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Additionally, it discusses correlated subqueries, joining and filtering datasets, using SQL in calculations, segmenting and classifying data, rolling analysis, and analyzing data over time. The book concludes with a chapter on advanced data presentation.
This book constitutes revised selected papers from the International Workshop on Data Quality and Trust in Big Data, QUAT 2018, which was held in conjunction with the International Conference on Web Information Systems Engineering, WISE 2018, in Dubai, UAE, in November 2018.
As data continues to grow exponentially, knowledge of data science and machine learning has become more crucial than ever. Machine learning has grown exponentially, however, the abundance of resources can be overwhelming
Many organizations today analyze and share large, sensitive datasets about individuals. Whether these datasets cover healthcare details, financial records, or exam scores,... Læs mere
With the surge in big data and AI, organizations can rapidly create data products. However, the effectiveness of their... Læs mere
Big Data Systems encompass massive challenges related to data diversity, storage mechanisms, and requirements of massive computational power. The book's purpose is... Læs mere
By following the lessons in this book, you'll be able to achieve interactive, batch, machine learning, and streaming analytics with this lakehouse. Authors Tomer Shiran, Jason Hughes, Alex Merced, and Dipankar Mazumdar from Dremio guide you through the process.
The two-volume set LNCS 13833 and LNCS 13834 constitutes the proceedings of the 29th... Læs mere