The conference proceedings - Multidisciplinary Academic Conference on Education, Teaching and Learning, Czech Republic, Prague (MAC-ETL 2016)

Multidisciplinary Academic Conference on Education, Teaching and Learning, Czech Republic, Prague (MAC-ETL 2018) Multidisciplinary Academic Conference on Management, Marketing and Economics, Czech Republic, Prague (MAC-MME 2018) Multidisciplinary Academic Conference on Transport, Tourism and Sport Science, Czech Republic, Prague (MAC-TTSS 2018) Friday - Sunday, December 7 - 9, 2018

International Academic Conference on Education, Teaching and Learning in Prague 2017 and International Academic Conference on Management, Marketing and Economics in Prague 2017 and International Academic Conference on Transport, Tourism and Sport Science in Prague 2017

Multidisciplinary Academic Conference on Education, Teaching and Learning, Czech Republic, Prague (MAC-ETL 2019) Multidisciplinary Academic Conference on Management, Marketing and Economics, Czech Republic, Prague (MAC-MME 2019) Multidisciplinary Academic Conference on Transport, Tourism and Sport Science, Czech Republic, Prague (MAC-TTSS 2019)

Multidisciplinary Academic Conference on Education, Teaching and Learning, Czech Republic, Prague (MAC-ETL 2020) Multidisciplinary Academic Conference on Management, Marketing and Economics, Czech Republic, Prague (MAC-MME 2020) Saturday - Sunday, December 5 - 6, 2020

Harness the power of SQL Server 2017 Integration Services to build your data integration solutions with ease About This Book Acquaint yourself with all the newly introduced features in SQL Server 2017 Integration Services Program and extend your packages to enhance their functionality This detailed, step-by-step guide covers everything you need to develop efficient data integration and data transformation solutions for your organization Who This Book Is For This book is ideal for software engineers, DW/ETL architects, and ETL developers who need to create a new, or enhance an existing, ETL implementation with SQL Server 2017 Integration Services. This book would also be good for individuals who develop ETL solutions that use SSIS and are keen to learn the new features and capabilities in SSIS 2017. What You Will Learn Understand the key components of an ETL solution using SQL Server 2016-2017 Integration Services Design the architecture of a modern ETL solution Have a good knowledge of the new capabilities and features added to Integration Services Implement ETL solutions using Integration Services for both on-premises and Azure data Improve the performance and scalability of an ETL solution Enhance the ETL solution using a custom framework Be able to work on the ETL solution with many other developers and have common design paradigms or techniques Effectively use scripting to solve complex data issues In Detail SQL Server Integration Services is a tool that facilitates data extraction, consolidation, and loading options (ETL), SQL Server coding enhancements, data warehousing, and customizations. With the help of the recipes in this book, you'll gain complete hands-on experience of SSIS 2017 as well as the 2016 new features, design and development improvements including SCD, Tuning, and Customizations. At the start, you'll learn to install and set up SSIS as well other SQL Server resources to make optimal use of this Business Intelligence tools. We'll begin by taking you through the new features in SSIS 2016/2017 and implementing the necessary features to get a modern scalable ETL solution that fits the modern data warehouse. Through the course of chapters, you will learn how to design and build SSIS data warehouses packages using SQL Server Data Tools. Additionally, you'll learn to develop SSIS packages designed to maintain a data warehouse using the Data Flow and other control flow tasks. You'll also be demonstrated many recipes on cleansing data and how to get the end result after applying different transformations. Some real-world scenarios that you might face are also covered and how to handle various issues that you might face when designing your packages. At the end of this book, you'll get to know all the key concepts to perform data integration and transformation. You'll have explored on-premises Big Data integration processes to create a classic data warehouse, and will know how to extend the toolbox with custom tasks and transforms. Style and approach This cookbook follows a problem-solution approach and tackles all kinds of data integration scenarios by using the capabilities of SQL Server 2016 Integration Services. This book is well supplemented with screenshots, tips, and tricks. Each recipe focuses on a particular task and is written in a very easy-to-follow manner.

Apache Spark is a popular open-source big-data processing framework thatÕs built around speed, ease of use, and unified distributed computing architecture. Not only it supports developing applications in different languages like Java, Scala, Python, and R, itÕs also hundred times faster in memory and ten times faster even when running on disk compared to traditional data processing frameworks. Whether you are currently working on a big data project or interested in learning more about topics like machine learning, streaming data processing, and graph data analytics, this book is for you. You can learn about Apache Spark and develop Spark programs for various use cases in big data analytics using the code examples provided. This book covers all the libraries in Spark ecosystem: Spark Core, Spark SQL, Spark Streaming, Spark ML, and Spark GraphX.

Learn how to use, deploy, and maintain Apache Spark with this comprehensive guide, written by the creators of the open-source cluster-computing framework. With an emphasis on improvements and new features in Spark 2.0, authors Bill Chambers and Matei Zaharia break down Spark topics into distinct sections, each with unique goals. Youâ??ll explore the basic operations and common functions of Sparkâ??s structured APIs, as well as Structured Streaming, a new high-level API for building end-to-end streaming applications. Developers and system administrators will learn the fundamentals of monitoring, tuning, and debugging Spark, and explore machine learning techniques and scenarios for employing MLlib, Sparkâ??s scalable machine-learning library. Get a gentle overview of big data and Spark Learn about DataFrames, SQL, and Datasetsâ??Sparkâ??s core APIsâ??through worked examples Dive into Sparkâ??s low-level APIs, RDDs, and execution of SQL and DataFrames Understand how Spark runs on a cluster Debug, monitor, and tune Spark clusters and applications Learn the power of Structured Streaming, Sparkâ??s stream-processing engine Learn how you can apply MLlib to a variety of problems, including classification or recommendation

This powerful, unsettling book gives us a rare glimpse behind the closed doors of global financial institutions by the winner of the 2001 Nobel Prize in Economics. When it was first published, this national bestseller quickly became a touchstone in the globalization debate. Renowned economist and Nobel Prize winner Joseph E. Stiglitz had a ringside seat for most of the major economic events of the last decade, including stints as chairman of the Council of Economic Advisers and chief economist at the World Bank. Particularly concerned with the plight of the developing nations, he became increasingly disillusioned as he saw the International Monetary Fund and other major institutions put the interests of Wall Street and the financial community ahead of the poorer nations. Those seeking to understand why globalization has engendered the hostility of protesters in Seattle and Genoa will find the reasons here. While this book includes no simple formula on how to make globalization work, Stiglitz provides a reform agenda that will provoke debate for years to come. Rarely do we get such an insider's analysis of the major institutions of globalization as in this penetrating book. With a new foreword for this paperback edition.