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Data Pipelines Pocket Reference Moving and Processing Data for Analytics

Data pipelines are the foundation for success in data analytics. Moving data from numerous diverse sources and transforming it to provide;

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The Definitive Guide to Azure Data Engineering

Build efficient and scalable batch and real-time data ingestion pipelines, DevOps continuous integration and deployment pipelines, and;

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Multimodal Analytics for Next-Generation Big Data Technologies and Applications

This edited book will serve as a source of reference for technologies and applications for multimodality data analytics in big data;

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Big Data Analytics for Time-Critical Mobility Forecasting

This book provides detailed descriptions of big data solutions for activity detection and forecasting of very large numbers of moving;

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Big Data Analytics for Time-Critical Mobility Forecasting

This book provides detailed descriptions of big data solutions for activity detection and forecasting of very large numbers of moving;

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Understanding Azure Data Factory

of operationalizing the pipelines and ETL with SSIS is included. You will know how to leverage Azure Data Factory to run existing SSIS packages. As you;

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Beginning Azure Synapse Analytics

analyze your big data using Serverless Synapse SQL Pool. You also will learn Synapse Spark and Synapse Pipelines, with examples. And you will;

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Big Data Analytics

A handy reference guide for data analysts and data scientists to help to obtain value from big data analytics using Spark on Hadoop;

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Large Scale and Big Data

currently available for large-scale data processing. Presenting chapters written by leading researchers, academics, and practitioners, it addresses;

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Large Scale and Big Data

currently available for large-scale data processing. Presenting chapters written by leading researchers, academics, and practitioners, it addresses;

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Beginning Apache Spark 3

efficient distributed data processing engine inside of Apache Spark; its user-friendly, comprehensive, and flexible programming model for processing;

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Machine Learning Pocket Reference Working with Structured Data in Python

your next machine learning project. Ideal for programmers, data scientists, and AI engineers, this book includes an overview of the machine;

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Distributed Computing in Big Data Analytics

considerations that make big data analytics possible within stipulated cost and time practical for consumption by human and machines. However, the;

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Spring Cloud Data Flow

integration, real-time analytics and data processing pipelines, batch processing, and data export. With this book you will develop a foundation for;

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Programming Pig

flow language for building and maintaining pipelines for processing data. Advanced users learn how to build complex data processing pipelines;

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Mapping Data Flows in Azure Data Factory

Mapping Data Flows Apply best practices for designing and managing complex ETL data pipelines in Azure Data Factory Add cloud-based ETL patterns;

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Big Data Analytics for Sustainable Computing

Big data consists of data sets that are too large and complex for traditional data processing and data management applications. Therefore;

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Business Intelligence and Data Warehousing

Business Intelligence and Data Warehousing deals with the main components of a data warehouse for business intelligence applications;

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Self-Service Data Analytics and Governance for Managers

Motivated by the promise of control and efficiency benefits, the widespread adoption of data analytics tools has created a new fast-moving;

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Handbook of Big Data Analytics: Applications in ICT, security and business analytics

work is aimed at providing a unique platform for researchers, engineers, developers, educators and advanced students in the field of Big Data;

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Learning Spark

Data is getting bigger, arriving faster, and coming in varied formats-and it all needs to be processed at scale for analytics or machine;

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Real-Time Big Data Analytics

explore the techniques and programming concepts using Apache Storm. Moving on, we'll familiarize you with Amazon Kinesis for real-time data;

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Handbook of Big Data Analytics: Methodologies

work is aimed at providing a unique platform for researchers, engineers, developers, educators and advanced students in the field of Big Data;

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Knowledge Graphs and Big Data Processing

of the definitions, methods, tools, frameworks, and solutions for big data processing, starting from the process of information extraction and;

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Big Data Processing With Hadoop

Due to the increasing availability of affordable internet services, the number of users, and the need for a wider range of multimedia-based;

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Big Data Analytics with Hadoop 3

Spark and Apache Flink for real-time data analytics and stream processing. In addition to this, you will understand how to use Hadoop to build;

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Artificial Intelligence and Big Data Analytics for Smart Healthcare

Artificial Intelligence and Big Data Analytics for Smart Healthcare serves as a key reference for practitioners and experts involved;

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