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: Microsoft Project For Dummies
: Cynthia Snyder Dionisio
: For Dummies
: 2022
: True PDF
: 384
: 13 Mb
: English

Blow past the jargon and get hands-on, practical guidance on managing any project with Microsoft Project
Lean. Agile. Hybrid. It seems that project management these days comes with more confusing buzzwords than ever. But you can make managing your next project simple and straightforward with help from Microsoft Project For Dummies.
This book unpacks Microsoft's bestselling project management platform and walks you through every important feature, step-by-step, until you're ready to take on virtually any project, no matter the size. From getting set up for the first time to creating tasks, managing resources and working with time management features, you'll learn everything you need to know about managing a project in Microsoft's iconic software.
: vitvikvas 14-01-2022, 17:42 | : 0 |

: Android
: ..
: --; :
: 2020
: pdf, djvu
: 116
: 11 mb
:

Android Android, Kotlin Java. Kotlin, , , API.
: na5ballov 14-01-2022, 17:25 | : 0 |
Snowflake: The Definitive Guide: Architecting, Designing, and Deploying on the Snowflake Data Cloud (Fourth Early Release): Snowflake: The Definitive Guide: Architecting, Designing, and Deploying on the Snowflake Data Cloud (Fourth Early Release)
: Joyce Kay Avila
: OReilly Media, Inc.
: 2021-12-17
: 221
:
: pdf, epub
: 11.8 MB

Snowflake's ability to eliminate data silos and run workloads from a single platform creates opportunities to democratize data analytics, allowing users at all levels within an organization to make data-driven decisions. This clear, comprehensive guide will show you how to build integrated data applications and develop new revenue streams based on data. The author deftly unravels complex topics, provides hands-on SQL examples, and reveals how you can use the Snowflake Data Cloud to avoid replatforming or migrating data unnecessarily.
: Ingvar16 14-01-2022, 15:26 | : 0 |
What Is Causal Inference?: What Is Causal Inference? An Introduction for Data Scientists
: Hugo Bowne-Anderson, Mike Loukides
: OReilly Media, Inc.
: 2022-01-13
:
: pdf, epub
: 10.2 MB

Causal inference lies at the heart of our ability to understand why things happen by helping us predict the result of any action. This process is vital for businesses that aspire to turn data and information into valuable knowledge. With this report, data scientists and analysts will learn a principled way of thinking about causality using a suite of causal inference techniques now available. Authors Hugo Bowne-Anderson, a data science consultant, and Mike Loukides, vice president of content strategy at O'Reilly Media, introduce causality and discuss randomized control trials (RCTs), key aspects of causal graph theory, and well-needed techniques from econometrics.
: Ingvar16 14-01-2022, 03:30 | : 0 |
Data Quality Fundamentals: A Practitioners Guide to Building More Trustworthy Data Pipelines (Second Early Release): Data Quality Fundamentals: A Practitioners Guide to Building More Trustworthy Data Pipelines (Second Early Release)
: Barr Moses, Lior Gavish
: OReilly Media, Inc.
: 2022-01-13
: 97
:
: pdf, epub
: 10.17 MB

Do your product dashboards look funky? Are your quarterly reports stale? Is the dataset you're using broken or just plain wrong? These problems affect almost every team, yet they're usually addressed on an ad hoc basis and in a reactive manner. If you answered yes to any of the questions above, this book is for you. Many data engineering teams today face the "good pipelines, bad data" problem. It doesn't matter how advanced your data infrastructure is if the data you're piping is bad. In this book, Barr Moses, Lior Gavish, and Molly Vorwerck from the data reliability company Monte Carlo explain how to tackle data quality and trust at scale by leveraging best practices and technologies used by some of the world's most innovative companies.
: Ingvar16 14-01-2022, 03:00 | : 0 |
: Advances in Big Data Analytics: Theory, Algorithms and Practices
: Yong Shi
: Springer
: 2022
: PDF
: 723
: 11,6 Mb
: English

Today, big data affects countless aspects of our daily lives. This book provides a comprehensive and cutting-edge study on big data analytics, based on the research findings and applications developed by the author and his colleagues in related areas. It addresses the concepts of big data analytics and/or data science, multi-criteria optimization for learning, expert and rule-based data analysis, support vector machines for classification, feature selection, data stream analysis, learning analysis, sentiment analysis, link analysis, and evaluation analysis. The book also explores lessons learned in applying big data to business, engineering and healthcare. Lastly, it addresses the advanced topic of intelligence-quotient (IQ) tests for artificial intelligence.

Since each aspect mentioned above concerns a specific domain of application, taken together, the algorithms, procedures, analysis and empirical studies presented here offer a general picture of big data developments. Accordingly, the book can not only serve as a textbook for graduates with a fundamental grasp of training in big data analytics, but can also show practitioners how to use the proposed techniques to deal with real-world big data problems.
: vitvikvas 13-01-2022, 11:26 | : 0 |
Rhythmic Advantages in Big Data and Machine Learning: Rhythmic Advantages in Big Data and Machine Learning
: Anirban Bandyopadhyay, Kanad Ray
: Springer
: 2022
: 270
:
: pdf (true)
: 10.15 MB

The current book in the series of Systems in Rhythm Engineering, SRE, compiles rhythms from Big data in pure computation, astrophysics to basic biological structures. In todays world, anything and everything is data and we generate voluminous data almost every passing second which actually gave birth to Big Data. The phrase Big Data which buzzes around us everywhere, is applied to a specific type of data that has certain traits. However, this phrase has been over used and often incorrectly, which is why itis difficult to gauge its true meaning. For commoners, it is very difficult to understand if Big Data is a tool or a technology or just a buzzword used by data scientists to scare us. Another concern is if Big Data really has the potential to usher in dramatic changes or will the hype fade away with time. In any case, over the past few years, Big Data has become an integral part of several industries and in many cases has shown the potential to be a game-changer.
: Ingvar16 13-01-2022, 06:58 | : 0 |
Accelerating Enterprise Digital Transformation with a Next Generation Database: Accelerating Enterprise Digital Transformation with a Next Generation Database
: Steve Suehring
: OReilly Media, Inc.
: 2022-01-11
:
: pdf, epub
: 10.2 MB

Determining the best database infrastructure for digital transformation can be tricky. How your organization stores and provides access to data can determine the success or failure of the entire enterprise. Data silos can't properly serve all your organization's needs. Managing multiple databases requires more maintenance, costs, and complexity. How do you determine the right balance? In this report, author Steve Suehring examines the need for next-generation databases and then guides you through the various attributes you need to consider when choosing the right platform for your company. With the increasing abundance and depth of data lakes, the ability to capitalize on real-time analytics becomes more difficult unless the database platform can support and accelerate enterprise digital transformation.
: Ingvar16 13-01-2022, 06:29 | : 0 |
Geospatial Data Analytics and Urban Applications: Geospatial Data Analytics and Urban Applications
: Sandeep Narayan Kundu
: Springer
: 2022
: 197
:
: pdf (true)
: 10.0 MB

This book highlights advanced applications of geospatial data analytics to address real-world issues in urban society. With a connected world, we are generating spatial at unprecedented rates which can be harnessed for insightful analytics which define the way we analyze past events and define the future directions. This book is an anthology of applications of spatial data and analytics performed on them for gaining insights which can be used for problem solving in an urban setting. Each chapter is contributed by spatially aware data scientists in the making who present spatial perspectives drawn on spatial Big Data. The book shall benefit mature researchers and student alike to discourse a variety of urban applications which display the use of Machine Learning algorithms on spatial Big Data for real-world problem solving.
: Ingvar16 12-01-2022, 18:53 | : 0 |
Why External Data Needs to Be Part of Your Data and Analytics Strategy: Why External Data Needs to Be Part of Your Data and Analytics Strategy
: Joseph D. Stec
: OReilly Media, Inc.
: 2022-01-10
:
: pdf, epub
: 10.1 MB

Innovative organizations today are reaping the benefits of combining data from a variety of internal and external sources. By collecting, storing, analyzing, and leveraging external data, these companies are able to outperform competitors by unlocking improvements in growth, productivity, and risk management. This report explains how you can harness the power of external data to boost analytics, find competitive advantages, and drive value.
: Ingvar16 11-01-2022, 19:27 | : 0 |

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