Follow along by implementing these statistical and machine learning solutions in your own project on GCP, and discover how this platform provides a transformative and more collaborative way of doing data science.
You’ll learn how to:
Valliappa (Lak) Lakshmanan is currently a Tech Lead for Data and Machine Learning Professional Services for Google Cloud. His mission is to democratize machine learning so that it can be done by anyone anywhere using Google's amazing infrastructure, without deep knowledge of statistics or programming or ownership of a lot of hardware. Before Google, he led a team of data scientists at the Climate Corporation and was a Research Scientist at NOAA National Severe Storms Laboratory, working on machine learning applications for severe weather diagnosis and prediction.
This book targets IT professionals, business analysts, BI developers, managers, newcomers to SAP Analytics Cloud, and ultimately anyone who wants to learn from self-paced, professional guidance and needs a solid foundation in SAP Analytics Cloud.What You Will LearnA clear understanding of SAP Analytics Cloud platformCreate data models using different data sources, including Excel and text files .Present professional analyses using different types of charts, tables, geo maps, and moreUsing stories, drill up and down instantly to analyze data from various anglesShare completed stories with other team members or compile them in SAP Digital Boardroom agendas for presentation to major stakeholdersExport the results of a story to a PDF fileSave time by planning, analyzing, predicting, and collaborating in contextDiscover, visualize, plan, and predict in one product as opposed to separate solutionsIn Detail
The book starts with the basics of SAP Analytics Cloud (formerly known as SAP BusinessObjects Cloud) and exposes almost every significant feature a beginner needs to master. Packed with illustrations and short, essential, to-the-point descriptions, the book provides a unique learning experience. Your journey of exploration starts with a basic introduction to the SAP Analytics Cloud platform. You will then learn about different segments of the product, such as Models, Stories, Digital Boardroom, and so on. Then, you are introduced to the product's interface: the Home screen, the main menu, and more. Then comes the hands-on aspect of the book, which starts with model creation. Next, you learn how to utilize a model to prepare different types of stories(reports) with the help of charts, tables, Geo Maps, and more. In the final chapters of this book, you will learn about Digital Boardroom, Collaboration, and Administration.Style and approach
The easy-to-follow visual instructions provided in this book help business users and report developers create simple and complex stories (reports) quickly
The complex structure of data these days requires sophisticated solutions for data transformation, to make the information more accessible to the users.This book empowers you to build such solutions with relative ease with the help of Apache Hadoop, along with a host of other Big Data tools.
This book will give you a complete understanding of the data lifecycle management with Hadoop, followed by modeling of structured and unstructured data in Hadoop. It will also show you how to design real-time streaming pipelines by leveraging tools such as Apache Spark, and build efficient enterprise search solutions using Elasticsearch. You will learn to build enterprise-grade analytics solutions on Hadoop, and how to visualize your data using tools such as Apache Superset. This book also covers techniques for deploying your Big Data solutions on the cloud Apache Ambari, as well as expert techniques for managing and administering your Hadoop cluster.
By the end of this book, you will have all the knowledge you need to build expert Big Data systems.What you will learn Build an efficient enterprise Big Data strategy centered around Apache Hadoop Gain a thorough understanding of using Hadoop with various Big Data frameworks such as Apache Spark, Elasticsearch and more Set up and deploy your Big Data environment on premises or on the cloud with Apache AmbariDesign effective streaming data pipelines and build your own enterprise search solutions Utilize the historical data to build your analytics solutions and visualize them using popular tools such as Apache Superset Plan, set up and administer your Hadoop cluster efficientlyWho this book is for
This book is for Big Data professionals who want to fast-track their career in the Hadoop industry and become an expert Big Data architect. Project managers and mainframe professionals looking forward to build a career in Big Data Hadoop will also find this book to be useful. Some understanding of Hadoop is required to get the best out of this book.
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 implementationWhat you will learn Explore the basics of cloud analytics and the major cloud solutions Learn how organizations are using cloud analytics to improve the ROI Explore the design considerations while adopting cloud services Work with the ingestion and storage tools of GCP such as Cloud Pub/Sub Process your data with tools such as Cloud Dataproc, BigQuery, etcOver 70 GCP tools to build an analytics engine for cloud analytics Implement machine learning and other AI techniques on GCP Who this book is for
This book is targeted at CIOs, CTOs, and even analytics professionals looking for various alternatives to implement their analytics pipeline on the cloud. Data professionals looking to get started with cloud-based analytics will also find this book useful. Some basic exposure to cloud platforms such as GCP will be helpful, but not mandatory.
If you are looking for a resource that teaches you how to process continuous streams of data in real-time, this book is what you need. A basic understanding of the concepts in analytics is all you need to get started with this bookWhat You Will LearnPerform real-time event processing with Azure Stream AnalysisIncorporate the features of Big Data Lambda architecture pattern in real-time data processingDesign a streaming pipeline for storage and batch analysisImplement data transformation and computation activities over stream of eventsAutomate your streaming pipeline using Powershell and the .NET SDKIntegrate your streaming pipeline with popular Machine Learning and Predictive Analytics modelling algorithmsMonitor and troubleshoot your Azure Streaming jobs effectivelyIn Detail
Microsoft Azure is a very popular cloud computing service used by many organizations around the world. Its latest analytics offering, Stream Analytics, allows you to process and get actionable insights from different kinds of data in real-time.
This book is your guide to understanding the basics of how Azure Stream Analytics works, and building your own analytics solution using its capabilities. You will start with understanding what Stream Analytics is, and why it is a popular choice for getting real-time insights from data. Then, you will be introduced to Azure Stream Analytics, and see how you can use the tools and functions in Azure to develop your own Streaming Analytics. Over the course of the book, you will be given comparative analytic guidance on using Azure Streaming with other Microsoft Data Platform resources such as Big Data Lambda Architecture integration for real time data analysis and differences of scenarios for architecture designing with Azure HDInsight Hadoop clusters with Storm or Stream Analytics. The book also shows you how you can manage, monitor, and scale your solution for optimal performance.
By the end of this book, you will be well-versed in using Azure Stream Analytics to develop an efficient analytics solution that can work with any type of data.Style and approach
A comprehensive guidance on developing real-time event processing with Azure Stream Analysis
This book answers the following questions:What forces created the need for Enterprise Services Architecture?How does ESA enable business process innovation?How is model-driven development used at all levels of design, configuration, and deployment?How do all the layers of technology that support ESA work together?How will composite applications extend business process automation?How does ESA create new models for IT governance?How can companies manage disruptive change?How can enterprise services be discovered and designed?How will the process of adapting applications be simplified?
Based on extensive research with experts from the German software company SAP, this definitive book is ideal for architects, developers, and other IT professionals who want to understand the technology and business relevance of ESA in a detailed way--especially those who want to move on the technology now, rather than in the next year or two.
In this practical and comprehensive guide, author Martin Kleppmann helps you navigate this diverse landscape by examining the pros and cons of various technologies for processing and storing data. Software keeps changing, but the fundamental principles remain the same. With this book, software engineers and architects will learn how to apply those ideas in practice, and how to make full use of data in modern applications.Peer under the hood of the systems you already use, and learn how to use and operate them more effectivelyMake informed decisions by identifying the strengths and weaknesses of different toolsNavigate the trade-offs around consistency, scalability, fault tolerance, and complexityUnderstand the distributed systems research upon which modern databases are builtPeek behind the scenes of major online services, and learn from their architectures