Bazy danych

Data Management Strategy at Microsoft. Best practices from a tech giant's decade-long data transformation journey

Aleksejs Plotnikovs

Microsoft pioneered data innovation and investment ahead of many in the industry, setting a remarkable standard for data maturity. Written by a data leader with over 15 years of experience following Microsoft’s data journey, this book delves into every crucial aspect of this journey, including change management, aligning with business needs, enhancing data value, and cultivating a data-driven culture.This book emphasizes that success in a data-driven enterprise goes beyond relying solely on modern technology and highlights the importance of prioritizing genuine business needs to propel necessary modernizations through change management practices. You’ll see how data-driven innovation does not solely reside within central IT engineering teams but also among the data's business owners who rely on data daily for their operational needs. This guide empower these professionals with clean, easily discoverable, and business-ready data, marking a significant breakthrough in how data is perceived and utilized throughout an enterprise. You’ll also discover advanced techniques to nurture the value of data as unique intellectual property, and differentiate your organization with the power of data.Its storytelling approach and summary of essential insights at the end of each chapter make this book invaluable for business and data leaders to advocate for crucial data investments.

Data Modeling with Snowflake. A practical guide to accelerating Snowflake development using universal data modeling techniques

Serge Gershkovich, Kent Graziano

The Snowflake Data Cloud is one of the fastest-growing platforms for data warehousing and application workloads. Snowflake's scalable, cloud-native architecture and expansive set of features and objects enables you to deliver data solutions quicker than ever before.Yet, we must ensure that these solutions are developed using recommended design patterns and accompanied by documentation that’s easily accessible to everyone in the organization.This book will help you get familiar with simple and practical data modeling frameworks that accelerate agile design and evolve with the project from concept to code. These universal principles have helped guide database design for decades, and this book pairs them with unique Snowflake-native objects and examples like never before – giving you a two-for-one crash course in theory as well as direct application.By the end of this Snowflake book, you’ll have learned how to leverage Snowflake’s innovative features, such as time travel, zero-copy cloning, and change-data-capture, to create cost-effective, efficient designs through time-tested modeling principles that are easily digestible when coupled with real-world examples.

Data Modeling with Snowflake. A practical guide to accelerating Snowflake development using universal modeling techniques - Second Edition

Serge Gershkovich, Joe Reis

Struggling with rising Snowflake costs and constant tuning? Poorly aligned data models can lead to bloated expenses, inefficient queries, and time-consuming rework. Data Modeling with Snowflake helps you harness the Snowflake Data Cloud’s scalable, cloud-native architecture and expansive feature set to deliver data solutions faster than ever.This book introduces simple, practical data modeling frameworks that accelerate agile design and evolve alongside your projects from concept to code. Rooted in decades of proven database design principles, these frameworks are paired, for the first time, with Snowflake-native objects and real-world examples, offering a two-in-one crash course in theory and direct application.Through real-world examples designed to make learning easy, you’ll leverage Snowflake’s innovative features like Time Travel, Zero-Copy Cloning, and Change Data Capture (CDC) to create cost-efficient solutions. Whether you're just starting out or refining your architecture, this book will guide you in designing smarter, scaling faster, and cutting costs by aligning timeless modeling principles with the power of Snowflake.*Email sign-up and proof of purchase required

Data Modeling with Tableau. A practical guide to building data models using Tableau Prep and Tableau Desktop

Kirk Munroe

Tableau is unlike most other BI platforms that have a single data modeling tool and enterprise data model (for example, LookML from Google’s Looker). That doesn’t mean Tableau doesn’t have enterprise data governance; it is both robust and highly flexible. This book will help you effectively use Tableau governance models to build a data-driven organization.Data Modeling with Tableau is an extensive guide, complete with step-by-step explanations of essential concepts, practical examples, and hands-on exercises. As you progress through the chapters, you’ll learn the role that Tableau Prep Builder and Tableau Desktop each play in data modeling. You’ll also explore the components of Tableau Server and Tableau Cloud that make data modeling more robust, secure, and performant. Moreover, by extending data models for Ask and Explain Data, you’ll gain the knowledge required to extend analytics to more people in their organizations, leading to better data-driven decisions. Finally, this book will guide you through the entire Tableau stack and the techniques required to build the right level of governance into Tableau data models for the correct use cases.By the end of this Tableau book, you’ll have a firm understanding of how to leverage data modeling in Tableau to benefit your organization.

Data Quality in the Age of AI. Building a foundation for AI strategy and data culture

Andrew Jones

As organizations worldwide seek to revamp their data strategies to leverage AI advancements and benefit from newfound capabilities, data quality emerges as the cornerstone for success. Without high-quality data, even the most advanced AI models falter. Enter Data Quality in the Age of AI, a detailed report that illuminates the crucial role of data quality in shaping effective data strategies.Packed with actionable insights, this report highlights the critical role of data quality in your overall data strategy. It equips teams and organizations with the knowledge and tools to thrive in the evolving AI landscape, serving as a roadmap for harnessing the power of data quality, enabling them to unlock their data's full potential, leading to improved performance, reduced costs, increased revenue, and informed strategic decisions.

Data science od podstaw. Analiza danych w Pythonie. Wydanie II

Joel Grus

Analityka danych jest uważana za wyjątkowo obiecującą dziedzinę wiedzy. Rozwija się błyskawicznie i znajduje coraz to nowsze zastosowania. Profesjonaliści biegli w eksploracji danych i wydobywaniu z nich pożytecznych informacji mogą liczyć na interesującą pracę i bardzo atrakcyjne warunki zatrudnienia. Jednak aby zostać analitykiem danych, trzeba znać matematykę i statystykę, a także nauczyć się programowania. Umiejętności w zakresie uczenia maszynowego i uczenia głębokiego również są ważne. W przypadku tak specyficznej dziedziny, jaką jest nauka o danych, szczególnie istotne jest zdobycie gruntownych podstaw i dogłębne ich zrozumienie. W tym przewodniku opisano zagadnienia związane z podstawami nauki o danych. Wyjaśniono niezbędne elementy matematyki i statystyki. Przedstawiono także techniki budowy potrzebnych narzędzi i sposoby działania najistotniejszych algorytmów. Książka została skonstruowana tak, aby poszczególne implementacje były jak najbardziej przejrzyste i zrozumiałe. Zamieszczone tu przykłady napisano w Pythonie: jest to język dość łatwy do nauki, a pracę na danych ułatwia szereg przydatnych bibliotek Pythona. W drugim wydaniu znalazły się nowe tematy, takie jak uczenie głębokie, statystyka i przetwarzanie języka naturalnego, a także działania na ogromnych zbiorach danych. Zagadnienia te często pojawiają się w pracy współczesnego analityka danych. W książce między innymi: elementy algebry liniowej, statystyki i rachunku prawdopodobieństwa zbieranie, oczyszczanie i eksploracja danych algorytmy modeli analizy danych podstawy uczenia maszynowego systemy rekomendacji i przetwarzanie języka naturalnego analiza sieci społecznościowych i algorytm MapReduce Nauka o danych: bazuj na solidnych podstawach!

Data Storytelling with Google Looker Studio. A hands-on guide to using Looker Studio for building compelling and effective dashboards

Sireesha Pulipati

Presenting data visually makes it easier for organizations and individuals to interpret and analyze information. Looker Studio is an easy-to-use, collaborative tool that enables you to transform your data into engaging visualizations. This allows you to build and share dashboards that help monitor key performance indicators, identify patterns, and generate insights to ultimately drive decisions and actions.Data Storytelling with Looker Studio begins by laying out the foundational design principles and guidelines that are essential to creating accurate, effective, and compelling data visualizations. Next, you’ll delve into features and capabilities of Looker Studio – from basic to advanced – and explore their application with examples. The subsequent chapters walk you through building dashboards with a structured three-stage process called the 3D approach using real-world examples that’ll help you understand the various design and implementation considerations. This approach involves determining the objectives and needs of the dashboard, designing its key components and layout, and developing each element of the dashboard.By the end of this book, you will have a solid understanding of the storytelling approach and be able to create data stories of your own using Looker Studio.

Data Visualization: a successful design process

Andy Kirk

Do you want to create more attractive charts? Or do you have huge data sets and need to unearth the key insights in a visual manner? Data visualization is the representation and presentation of data, using proven design techniques to bring alive the patterns, stories and key insights locked away.Data Visualization: a Successful Design Process explores the unique fusion of art and science that is data visualization; a discipline for which instinct alone is insufficient for you to succeed in enabling audiences to discover key trends, insights and discoveries from your data. This book will equip you with the key techniques required to overcome contemporary data visualization challenges. You'll discover a proven design methodology that helps you develop invaluable knowledge and practical capabilities.You'll never again settle for a default Excel chart or resort to fancy-looking graphs. You will be able to work from the starting point of acquiring, preparing and familiarizing with your data, right through to concept design. Choose your killer visual representation to engage and inform your audience.Data Visualization: a Successful Design Process will inspire you to relish any visualization project with greater confidence and bullish know-how; turning challenges into exciting design opportunities.