Maturing the snowflake data cloud, Carruthers, Andrew Ahmed, Sahir

Автор: Jeffry Stra?er
Название: Integrated Risk Management of Non-Maturing Accounts
ISBN: 3658049022 ISBN-13(EAN): 9783658049027
Издательство: Springer
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Цена: 9390.00 р.
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Описание: ГЇВїВЅ Customer accounts that neither have a fixed maturity nor a fixed interest rate represent a substantial part of a consumer bank`s funding. The modelling for their risk management and pricing is a challenging yet crucial task in today`s asset/liability management, with increasing computational power allowing for new approaches.

Автор: Pericles Antoniades
Название: SOA Maturity Model
ISBN: 3319024523 ISBN-13(EAN): 9783319024523
Издательство: Springer
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Цена: 6097.00 р.
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Описание:

Companies have long sought to integrate existing Information Systems (IS) in order to support existing and potentially new business processes spread throughout their "territories" and possibly to collaborating organizations. A variety of designs can be used to this end, ranging from rigid point-to-point electronic data interchange (EDI) interactions to "Web auctions". By updating older technologies, such as "Internet-enabling" EDI-based systems, companies can make their IT systems available to internal or external customers; but the resulting systems have not proven to be flexible enough to meet business demands. A more flexible, standardized architecture is required to better support the connection of various applications and the sharing of data. Service-Oriented Architecture (SOA) is one such architecture. It unifies ("orchestrates") business processes by structuring large applications as an ad-hoc collection of smaller modules called "Services". These applications can be used by different groups of people both inside and outside the company, and new applications built from a mix of services (located in a global repository) exhibit greater agility and uniformity.

Thus, SOA is a design framework for realizing rapid and low-cost system development and improving total system quality. SOA uses the Web Services standards and technologies and is rapidly becoming a standard approach for enterprise information systems integration.

SOA adoption by enterprises has been identified as one of the highest business priorities by a recent Gartner study (Gartner 2007) and enterprises increasingly recognize the requirement for an increased "Service-orientation" and relevant comprehensive frameworks, which will not only help them position themselves and evaluate their SOA initiatives, but also guide them in achieving higher levels of SOA maturity. This in turn, will help enterprises acquire (and retain) competitive advantage over other players in the market who are not (using SOA and thus they are not) so flexibly adjusting themselves to address new business requirements.

This book proposes a new SOA Maturity Model (MM) using a Delphi-variant technique and this constitutes one of its distinguishing features because none of the relevant existing works utilized Delphi. Moreover, the fact that the proposed SOA MM supports inter-enterprise setups makes it even more distinct.

The newly proposed SOA MM is then used to help the participating organizations position themselves in respect to SOA (current status), guide them to achieve higher levels of SOA maturity, and anticipate their SOA maturity in five years' time.

Furthermore, the "local" or "global" nature of the proposed SOA MM is investigated. This is checked firstly against selected expert panel participants and secondly against local business practitioners.

Автор: L`Esteve
Название: The Azure Data Lakehouse Toolkit
ISBN: 1484282329 ISBN-13(EAN): 9781484282328
Издательство: Springer
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Цена: 7317.00 р.
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Описание: Design and implement a modern data lakehouse on the Azure Data Platform using Delta Lake, Apache Spark, Azure Databricks, Azure Synapse Analytics, and Snowflake. This book teaches you the intricate details of the Data Lakehouse Paradigm and how to efficiently design a cloud-based data lakehouse using highly performant and cutting-edge Apache Spark capabilities using Azure Databricks, Azure Synapse Analytics, and Snowflake. You will learn to write efficient PySpark code for batch and streaming ELT jobs on Azure. And you will follow along with practical, scenario-based examples showing how to apply the capabilities of Delta Lake and Apache Spark to optimize performance, and secure, share, and manage a high volume, high velocity, and high variety of data in your lakehouse with ease. The patterns of success that you acquire from reading this book will help you hone your skills to build high-performing and scalable ACID-compliant lakehouses using flexible and cost-efficient decoupled storage and compute capabilities. Extensive coverage of Delta Lake ensures that you are aware of and can benefit from all that this new, open source storage layer can offer. In addition to the deep examples on Databricks in the book, there is coverage of alternative platforms such as Synapse Analytics and Snowflake so that you can make the right platform choice for your needs. After reading this book, you will be able to implement Delta Lake capabilities, including Schema Evolution, Change Feed, Live Tables, Sharing, and Clones to enable better business intelligence and advanced analytics on your data within the Azure Data Platform. What You Will Learn * Implement the Data Lakehouse Paradigm on Microsoft’s Azure cloud platform * Benefit from the new Delta Lake open-source storage layer for data lakehouses * Take advantage of schema evolution, change feeds, live tables, and more * Write functional PySpark code for data lakehouse ELT jobs * Optimize Apache Spark performance through partitioning, indexing, and other tuning options * Choose between alternatives such as Databricks, Synapse Analytics, and Snowflake Who This Book Is For Data, analytics, and AI professionals at all levels, including data architect and data engineer practitioners. Also for data professionals seeking patterns of success by which to remain relevant as they learn to build scalable data lakehouses for their organizations and customers who are migrating into the modern Azure Data Platform.