Effective Business Intelligence With Quicksight
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Effective Business Intelligence with QuickSight
Author: Rajesh Nadipalli
language: en
Publisher: Packt Publishing Ltd
Release Date: 2017-03-10
From data to actionable business insights using Amazon QuickSight! About This Book A practical hands-on guide to improving your business with the power of BI and Quicksight Immerse yourself with an end-to-end journey for effective analytics using QuickSight and related services Packed with real-world examples with Solution Architectures needed for a cloud-powered Business Intelligence service Who This Book Is For This book is for Business Intelligence architects, BI developers, Big Data architects, and IT executives who are looking to modernize their business intelligence architecture and deliver a fast, easy-to-use, cloud powered business intelligence service. What You Will Learn Steps to test drive QuickSight and see how it fits in AWS big data eco system Load data from various sources such as S3, RDS, Redshift, Athena, and SalesForce and visualize using QuickSight Understand how to prepare data using QuickSight without the need of an IT developer Build interactive charts, reports, dashboards, and storyboards using QuickSight Access QuickSight using the mobile application Architect and design for AWS Data Lake Solution, leveraging AWS hosted services Build a big data project with step-by-step instructions for data collection, cataloguing, and analysis Secure your data used for QuickSight from S3, RedShift, and RDS instances Manage users, access controls, and SPICE capacity In Detail Amazon QuickSight is the next-generation Business Intelligence (BI) cloud service that can help you build interactive visualizations on top of various data sources hosted on Amazon Cloud Infrastructure. QuickSight delivers responsive insights into big data and enables organizations to quickly democratize data visualizations and scale to hundreds of users at a fraction of the cost when compared to traditional BI tools. This book begins with an introduction to Amazon QuickSight, feature differentiators from traditional BI tools, and how it fits in the overall AWS big data ecosystem. With practical examples, you will find tips and techniques to load your data to AWS, prepare it, and finally visualize it using QuickSight. You will learn how to build interactive charts, reports, dashboards, and stories using QuickSight and share with others using just your browser and mobile app. The book also provides a blueprint to build a real-life big data project on top of AWS Data Lake Solution and demonstrates how to build a modern data lake on the cloud with governance, data catalog, and analysis. It reviews the current product shortcomings, features in the roadmap, and how to provide feedback to AWS. Grow your profits, improve your products, and beat your competitors. Style and approach This book takes a fast-paced, example-driven approach to demonstrate the power of QuickSight to improve your business' efficiency. Every chapter is accompanied with a use case that shows the practical implementation of the step being explained.
Next-Generation Enterprise Security and Governance
The Internet is making our daily lives as digital as possible, and this new era is called the Internet of Everything (IoE). The key force behind the rapid growth of the Internet is the technological advancement of enterprises. The digital world we live in is facilitated by these enterprises’ advances and business intelligence. These enterprises need to deal with gazillions of bytes of data, and in today’s age of General Data Protection Regulation, enterprises are required to ensure privacy and security of large-scale data collections. However, the increased connectivity and devices used to facilitate IoE are continually creating more room for cybercriminals to find vulnerabilities in enterprise systems and flaws in their corporate governance. Ensuring cybersecurity and corporate governance for enterprises should not be an afterthought or present a huge challenge. In recent times, the complex diversity of cyber-attacks has been skyrocketing, and zero-day attacks, such as ransomware, botnet, and telecommunication attacks, are happening more frequently than before. New hacking strategies would easily bypass existing enterprise security and governance platforms using advanced, persistent threats. For example, in 2020, the Toll Group firm was exploited by a new crypto-attack family for violating its data privacy, where an advanced ransomware technique was launched to exploit the corporation and request a huge figure of monetary ransom. Even after applying rational governance hygiene, cybersecurity configuration and software updates are often overlooked when they are most needed to fight cyber-crime and ensure data privacy. Therefore, the threat landscape in the context of enterprises has become wider and far more challenging. There is a clear need for collaborative work throughout the entire value chain of this network. In this context, this book addresses the cybersecurity and cooperate governance challenges associated with enterprises, which will provide a bigger picture of the concepts, intelligent techniques, practices, and open research directions in this area. This book serves as a single source of reference for acquiring the knowledge on the technology, process, and people involved in next-generation privacy and security.
Data Lakes
The concept of a data lake is less than 10 years old, but they are already hugely implemented within large companies. Their goal is to efficiently deal with ever-growing volumes of heterogeneous data, while also facing various sophisticated user needs. However, defining and building a data lake is still a challenge, as no consensus has been reached so far. Data Lakes presents recent outcomes and trends in the field of data repositories. The main topics discussed are the data-driven architecture of a data lake; the management of metadata supplying key information about the stored data, master data and reference data; the roles of linked data and fog computing in a data lake ecosystem; and how gravity principles apply in the context of data lakes. A variety of case studies are also presented, thus providing the reader with practical examples of data lake management.