IBM Db2 11.1 Certification Guide: Explore techniques to master database programming and administration tasks in IBM Db2

IBM Db2 11.1 Certification Guide: Explore techniques to master database programming and administration tasks in IBM Db2
Mastering material for dealing with DBA certification exams Key Features Prepare yourself for the IBM C2090-600 certification exam Cover over 50 Db2 procedures including database design, performance, and security Work through over 150 Q&As to gain confidence on each topic Book DescriptionIBM Db2 is a relational database management system (RDBMS) that helps you store, analyze, and retrieve data efficiently. This comprehensive book is designed to help you master all aspects of IBM Db2 database administration and prepare you to take and pass IBM’s Certification Exams C2090-600. Building on years of extensive experience, the authors take you through all areas covered by the test. The book delves deep into each certification topic: Db2 server management, physical design, business rules implementation, activity monitoring, utilities, high availability, and security. IBM Db2 11.1 Certification Guide provides you with more than 150 practice questions and answers, simulating real certification examination questions. Each chapter includes an extensive set of practice questions along with carefully explained answers. This book will not just prepare you for the C2090-600 exam but also help you troubleshoot day-to-day database administration challenges. What you will learn Configure and manage Db2 servers, instances, and databases Implement Db2 BLU Acceleration and a DB2 pureScale environment Create, manage, and alter Db2 database objects Use the partitioning capabilities available within Db2 Enforce constraint checking with the SET INTEGRITY command Utilize the Db2 problem determination (db2pd) and dsmtop tools Configure and manage HADR Understand how to encrypt data in transit and at rest Who this book is forThe IBM Db2 11.1 Certification Guide is an excellent choice for database administrators, architects, and application developers who are keen to obtain certification in Db2. Basic understanding of Db2 is expected in order to get the most out of this guide.
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Mastering Numerical Computing with NumPy: Master scientific computing and perform complex operations with ease

Mastering Numerical Computing with NumPy: Master scientific computing and perform complex operations with ease
Enhance the power of NumPy and start boosting your scientific computing capabilities Key Features Grasp all aspects of numerical computing and understand NumPy Explore examples to learn exploratory data analysis (EDA), regression, and clustering Access NumPy libraries and use performance benchmarking to select the right tool Book DescriptionNumPy is one of the most important scientific computing libraries available for Python. Mastering Numerical Computing with NumPy teaches you how to achieve expert level competency to perform complex operations, with in-depth coverage of advanced concepts. Beginning with NumPy’s arrays and functions, you will familiarize yourself with linear algebra concepts to perform vector and matrix math operations. You will thoroughly understand and practice data processing, exploratory data analysis (EDA), and predictive modeling. You will then move on to working on practical examples which will teach you how to use NumPy statistics in order to explore US housing data and develop a predictive model using simple and multiple linear regression techniques. Once you have got to grips with the basics, you will explore unsupervised learning and clustering algorithms, followed by understanding how to write better NumPy code while keeping advanced considerations in mind. The book also demonstrates the use of different high-performance numerical computing libraries and their relationship with NumPy. You will study how to benchmark the performance of different configurations and choose the best for your system. By the end of this book, you will have become an expert in handling and performing complex data manipulations. What you will learn Perform vector and matrix operations using NumPy Perform exploratory data analysis (EDA) on US housing data Develop a predictive model using simple and multiple linear regression Understand unsupervised learning and clustering algorithms with practical use cases Write better NumPy code and implement the algorithms from scratch Perform benchmark tests to choose the best configuration for your system Who this book is forMastering Numerical Computing with NumPy is for you if you are a Python programmer, data analyst, data engineer, or a data science enthusiast, who wants to master the intricacies of NumPy and build solutions for your numeric and scientific computational problems. You are expected to have familiarity with mathematics to get the most out of this book.
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PySpark Cookbook: Over 60 recipes for implementing big data processing and analytics using Apache Spark and Python

PySpark Cookbook: Over 60 recipes for implementing big data processing and analytics using Apache Spark and Python
Combine the power of Apache Spark and Python to build effective big data applications Key Features Perform effective data processing, machine learning, and analytics using PySpark Overcome challenges in developing and deploying Spark solutions using Python Explore recipes for efficiently combining Python and Apache Spark to process data Book DescriptionApache Spark is an open source framework for efficient cluster computing with a strong interface for data parallelism and fault tolerance. The PySpark Cookbook presents effective and time-saving recipes for leveraging the power of Python and putting it to use in the Spark ecosystem. You’ll start by learning the Apache Spark architecture and how to set up a Python environment for Spark. You’ll then get familiar with the modules available in PySpark and start using them effortlessly. In addition to this, you’ll discover how to abstract data with RDDs and DataFrames, and understand the streaming capabilities of PySpark. You’ll then move on to using ML and MLlib in order to solve any problems related to the machine learning capabilities of PySpark and use GraphFrames to solve graph-processing problems. Finally, you will explore how to deploy your applications to the cloud using the spark-submit command. By the end of this book, you will be able to use the Python API for Apache Spark to solve any problems associated with building data-intensive applications. What you will learn Configure a local instance of PySpark in a virtual environment Install and configure Jupyter in local and multi-node environments Create DataFrames from JSON and a dictionary using pyspark.sql Explore regression and clustering models available in the ML module Use DataFrames to transform data used for modeling Connect to PubNub and perform aggregations on streams Who this book is forThe PySpark Cookbook is for you if you are a Python developer looking for hands-on recipes for using the Apache Spark 2.x ecosystem in the best possible way. A thorough understanding of Python (and some familiarity with Spark) will help you get the best out of the book.
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Learning Azure Cosmos DB: A beginner’s guide to creating scalable, globally distributed, and highly responsive applications using Cosmos DB


Gain an in-depth understanding of Azure Cosmos DB – a multi-model database from Microsoft Key Features Develop your skills to build and scale applications using the power of Azure CosmosDB. Learn how to store and access data with a variety of APIs including MongoDB, Gremlin, SQL, Azure Tables and much more. Fast paced guide to have a better understanding of the features with the practical approach mentioned. Book DescriptionMicrosoft has introduced a new globally distributed database, called Azure Cosmos DB. It is a superset of Microsoft’s existing NoSQL Document DB service. Azure Cosmos DB enables you to scale throughput and storage elastically and independently across any number of Azure’s geographic regions. This book is a must-have for anyone who wants to get introduced to the world of Cosmos DB. This book will focus on building globally-distributed applications without the hassle of complex, multiple datacenter configurations. This book will shed light on how Cosmos DB offers multimodal NoSQL database capabilities in the cloud at a scale that is one product with different database engines, such as key-value, document, graph, and wide column store. We will cover detailed practical examples on how to create a CRUD application using Cosmos DB with a frontend framework of your choice. This book will empower developers to choose their favorite database engines to perform integration, along with other systems that utilize the most popular languages, such as Node.js. This book will take you through the tips and trick, of Cosmos DB deployment, management, and the security offered by Azure Cosmos DB in order to detect, prevent, and respond to database breaches. By the end of this book, you will not only be aware of the best capabilities of relational and non-relational databases, but you will also be able to build scalable, globally distributed, and highly responsive applications. What you will learn Build highly responsive and mission-critical applications Understand how distributed databases are important for global scale and low latency Understand how to write globally distributed applications the right way Implement comprehensive SLAs for throughput, latency, consistency, and availability Implement multiple data models and popular APIs for accessing and querying data Implement best practices covering data security in order to detect, prevent and respond to database breaches Who this book is forThis book is intended to anyone who wants to get well versed with Microsoft’s new NoSQL database called Azure Cosmos DB. Get the database into work with the practical examples mentioned.
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Hands-On Data Warehousing with Azure Data Factory: ETL techniques to load and transform data from various sources, both on-premises and on cloud

Hands-On Data Warehousing with Azure Data Factory: ETL techniques to load and transform data from various sources, both on-premises and on cloud

Leverage the power of Microsoft Azure Data Factory v2 to build hybrid data solutions

Key Features

  • Combine the power of Azure Data Factory v2 and SQL Server Integration Services
  • Design and enhance performance and scalability of a modern ETL hybrid solution
  • Interact with the loaded data in data warehouse and data lake using Power BI

Book Description

ETL is one of the essential techniques in data processing. Given data is everywhere, ETL will always be the vital process to handle data from different sources.

Hands-On Data Warehousing with Azure Data Factory starts with the basic concepts of data warehousing and ETL process. You will learn how Azure Data Factory and SSIS can be used to understand the key components of an ETL solution. You will go through different services offered by Azure that can be used by ADF and SSIS, such as Azure Data Lake Analytics, Machine Learning and Databrick’s Spark with the help of practical examples. You will explore how to design and implement ETL hybrid solutions using different integration services with a step-by-step approach. Once you get to grips with all this, you will use Power BI to interact with data coming from different sources in order to reveal valuable insights.

By the end of this book, you will not only learn how to build your own ETL solutions but also address the key challenges that are faced while building them.

What you will learn

  • Understand the key components of an ETL solution using Azure Data Factory and Integration Services
  • Design the architecture of a modern ETL hybrid solution
  • Implement ETL solutions for both on-premises and Azure data
  • Improve the performance and scalability of your ETL solution
  • Gain thorough knowledge of new capabilities and features added to Azure Data Factory and Integration Services

Who This Book Is For

This book is for you if you are a software professional who develops and implements ETL solutions using Microsoft SQL Server or Azure cloud. It will be an added advantage if you are a software engineer, DW/ETL architect, or ETL developer, and know how to create a new ETL implementation or enhance an existing one with ADF or SSIS.

Table of Contents

  1. Azure Data Factory
  2. Getting Started with Our First Data Factory
  3. ADF and SSIS in PaaS
  4. Azure Data Lake
  5. Machine Learning on the Cloud
  6. Sparks with Databrick
  7. Power BI reports

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Practical SQL: A Beginner’s Guide to Storytelling with Data


Practical SQL is an approachable and fast-paced guide to SQL (Structured Query Language), the standard programming language for defining, organizing, and exploring data in relational databases. The book focuses on using SQL to find the story your data tells, with the popular open-source database PostgreSQL and the pgAdmin interface as its primary tools.

You’ll first cover the fundamentals of databases and the SQL language, then build skills by analyzing data from the U.S. Census and other federal and state government agencies. With exercises and real-world examples in each chapter, this book will teach even those who have never programmed before all the tools necessary to build powerful databases and access information quickly and efficiently.

You’ll learn how to:
-Create databases and related tables using your own data
-Define the right data types for your information
-Aggregate, sort, and filter data to find patterns
-Use basic math and advanced statistical functions
-Identify errors in data and clean them up
-Import and export data using delimited text files
-Write queries for geographic information systems (GIS)
-Create advanced queries and automate tasks

Learning SQL doesn’t have to be dry and complicated. Practical SQL delivers clear examples with an easy-to-follow approach to teach you the tools you need to build and manage your own databases.

This book uses PostgreSQL, but the SQL syntax is applicable to many database applications, including Microsoft SQL Server and MySQL.
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Learning Azure Cosmos DB: A beginner’s guide to creating scalable, globally distributed, and highly responsive applications using Cosmos DB


Gain an in-depth understanding of Azure Cosmos DB – a multi-model database from Microsoft Key Features Develop your skills to build and scale applications using the power of Azure CosmosDB. Learn how to store and access data with a variety of APIs including MongoDB, Gremlin, SQL, Azure Tables and much more. Fast paced guide to have a better understanding of the features with the practical approach mentioned. Book DescriptionMicrosoft has introduced a new globally distributed database, called Azure Cosmos DB. It is a superset of Microsoft’s existing NoSQL Document DB service. Azure Cosmos DB enables you to scale throughput and storage elastically and independently across any number of Azure’s geographic regions. This book is a must-have for anyone who wants to get introduced to the world of Cosmos DB. This book will focus on building globally-distributed applications without the hassle of complex, multiple datacenter configurations. This book will shed light on how Cosmos DB offers multimodal NoSQL database capabilities in the cloud at a scale that is one product with different database engines, such as key-value, document, graph, and wide column store. We will cover detailed practical examples on how to create a CRUD application using Cosmos DB with a frontend framework of your choice. This book will empower developers to choose their favorite database engines to perform integration, along with other systems that utilize the most popular languages, such as Node.js. This book will take you through the tips and trick, of Cosmos DB deployment, management, and the security offered by Azure Cosmos DB in order to detect, prevent, and respond to database breaches. By the end of this book, you will not only be aware of the best capabilities of relational and non-relational databases, but you will also be able to build scalable, globally distributed, and highly responsive applications. What you will learn Build highly responsive and mission-critical applications Understand how distributed databases are important for global scale and low latency Understand how to write globally distributed applications the right way Implement comprehensive SLAs for throughput, latency, consistency, and availability Implement multiple data models and popular APIs for accessing and querying data Implement best practices covering data security in order to detect, prevent and respond to database breaches Who this book is forThis book is intended to anyone who wants to get well versed with Microsoft’s new NoSQL database called Azure Cosmos DB. Get the database into work with the practical examples mentioned.
Buy the book Learning Azure Cosmos DB: A beginner’s guide to creating scalable, globally distributed, and highly responsive applications using Cosmos DB from Ideakart.com.