Big data
Davide Moraschi
Business intelligence is becoming more important by the day, with cloud offerings and mobile devices gaining wider acceptance and achieving better market penetration. MicroStrategy Reporting Suite is a complete business intelligence platform that covers all the data analysis needs of an enterprise. Scorecards, dashboards, and reports can be explored and delivered on desktop, the Web, mobile devices, and the Cloud. With the latest Visual Insight tool, MicroStrategy brings the power of BI to the business users, allowing them to discover information without the help of IT personnel.Business Intelligence with MicroStrategy Cookbook covers the full cycle of a BI project with the MicroStrategy platform, from setting up the software to using dashboards in the cloud and on mobile devices. This book uses step-by-step instructions to teach you everything from the very basics to the more advanced topics. We will start by downloading and installing the software and a well-known sample SQL Server database. Then, one brick at a time, we will construct a fully-featured BI solution with a web interface, mobile reporting, and agile analytics.The chapters are ordered by increasing difficulty, and each one builds on top of the preceding chapter so that the learning process is progressive. The examples given in this book are practical, and you will be able to see the immediate result of your efforts. We will first cover setting up the platform, including the creation of the metadata and the different objects that are part of a BI project: tables, attributes, and metrics. Then, we take a look at how to create and analyze reports, charts, documents, and dashboards, as well as how to manipulate data with the desktop application, the web Interface, and an iPad device.The last part of the book is dedicated to advanced topics like the new agile analytics technology from MicroStrategy, where we cover both Visual Insight and MicroStrategy Cloud Express. Whether you are a database developer, data analyst, or a business user, Business Intelligence with MicroStrategy Cookbook will get you up to speed with one of the most powerful BI platforms on the market with the smallest possible investment of time and money.
Cacti Beginner's Guide. Leverage Cacti to design a robust network operations center - Second Edition
Thomas Urban
Cacti is a performance measurement tool that provides easy methods and functions for gathering and graphing system data. You can use Cacti to develop a robust event management system that can alert on just about anything you would like it to. But to do that, you need to gain a solid understanding of the basics of Cacti, its plugin architecture, and automation concepts.Cacti Beginner's Guide will introduce you to the wide variety of features of Cacti and will guide you on how to use them for maximum effectiveness. Advanced topics such as the plugin architecture and Cacti automation using the command-line interface will help you build a professional performance measurement system. Designed as a beginner's guide, the book starts off with the basics of installing and using Cacti, and also covers the advanced topics that will show you how to customize and extend the core Cacti functionalities. The book offers essential tutorials for creating advanced graphs and using plugins to create enterprise-class reports to show your customers and colleagues. From data templates to input methods and plugin installation to creating your own customized plugins, this book provides you with a rich selection of step-by-step instructions to reach your goals. It covers all you need to know to implement professional performance measurement techniques with Cacti and ways to fully customize Cacti to fit your needs. You will also learn how to migrate Cacti to new servers. Lastly you will also be introduced to the latest feature of building a scalable remote poller environment. By the end of the book, you will be able to implement and extend Cacti to monitor, display, and report the performance of your network exactly the way you want.
David Mertz
Data cleaning is the all-important first step to successful data science, data analysis, and machine learning. If you work with any kind of data, this book is your go-to resource, arming you with the insights and heuristics experienced data scientists had to learn the hard way.In a light-hearted and engaging exploration of different tools, techniques, and datasets real and fictitious, Python veteran David Mertz teaches you the ins and outs of data preparation and the essential questions you should be asking of every piece of data you work with.Using a mixture of Python, R, and common command-line tools, Cleaning Data for Effective Data Science follows the data cleaning pipeline from start to end, focusing on helping you understand the principles underlying each step of the process. You'll look at data ingestion of a vast range of tabular, hierarchical, and other data formats, impute missing values, detect unreliable data and statistical anomalies, and generate synthetic features. The long-form exercises at the end of each chapter let you get hands-on with the skills you've acquired along the way, also providing a valuable resource for academic courses.
MrExcel's Holy Macro! Books, Oz du Soleil
This book provides a step-by-step guide to using Power Query in Excel for efficient data cleaning and transformation. Starting with an introduction to its capabilities, it explains how to import data, handle missing values, and parse text fields with ease.Advanced techniques such as merging datasets, appending data, and performing joins are explored in detail. The book also covers grouping data, creating conditional and custom columns, and reshaping data through unpivoting for analysis. Each concept is illustrated with practical examples for clarity.By the end of the book, readers will be equipped with the skills to automate repetitive tasks and streamline workflows. Whether dealing with messy data or preparing datasets for analysis, this guide ensures you can confidently tackle any Excel data transformation challenge.
Clojure for Data Science. Statistics, big data, and machine learning for Clojure programmers
Henry Garner
The term “data science” has been widely used to define this new profession that is expected to interpret vast datasets and translate them to improved decision-making and performance. Clojure is a powerful language that combines the interactivity of a scripting language with the speed of a compiled language. Together with its rich ecosystem of native libraries and an extremely simple and consistent functional approach to data manipulation, which maps closely to mathematical formula, it is an ideal, practical, and flexible language to meet a data scientist’s diverse needs.Taking you on a journey from simple summary statistics to sophisticated machine learning algorithms, this book shows how the Clojure programming language can be used to derive insights from data. Data scientists often forge a novel path, and you’ll see how to make use of Clojure’s Java interoperability capabilities to access libraries such as Mahout and Mllib for which Clojure wrappers don’t yet exist. Even seasoned Clojure developers will develop a deeper appreciation for their language’s flexibility!You’ll learn how to apply statistical thinking to your own data and use Clojure to explore, analyze, and visualize it in a technically and statistically robust way. You can also use Incanter for local data processing and ClojureScript to present interactive visualisations and understand how distributed platforms such as Hadoop sand Spark’s MapReduce and GraphX’s BSP solve the challenges of data analysis at scale, and how to explain algorithms using those programming models.Above all, by following the explanations in this book, you’ll learn not just how to be effective using the current state-of-the-art methods in data science, but why such methods work so that you can continue to be productive as the field evolves into the future.
Sanket Thodge
With the ongoing data explosion, more and more organizations all over the world are slowly migrating their infrastructure to the cloud. These cloud platforms also provide their distinct analytics services to help you get faster insights from your data. This book will give you an introduction to the concept of analytics on the cloud, and the different cloud services popularly used for processing and analyzing data. If you’re planning to adopt the cloud analytics model for your business, this book will help you understand the design and business considerations to be kept in mind, and choose the best tools and alternatives for analytics, based on your requirements. The chapters in this book will take you through the 70+ services available in Google Cloud Platform and their implementation for practical purposes. From ingestion to processing your data, this book contains best practices on building an end-to-end analytics pipeline on the cloud by leveraging popular concepts such as machine learning and deep learning.By the end of this book, you will have a better understanding of cloud analytics as a concept as well as a practical know-how of its implementation
Kathrin Melcher, Rosaria Silipo
KNIME Analytics Platform is an open source software used to create and design data science workflows. This book is a comprehensive guide to the KNIME GUI and KNIME deep learning integration, helping you build neural network models without writing any code. It’ll guide you in building simple and complex neural networks through practical and creative solutions for solving real-world data problems.Starting with an introduction to KNIME Analytics Platform, you’ll get an overview of simple feed-forward networks for solving simple classification problems on relatively small datasets. You’ll then move on to build, train, test, and deploy more complex networks, such as autoencoders, recurrent neural networks (RNNs), long short-term memory (LSTM), and convolutional neural networks (CNNs). In each chapter, depending on the network and use case, you’ll learn how to prepare data, encode incoming data, and apply best practices.By the end of this book, you’ll have learned how to design a variety of different neural architectures and will be able to train, test, and deploy the final network.