Data lakes
Material type:
TextLanguage: English Publication details: New Jersey: Wiley Data and Cybersecurity, 2020. Edition: 1st edDescription: xii, 221pISBN: 9781119720423Subject(s): Architecture of Data Lakes | Metadata in Data Lake Ecosystems | Master Data and Reference Data in Data Lake EcosystemsDDC classification: 005.7 Online resources: Click here to access online
| Item type | Current library | Call number | Status | Date due | Barcode |
|---|---|---|---|---|---|
| e-Books | Dr. S. R. Ranganathan Library Ebook (Online Access) | 005.7 (Browse shelf(Opens below)) | Available | EB0118 |
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| 005.55 (Online Access) A data scientist's guide to acquiring, cleaning, and managing data in R | 005.55 (Online Access) Automated data collection with R: A practical guide to web scraping and text mining | 005.55 (Online Access) Data science fundamentals with R, python, and open data | 005.7 Data lakes | 005.7 Sharing economy and big data analytics | 005.7 (Online Access) Big data analytics for internet of things | 005.7 (Online Access) Big data and differential privacy: analysis strategies for railway track engineering |
The concept of a data lake is less than 10 years old, but they are already hugely implemented within large companies. Their goal is to efficiently deal with ever-growing volumes of heterogeneous data, while also facing various sophisticated user needs. However, defining and building a data lake is still a challenge, as no consensus has been reached so far. Data Lakes presents recent outcomes and trends in the field of data repositories. The main topics discussed are the data-driven architecture of a data lake; the management of metadata – supplying key information about the stored data, master data and reference data; the roles of linked data and fog computing in a data lake ecosystem; and how gravity principles apply in the context of data lakes. A variety of case studies are also presented, thus providing the reader with practical examples of data lake management