Business Intelligence Cookbook

Leverage the computational power of Python with more than 60 recipes that arm you with the required skills to make informed business decisions About This Book Want to minimize risk and optimize profits of your business? Learn to create efficient analytical reports with ease using this highly practical, easy-to-follow guide Learn to apply Python for business intelligence tasks—preparing, exploring, analyzing, visualizing and reporting—in order to make more informed business decisions using data at hand Learn to explore and analyze business data, and build business intelligence dashboards with the help of various insightful recipes Who This Book Is For This book is intended for data analysts, managers, and executives with a basic knowledge of Python, who now want to use Python for their BI tasks. If you have a good knowledge and understanding of BI applications and have a “working” system in place, this book will enhance your toolbox. What You Will Learn Install Anaconda, MongoDB, and everything you need to get started with your data analysis Prepare data for analysis by querying cleaning and standardizing data Explore your data by creating a Pandas data frame from MongoDB Gain powerful insights, both statistical and predictive, to make informed business decisions Visualize your data by building dashboards and generating reports Create a complete data processing and business intelligence system In Detail The amount of data produced by businesses and devices is going nowhere but up. In this scenario, the major advantage of Python is that it's a general-purpose language and gives you a lot of flexibility in data structures. Python is an excellent tool for more specialized analysis tasks, and is powered with related libraries to process data streams, to visualize datasets, and to carry out scientific calculations. Using Python for business intelligence (BI) can help you solve tricky problems in one go. Rather than spending day after day scouring Internet forums for “how-to” information, here you'll find more than 60 recipes that take you through the entire process of creating actionable intelligence from your raw data, no matter what shape or form it's in. Within the first 30 minutes of opening this book, you'll learn how to use the latest in Python and NoSQL databases to glean insights from data just waiting to be exploited. We'll begin with a quick-fire introduction to Python for BI and show you what problems Python solves. From there, we move on to working with a predefined data set to extract data as per business requirements, using the Pandas library and MongoDB as our storage engine. Next, we will analyze data and perform transformations for BI with Python. Through this, you will gather insightful data that will help you make informed decisions for your business. The final part of the book will show you the most important task of BI—visualizing data by building stunning dashboards using Matplotlib, PyTables, and iPython Notebook. Style and approach This is a step-by-step guide to help you prepare, explore, analyze and report data, written in a conversational tone to make it easy to grasp. Whether you're new to BI or are looking for a better way to work, you'll find the knowledge and skills here to get your job done efficiently.

Create powerful, effective visualizations to help analyze your data with Tableau 10 by your side About This Book Cook your favorite Tableau 10 business intelligence recipe with the help of this easy-to-follow book Build beautiful, interactive dashboards and visualizations in Tableau 10 that help you make informed decisions This rich collection of independent recipes cover everything needed to become an advanced Tableau user and get an edge over other Tableau users Who This Book Is For This book is targeted to business, data, and analytics professionals who want to build rich interactive visualizations using Tableau. Familiarity with previous versions of Tableau would be helpful, but is not necessary. What You Will Learn Become familiar with the Tableau interface Build basic to more advanced charts with step-by-step recipes Use filters, calculated fields, parameters, and actions to add interactivity to charts and dashboards Prepare and transform data for analysis using Tableau's built-in tools and functions Create effective and compelling dashboards and story points Leverage Tableau's mapping capabilities to visualize location and shape data Integrate analytics and forecasting to enhance data analysis Get to know tips and tricks to work more quickly and effectively in Tableau Increase your confidence and competence in creating rich, interactive visualizations in Tableau In Detail Tableau is a software tool that can speed up data analysis through its rich visualization capabilities, and help uncover insights for better and smarter decision making. This book is for the business, technology, data and analytics professionals who use and analyze data and data-driven approaches to support business operations and strategic initiatives in their organizations. This book provides easy-to-follow recipes to get the reader up and running with Tableau 10, and covers basic to advanced use cases and scenarios. The book starts with building basic charts in Tableau and moves on to building more complex charts by incorporating different Tableau features and interactivity components. There is an entire chapter dedicated to dashboard techniques and best practices. A number of recipes specifically for geospatial visualization, analytics, and data preparation are also covered. By the end of this book, you'll have gained confidence and competence to analyze and communicate data and insights more efficiently and effectively by creating compelling interactive charts, dashboards, and stories in Tableau. Style and approach This book is a collection of independent recipes that cover a wide range of options for data visualization on offer with Tableau. With the help of the recipes in this book, you can explore Tableau and pick the business intelligence solution that's best suited for your needs.

Written in a cookbook style, this book will teach you through the use of recipes with examples and illustrations. Each recipe contains step-by-step instructions about everything necessary to execute a particular task.This book is intended for both BI and database developers who want to expand their knowledge of MicroStrategy. It is also useful for advanced data analysts who are evaluating different technologies. You do not need to be an SQL master to read this book, yet knowledge of some concepts like foreign keys and many-to-many relationships is assumed. Some knowledge of basic concepts such as dimensional modeling (fact tables, dimensions) will also help your comprehension of this book. No previous MicroStrategy knowledge is needed.

This book is written in a simple, easy to understand format with lots of screenshots and step-by-step explanations. If you are Project Managers or IT professionals looking to design and develop a data warehouse and business intelligence solution, then this is the best guide for you. This book assumes that you have a fundamental knowledge of data warehouse and business intelligence projects.

Use Looker for visualizing data, data analysis, and reporting, and learn how to connect to your data, build dashboards and reports, and share insights with your team Key Features Explore data visualization, analysis, and reporting with Looker to gain insights from your data Connect to data sources, build dashboards, and create reports to track and share key metrics Share insights with your team to make better business decisions Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionLooker is a data analytics and business intelligence platform that allows organizations to explore, analyze, and visualize their data. It provides tools for data modeling, exploration, and visualization, enabling you to gain insights from your data to make informed business decisions. You’ll start with the basics, from setting up your Looker environments to configuring views and models using LookML. As you progress, you’ll delve into more advanced topics, such as navigating data in Explore, tailoring dashboards to your needs, and adding dynamic elements for interactivity. Along the way, you'll gain invaluable troubleshooting skills to tackle common issues and optimize your Looker usage, ensuring a smooth and seamless experience. Furthermore, the book extends your understanding beyond the basics, equipping you with the knowledge you need to develop Looker applications and seamlessly integrate them with other tools and applications. You'll also explore advanced techniques for harnessing Looker's full potential, empowering you to establish data-driven decision-making and innovation within your organization. By the end of this BI book, you'll have gained a solid understanding of how to use Looker to find important information, make tasks easier, and derive important insights.What you will learn Understand Looker's key components, including LookML, data models, and dashboards. Explore Looker's functionality, including custom fields, calculations, and visualizations. Work with Looker dashboards using dynamic elements like links and actions. Use different types of filters for dimensions to create dashboards Develop Looker applications using essential tools and frameworks Explore additional applications for the Looker organization Integrate Looker with other tools using APIs, connectors, and data pipelines Who this book is for If you’re a business analyst, data analyst, or BI developer who wants to get well-versed with the features of Looker, this book is for you. Basic knowledge of business intelligence is required to get started.

Over 80 quick and advanced recipes that focus on real world techniques and solutions to manage, design, and build data warehouse and business intelligence projects with this book and ebook.

This book presents a comprehensive and systematic introduction to transforming process-oriented data into information about the underlying business process, which is essential for all kinds of decision-making. To that end, the authors develop step-by-step models and analytical tools for obtaining high-quality data structured in such a way that complex analytical tools can be applied. The main emphasis is on process mining and data mining techniques and the combination of these methods for process-oriented data. After a general introduction to the business intelligence (BI) process and its constituent tasks in chapter 1, chapter 2 discusses different approaches to modeling in BI applications. Chapter 3 is an overview and provides details of data provisioning, including a section on big data. Chapter 4 tackles data description, visualization, and reporting. Chapter 5 introduces data mining techniques for cross-sectional data. Different techniques for the analysis of temporal data are then detailed in Chapter 6. Subsequently, chapter 7 explains techniques for the analysis of process data, followed by the introduction of analysis techniques for multiple BI perspectives in chapter 8. The book closes with a summary and discussion in chapter 9. Throughout the book, (mostly open source) tools are recommended, described and applied; a more detailed survey on tools can be found in the appendix, and a detailed code for the solutions together with instructions on how to install the software used can be found on the accompanying website. Also, all concepts presented are illustrated and selected examples and exercises are provided. The book is suitable for graduate students in computer science, and the dedicated website with examples and solutions makes the book ideal as a textbook for a first course in business intelligence in computer science or business information systems. Additionally, practitioners and industrial developers who are interested in the concepts behind business intelligence will benefit from the clear explanations and many examples.

This book examines the managerial dimensions of business intelligence (BI) systems. It develops a set of guidelines for value creation by implementing business intelligence systems and technologies. In particular the book looks at BI as a process – driven by a mix of human and technological capabilities – to serve complex information needs in building insights and providing aid in decision making. After an introduction to the key concepts of BI and neighboring areas of information processing, the book looks at the complexity and multidimensionality of BI. It tackles both data integration and information integration issues. Bodies of knowledge and other widely accepted collections of experience are presented and turned into lessons learned. Following a straightforward introduction to the processes and technologies of BI the book embarks on BI maturity and agility, the components, drivers and inhibitors of BI culture and soft BI factors like attention, sense and trust. Eventually the book attempts to provide a holistic view on business intelligence, possible structures and tradeoffs and embarks to provide an outlook on possible developments in BI and analytics.