Database Management 7

Journey into the world of Web3-based application development, its related protocols, and its usage in developing decentralized applications. This book will explain how programmable blockchains are r……続きを見る

Solve common and not-so-common financial problems using Python libraries such as NumPy, SciPy, and pandas Key Features Use powerful Python libraries such as pandas, NumPy, and SciPy to analyze your……続きを見る

Data is getting bigger and more complex by the day, and so are your choices in handling it. Explore some of the most cutting-edge databases available - from a traditional relational database to newe……続きを見る

Take a journey toward discovering, learning, and using Apache Spark 3.0. In this book, you will gain expertise on the powerful and efficient distributed data processing engine inside of Apache Spark……続きを見る

Data pipelines are the foundation for success in data analytics. Moving data from numerous diverse sources and transforming it to provide context is the difference between having data and actually g……続きを見る

Protect your cloud, virtual, and on-premises environments by implementing Veeam's powerful backup and replication technology Key Features Gain in-depth knowledge of CDP and hardened repositories th……続きを見る

Cowritten by Ralph Kimball, the world's leading data warehousing authority, whose previous books have sold more than 150,000 copies Delivers real-world solutions for the most time- and labor-intens……続きを見る

Harness the power of Docker by containerizing your code with all its libraries and file systems to consistently run anywhere. This book is your source for learning all about Docker operations and de……続きを見る

RMAN Recipes for Oracle Database 12c is an example-driven approach to the Oracle database administrator's #1 job responsibility: Be able to recover the database. Of all the things you are responsi……続きを見る

Now in its fourth edition and covering Oracle Database 21c, this best-selling book continues to bring you some of the best thinking on how to apply Oracle Database to produce scalable applications t……続きを見る

Learn how to apply the principles of machine learning to time series modeling with this indispensable resource Machine Learning for Time Series Forecasting with Python is an incisive and straightfor……続きを見る

As you move data to the cloud, you need to consider a comprehensive approach to data governance, along with well-defined and agreed-upon policies to ensure your organization meets compliance require……続きを見る

Step-by-step guide to different data movement and processing techniques, using Google Cloud Platform Services Key Featuresa- Learn the basic concept of Cloud Computing along with different Cloud ser……続きを見る

Speed up the execution of important database queries by making good choices about which indexes to create. Choose correct index types for different scenarios. Avoid indexing pitfalls that can actual……続きを見る

TheData Vault was invented by Dan Linstedt at the U.S. Department of Defense, and the standard has been successfully applied to data warehousing projects at organizations of different sizes, from sm……続きを見る

Access much-needed information for building scalable, high-concurrency applications and deploying them against the Oracle Database. This new edition is updated to be current with Oracle Database 19.……続きを見る

Performance problems are rarely "problems" per se. They are more often "crises" during which you’re pressured for results by a manager standing outside your cubicle while your phone rings with queri……続きを見る

There are many excellent R resources for visualization, data science, and package development. Hundreds of scattered vignettes, web pages, and forums explain how to use R in particular domains. But ……続きを見る

This book provides a critical comprehensive summary of the coevolution of telecom markets, rules and public institutions over the last 25 years, focusing on the challenges that regulators and policy……続きを見る

With this practical book, AI and machine learning practitioners will learn how to successfully build and deploy data science projects on Amazon Web Services. The Amazon AI and machine learning stack……続きを見る

The definitive guide to dimensional design for your data warehouse Learn the best practices of dimensional design. Star Schema: The Complete Reference offers in-depth coverage of design principles a……続きを見る

This book comprehensively covers the topic of recommender systems, which provide personalized recommendations of products or services to users based on their previous searches or purchases. Recommen……続きを見る

Get the definitive handbook for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.10 and pandas 1.4, the third edition of this hands-on guide is packed with ……続きを見る

Learn how easy it is to apply sophisticated statistical and machine learning methods to real-world problems when you build using Google Cloud Platform (GCP). This hands-on guide shows data engineers……続きを見る

The missing expert-led manual for the AWS ecosystem ー go from foundations to building data engineering pipelines effortlessly Purchase of the print or Kindle book includes a free eBook in the PDF f……続きを見る

Implement real-world decentralized applications using Python, Vyper, Populus, and Ethereum Key Features Stay up-to-date with everything you need to know about the blockchain ecosystem Implement sma……続きを見る

While Excel remains ubiquitous in the business world, recent Microsoft feedback forums are full of requests to include Python as an Excel scripting language. In fact, it's the top feature requested.……続きを見る

Every enterprise application creates data, whether it consists of log messages, metrics, user activity, or outgoing messages. Moving all this data is just as important as the data itself. With this ……続きを見る

Discover how to use Neo4j to identify relationships within complex and large graph datasets using graph modeling, graph algorithms, and machine learning Key Features Get up and running with graph a……続きを見る

Data-driven insights are a key competitive advantage for any industry today, but deriving insights from raw data can still take days or weeks. Most organizations can’t scale data science teams fast ……続きを見る