Название: The Future of Observability with OpenTelemetry
Автор: Ted Young
Издательство: O’Reilly Media, Inc.
Год: 2022
Формат: ePUB
Страниц: 75
Размер: 10 Mb
Язык: English

The world of observability is in the midst of a seismic shift. Until recently, collecting telemetry data meant running multiple, uncoordinated pipelines. Now, OpenTelemetry provides users with a single integrated stream of data, containing all common forms of observability. With this report, CTOs, analysts, system architects, and DevOps practitioners will learn how OpenTelemetry will change the way we practice observability.

Название: Microsoft Office Inside Out (Office 2021 and Microsoft 365)
Автор: Joe Habraken
Издательство: Pearson Education
Год: 2022
Формат: ePUB
Страниц: 1138
Размер: 74,6 Mb
Язык: English

Conquer Office apps in Microsoft 365 -- from the inside out!
Dive into Microsoft Office and really put its productivity tools and services to work! This supremely organized reference packs hundreds of timesaving solutions, tips, and workarounds -- all you need to make the most of Office's most powerful tools for productivity and decision-making.
Renowned Office expert Joe Habraken offers a complete tour, with cutting-edge techniques and shortcuts for Word, Excel, PowerPoint, Outlook, OneNote, and Teams. Discover how experts tackle today's key tasks -- and challenge yourself to new levels of mastery.

Название: Microsoft Excel Data Analysis and Business Modeling (Office 2021 and Microsoft 365), 7th edition
Автор: Wayne L. Winston
Издательство: Microsoft Press/Pearson Education
Год: 2022
Страниц: 1168
Язык: английский
Формат: epub
Размер: 57.9 MB

Master business modeling and analysis techniques with Microsoft Excel and Office 365 and transform data into bottom-line results. Written by award-winning educator Wayne Winston, this hands-on, scenario-focused guide helps you use Excel to ask the right questions and get accurate, actionable answers. A lot has changed in Office 365 since the previous edition. This new edition covers new functions (STOCKHISTORY, LET, LAMBDA, XLOOKUP) and new array functions. It also covers the new Data types that have been added. Finally, we've increased the coverage of Power Pivot , Macros, and Power Query.

Название: Microsoft Excel Pivot Table Data Crunching (Office 2021 and Microsoft 365)
Автор: Bill Jelen
Издательство: Pearson Education
Год: 2022
Формат: ePUB
Страниц: 979
Размер: 30 MB
Язык: English

Renowned Excel expert Bill Jelen (MrExcel) helps you crunch data from any source with Excel pivot tables.
Use Excel pivot tables and pivot charts to produce powerful, dynamic reports in minutes instead of hours, to take control of your data and your business. Even if you’ve never created a pivot table before, this book will help you leverage all their remarkable flexibility and analytical powerincluding valuable improvements in Excel and Excel in Office 365. Drawing on years of Excel experience, Bill Jelen offers practical “recipes” for solving real business problems, helps you avoid common mistakes, and presents tips and tricks you’ll find nowhere else.

Название: Common Data Sense for Professionals: A Process-Oriented Approach for Data-Science Projects
Автор: Rajesh Jugulum
Издательство: Routledge
Год: 2022
Страниц: 123
Язык: английский
Формат: pdf (true)
Размер: 10.2 MB

Data is an intrinsic part of our daily lives. Everything we do is a data point. Many of these data points are recorded with the intent to help us lead more efficient lives. We have apps that track our workouts, sleep, food intake, and personal finance. We use the data to make changes to our lives based on goals we have set for ourselves. Businesses use vast collections of data to determine strategy and marketing. Data scientists take data, analyze it, and create models to help solve problems. The goal of this book is to provide a step-by-step guide to the Data Science process so that you can feel confident in leading your own data science project. Although this book is intended to help regular people by providing a step-by-step guide with simple game plans/strategies, it is important to have the right tools. The later chapters of the book will address data collection, model building, and analysis of data. In order to properly analyze data and begin model building, you will need access to data analytics software programs. The software will help you sort through your data and manipulate your data in order to gather insights. The choice of your software has no influence on the overall data science process.

Название: Data Science in Engineering and Management: Applications, New Developments, and Future Trends
Автор: Zdzislaw Polkowski, Sambit Kumar Mishra, Julian Vasilev
Издательство: CRC Press
Год: 2022
Формат: PDF
Страниц: 161
Размер: 12,5 Mb
Язык: English

This book brings insight into data science and offers applications and implementation strategies. It includes current developments and future directions and covers the concept of data science along with its origins. It focuses on the mechanisms of extracting data along with classifications, architectural concepts, and business intelligence with predictive analysis.

Название: Data Mesh in Practice: How to Set Up a Data-Driven Organization
Автор: Max Schultze, Arif Wider
Издательство: O’Reilly Media, Inc.
Год: 2021-12-16
Язык: английский
Формат: pdf, epub
Размер: 10.2 MB

The data mesh is poised to replace data lakes and data warehouses as the dominant architectural pattern in data and analytics. By promoting the concept of domain-focused data products that go beyond file sharing, data mesh helps you deal with data quality at scale by establishing true data ownership. This approach is so new, however, that many misconceptions and a general lack of practical experience for implementing data mesh are widespread. With this report, you'll learn how to successfully overcome challenges in the adoption process. By drawing on their experience building large-scale data infrastructure, designing data architectures, and contributing to data strategies of large and successful corporations, authors Max Schultze and Arif Wider have identified the most common pain points along the data mesh journey.

Название: Building Solutions with the Microsoft Power Platform: Solving Everyday Problems in the Enterprise (Early Release)
Автор: Jason Rivera
Издательство: O’Reilly Media, Inc.
Год: 2021-12-14
Язык: английский
Формат: pdf, epub
Размер: 10.2 MB

With the accelerating speed of business and the increasing dependence on technology, companies today are significantly changing the way they build in-house business solutions. Many now use low-code and no code technologies to help them deal with specific issues, but that's just the beginning. With this practical guide, power users and developers will discover ways to resolve everyday challenges by building end-to-end solutions with the Microsoft Power Platform. Author Jason Rivera, who specializes in SharePoint and the Microsoft 365 solution architecture, provides a comprehensive overview of how to use the Power Platform to build end-to-end solutions that address tactical business needs. By learning key components of the platform, including Power Apps, Power Automate, and Power BI, you'll be able to build low-code and no code applications, automate repeatable business processes, and create interactive reports from available data.

Название: On the Epistemology of Data Science: Conceptual Tools for a New Inductivism
Автор: Wolfgang Pietsch
Издательство: Springer
Год: 2022
Страниц: 308
Язык: английский
Формат: pdf (true)
Размер: 10.0 MB

This book addresses controversies concerning the epistemological foundations of Data Science: Is it a genuine science? Or is Data Science merely some inferior practice that can at best contribute to the scientific enterprise, but cannot stand on its own? The author proposes a coherent conceptual framework with which these questions can be rigorously addressed. The inductivist framework is shown to be adequate and useful for an analysis of the epistemological foundations of Data Science. The author points out that many aspects of the variational rationale are present in algorithms commonly used in Data Science. Introductions to algorithms and brief case studies of successful Data Science such as machine translation are included. Data Science is located with reference to several crucial distinctions regarding different kinds of scientific practices, including between exploratory and theory-driven experimentation, and between phenomenological and theoretical science. Computer scientists, philosophers and data scientists of various disciplines will find this philosophical perspective and conceptual framework of great interest, especially as a starting point for further in-depth analysis of algorithms used in Data Science.

Название: Data Science: Time Complexity, Inferential Uncertainty, and Spacekime Analytics
Автор: Ivo D. Dinov, Milen Velchev Velev
Издательство: De Gruyter
Год: 2022
Страниц: 490
Язык: английский
Формат: pdf (true)
Размер: 10.1 MB

The amount of new information is constantly increasing, faster than our ability to fully interpret and utilize it to improve human experiences. Addressing this asymmetry requires novel and revolutionary scientific methods and effective human and Artificial Intelligence interfaces. By lifting the concept of time from a positive real number to a 2D complex time (kime), this book uncovers a connection between Artificial Intelligence (AI), Data Science, and quantum mechanics. It proposes a new mathematical foundation for Data Science based on raising the 4D spacetime to a higher dimension where longitudinal data (e.g., time-series) are represented as manifolds (e.g., kime-surfaces). This new framework enables the development of innovative Data Science analytical methods for model-based and model-free scientific inference, derived computed phenotyping, and statistical forecasting. The book provides a transdisciplinary bridge and a pragmatic mechanism to translate quantum mechanical principles, such as particles and wavefunctions, into Data Science concepts, such as datum and inference-functions.