed data, teams, and systems. In this report, Apache Hive creators Ashish Thusoo and Joydeep Sen Sarma examine the characteristics of a data-driven organization that supports a self-service model. Explore related topics such as data lakes, metadata, cloud architecture, and data-infrastructure-as-a-service Examine conclusions from a survey of more than 400 senior executives whose companies are in various stages of data maturity Learn how data pioneers at Facebook, Uber, LinkedIn, Twitter, and eBay created data-driven cultures and self-service data infrastructures for their organizations.
Descripción Física:1 online resource (1 volume) : illustrations
Bibliografía:Includes bibliographical references.

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