GET MORE WITH MANNING An eBook copy of the previous edition, MongoDB in Action (First Edition), is included at no additional cost. It will be automatically added to your Manning Bookshelf within 24 hours of purchase. MongoDB in Action, Second Edition is a completely revised and updated version. It introduces MongoDB 3.0 and the document-oriented database model. This perfectly paced book gives you both the big picture you'll need as a developer and enough low-level detail to satisfy system engineers. About the Technology This document-oriented database was built for high availability, supports rich, dynamic schemas, and lets you easily distribute data across multiple servers. MongoDB 3.0 is flexible, scalable, and very fast, even with big data loads. About the Book MongoDB in Action, Second Edition is a completely revised and updated version. It introduces MongoDB 3.0 and the document-oriented database model. This perfectly paced book gives you both the big picture you'll need as a developer and enough low-level detail to satisfy system engineers. Lots of examples will help you develop confidence in the crucial area of data modeling. You'll also love the deep explanations of each feature, including replication, auto-sharding, and deployment. What's Inside Indexes, queries, and standard DB operations Aggregation and text searching Map-reduce for custom aggregations and reporting Deploying for scale and high availability Updated for Mongo 3.0 About the Reader Written for developers. No previous MongoDB or NoSQL experience is assumed. About the Authors After working at MongoDB, Kyle Banker is now at a startup. Peter Bakkum is a developer with MongoDB expertise. Shaun Verch has worked on the core server team at MongoDB. A Genentech engineer, Doug Garrett is one of the winners of the MongoDB Innovation Award for Analytics. A software architect, Tim Hawkins has led search engineering at Yahoo Europe. Technical Contributor: Wouter Thielen Technical Editor: Mihalis Tsoukalos Quotes A thorough manual for learning, practicing, and implementing MongoDB - Jeet Marwah, Acer Inc. A must-read to properly use MongoDB and model your data in the best possible way. - Hernan Garcia, Betterez Inc. Provides all the necessary details to get you jump-started with MongoDB. - Gregor Zurowski, Independent Software Development Consultant Awesome! MongoDB in a nutshell. - Hardy Ferentschik, Red Hat

What is life but a series of questions? Does that question even make any sense? We'll never know, as this wasn't a question that got asked on this episode. Instead, Tom Miller, co-host of the Measured Direction podcast, joined us to give us a taste of the format of his show: user-submitted analytics questions asked and answered on the fly. What do you do when you lose a room of executives 15 minutes into your presentation? What does the future hold for digital analytics? Will we ever be able to measure the impact of TV? Who would win in a bar fight between Robocop and the podcast hosts? Find out the answers in a mere 45 minutes of audio (30 minutes if, like our guest, you listen at 1.5X speed).

People, places, and things mentioned in this episode include:

Measured Direction podcast Kevin Hillstrom Mine That Data Radio podcast Hadley Wickham Hadley Wickham on the Data Stories podcast R Adobe's Analysis Workspace Domo Jim Sterne Moe Kiss Clarivoy Comscore acquisition of Rentrak Google Adometry The Gary Angel episode of The Digital Analytics Power Hour

Hadoop has revolutionized data processing and enterprise data warehousing, but its explosive growth has come with a large amount of uncertainty, hype, and confusion. With this report, enterprise decision makers will receive a concise crash course on what Hadoop is and why it’s important. Hadoop represents a major shift from traditional enterprise data warehousing and data analytics, and its technology can be daunting at first. Donald Miner, founder of the data science firm Miner & Kasch, covers just enough ground so you can make intelligent decisions about Hadoop in your enterprise. By the end of this report, you’ll know the basics of technologies such as HDFS, MapReduce, and YARN, without becoming mired in the details. Not only will you learn the basics of how Hadoop works and why it’s such an important technology, you’ll get examples of how you should probably be using it.

Organizations today are swimming in data, but most of them manage to analyze only a fraction of what they collect. To help build a stronger data-driven culture, many organizations are adopting a new approach called self-service analytics. This O’Reilly report examines how this approach provides data access to more people across a company, allowing business users to work with data themselves and create their own customized analyses. The result? More eyes looking at more data in more ways. Along with the perceived benefits, author Sandra Swanson also delves into the potential pitfalls of self-service analytics: balancing greater data access with concerns about security, data governance, and siloed data stores. Read this report and gain insights from enterprise tech (Yahoo), government (the City of Chicago), and disruptive retail (Warby Parker and Talend). Learn how these organizations are handling self-service analytics in practice. Sandra Swanson is a Chicago-based writer who’s covered technology, science, and business for dozens of publications, including ScientificAmerican.com. Connect with her on Twitter (@saswanson) or at www.saswanson.com.

This IBM® Redbooks® publication introduces the latest IBM z Systems™ platforms, the IBM z13™ and IBM z13s. It includes information about the z Systems environment and how it can help integrate data, transactions, and insight for faster and more accurate business decisions. The z13 and z13s are state-of-the-art data and transaction systems that deliver advanced capabilities that are vital to modern IT infrastructures. These capabilities include: Accelerated data and transaction serving Integrated analytics Access to the API economy Agile development and operations Efficient, scalable, and secure cloud services End-to-end security for data and transactions This book explains how these systems use both new innovations and traditional z Systems strengths to satisfy growing demand for cloud, analytics, and mobile applications. With one of these z Systems platforms as the base, applications can run in a trusted, reliable, and secure environment that both improves operations and lessens business risk.

IBM® Spectrum Control (Spectrum Control), a member of the IBM Spectrum™ Family of products, is the next-generation data management solution for software-defined environments (SDEs). With support for block, file, object workloads, and software-defined storage and predictive analytics, and automated and advanced monitoring to identify proactively storage performance problems, Spectrum Control enables administrators to provide efficient management for heterogeneous storage environments. IBM Spectrum Control™ (formerly IBM Tivoli® Storage Productivity Center) delivers a complete set of functions to manage IBM Spectrum Virtualize™, IBM Spectrum Accelerate™, and IBM Spectrum Scale™ storage infrastructures, and traditional IBM and select third-party storage hardware systems. This IBM Redbooks® publication provides practical examples and use cases that can be deployed with IBM Spectrum Control Standard Edition, with an overview of IBM Spectrum Control Advanced Edition. This book complements the Spectrum Control IBM Knowledge Center, which is referenced for product details, and for installation and implementation details throughout this book. You can find this resource as the following website: IBM Spectrum Control Knowledge Center Also provided are descriptions and an architectural overview of the IBM Spectrum Family, highlighting Spectrum Control, as integrated into software-defined storage environments. This publication is intended for storage administrators, clients who are responsible for maintaining IT and business infrastructures, and anyone who wants to learn more about employing Spectrum Control and Spectrum Control Standard Edition.

Dive into the world of regression analysis guided by Python in this comprehensive book. From simple linear regression to complex models, you'll gain a deep understanding of how to analyze data and predict outcomes. By the end of this book, you will be equipped with the skills to tidy data, build models, and apply regression techniques to real-world problems. What this Book will help me do Understand and format datasets to prepare them for regression analysis efficiently. Build and implement various regression models, such as linear and logistic regression, to solve data science problems. Develop techniques to combat overfitting and ensure predictive accuracy. Learn to scale and adapt regression models to large datasets and apply incremental learning. Apply the skills gained to make informed business decisions using predictive insights from regression models. Author(s) Luca Massaron and Alberto Boschetti are seasoned data professionals with years of expertise in data science, regression analysis, and Python programming. They are passionate about teaching and have crafted this book to demystify regression for learners interested in predictive analytics. Their approachable style ensures concepts are accessible yet comprehensive. Who is it for? This book is ideal for Python developers and data scientists who have a foundational knowledge of math and statistics. Whether you're looking to delve deeper into predictive modeling or efficiently analyze datasets, this book provides step-by-step guidance. If you've dabbled in data science and wish to expand your skillset to include regression analysis, this book is for you!

This book delves into the techniques and tools essential for designing, processing, and analyzing complex datasets in real-time using advanced frameworks like Apache Spark, Storm, and Amazon Kinesis. By engaging with this thorough guide, you'll build proficiency in creating robust, efficient, and scalable real-time data processing architectures tailored to real-world scenarios. What this Book will help me do Learn the fundamentals of real-time data processing and how it differs from batch processing. Gain hands-on experience with Apache Storm for creating robust data-driven solutions. Develop real-world applications using Amazon Kinesis for cloud-based analytics. Perform complex data queries and transformations with Spark SQL and understand Spark RDDs. Master the Lambda Architecture to combine batch and real-time analytics effectively. Author(s) Shilpi Saxena is a renowned expert in big data technologies, holding extensive experience in real-time data analytics. With a career spanning years in the industry, Shilpi has provided innovative solutions for big data challenges in top-tier organizations. Her teaching approach emphasizes practical applicability, making her writings accessible and impactful for developers and architects alike. Who is it for? This book is for software professionals such as Big Data architects, developers, or programmers looking to enhance their skills in real-time big data analytics. If you are familiar with basic programming principles and seek to build solutions for processing large data streams in real-time environments, this book caters to your needs. It is also suitable for those seeking to familiarize themselves with using state-of-the-art tools like Spark SQL, Apache Storm, and Amazon Kinesis. Whether you're extending current expertise or transitioning into this field, this resource helps you achieve your objectives.

As an analyst, it's never a good idea to make predictions without data. With that said, for our first predictions episode, we've chosen to make some big and small predictions for the digital analytics space for the remainder of 2016 -- using only experience and intuition! Join us in Episode 30 as we rely solely on intuition to predict the next 9 months of a multi-billion dollar industry - all in under 45 minutes. Note: Due to the lag between recording and release, our prediction during the episode about a certain Heisman Trophy winner actually came true...before this episode launched.

People, places, and things mentioned in this episode:

Tealium Ensighten Signal Mixpanel Amazon Redshift Looker Adobe Analytics Google Analytics Optimizely Adobe Target Johnny Manziel Cleveland Browns Paul DePodesta Moneyball Ben Gaines Median Absolute Deviation (MAD) Brian Clifton Domo Sweetspot Intelligence Tableau Software eMetrics "I Predict a Riot" (Kaiser Chiefs)

While big data has already made significant advances in business and government, data analytics is also beginning to transform education. This O’Reilly report explores how the use of analytics has already helped several educational programs, such as personalized learning and massive open online courses (MOOCs), for students of all ages. Of course, that’s only part of the story. As author Taylor Martin explains, researchers, educators, and private practitioners in the field have also run into several challenges in bringing the education field up to speed. Issues such as building data infrastructures, integrating data sources, and assuring student privacy still need to be resolved—as does the problem of teaching a new generation of data scientists about the challenges and opportunities unique to education. Download this report and find out what educators and analysts have accomplished so far, and how they hope data analytics will help improve outcomes for students, parents, schools, and teachers in the near future. Taylor Martin is a professor of Instructional Technology and Learning Sciences at Utah State University. She researches how people learn from active participation, both physical and social. Currently on rotation at the National Science Foundation, Dr. Martin focuses on a variety of efforts to understand how big data is impacting research in education and across the STEM disciplines.

Companies are collecting more data than ever. But, given how difficult it is to unify the many internal and external data streams they’ve built, more data doesn’t necessarily translate into better analytics. The real challenge is to provide deep and broad access to “a single source of truth” in their data that the typically slow ETL process for data warehousing cannot achieve. More than just fast access, analysts need the ability to explore data at a granular level. In this O’Reilly report, author Courtney Webster presents a roadmap to data centralization that will help your organization make data accessible, flexible, and actionable. Building a genuine data-driven culture depends on your company’s ability to quickly act upon new findings. This report explains how. Identify stakeholders: build a culture of trust and awareness among decision makers, data analysts, and quality management Create a data plan: define your needs, specify your metrics, identify data sources, and standardize metric definitions Centralize the data: evaluate each data source for existing common fields and, if you can, minor variances, and standardize data references Find the right tool(s) for the job: choose from legacy architecture tools, managed and cloud-only services, and data visualization or data exploration platforms Courtney Webster is a reformed chemist in the Washington, D.C. metro area. She spent a few years after grad school programming robots to do chemistry and is now managing web and mobile applications for clinical research trials.

Key Business Analytics will help managers apply tools to turn data into insights that help them better understand their customers, optimise their internal processes and identify cost savings and growth opportunities.

Philosopher, poet, and essayist George Santayana wrote, "Those who cannot remember the past are condemned to repeat it." We thought we'd have him on to reflect about the history of digital analytics...but he died in 1952. Ambrose Bierce wrote The Devil's Dictionary, which we think is brilliant, so we thought we would have him on...but he died in 1842! Lucky for us, we landed the best of both worlds with very-much-alive philosopher, poet, essayist, DAA founder and chairman, and eMetrics founder Jim Sterne.

People, places, and things mentioned in this episode officially ran a full, certifiable gamut:

The Devil's Data Dictionary The Digital Analytics Association (DAA) eMetrics The Web Analyst's Code of Ethics Some "web analytics" platforms: Sawmill (still going strong!), Analog (less so), NetGenesis (verymuchlessso) The IAB The DMA A bunch of people (or, in one case, an archetype, and, in another a conscious, gestalt, artificial intelligence system): Krista Seiden, Seth Romanow, Eric Peterson, June Li, Stéphane Hamel, Josh Aberant, HiPPOs, Skynet

Dynamic organizations want to accelerate growth while reducing costs. To do so, they must speed the deployment of business applications and adapt quickly to any changes in priorities. Organizations require an IT infrastructure to be easy, efficient, and versatile. The VersaStack solution by Cisco and IBM® can help you accelerate the deployment of your datacenters. It reduces costs by more efficiently managing information and resources while maintaining your ability to adapt to business change. The VersaStack solution combines the innovation of Cisco Unified Computing System (Cisco UCS) Integrated Infrastructure with the efficiency of the IBM Storwize® storage system. The Cisco UCS Integrated Infrastructure includes the Cisco UCS, Cisco Nexus and Cisco MDS switches, and Cisco UCS Director. The IBM Storwize V7000 storage system enhances virtual environments with its Data Virtualization, IBM Real-time Compression™, and IBM Easy Tier® features. These features deliver extraordinary levels of performance and efficiency. The VersaStack solution is Cisco Application Centric Infrastructure (ACI) ready. Your IT team can build, deploy, secure, and maintain applications through a more agile framework. Cisco Intercloud Fabric capabilities help enable the creation of open and highly secure solutions for the hybrid cloud. These solutions accelerate your IT transformation while delivering dramatic improvements in operational efficiency and simplicity. Cisco and IBM are global leaders in the IT industry. The VersaStack solution gives you the opportunity to take advantage of integrated infrastructure solutions that are targeted at enterprise applications, analytics, and cloud solutions. The VersaStack solution is backed by Cisco Validated Designs (CVDs) to provide faster delivery of applications, greater IT efficiency, and less risk. This IBM Redbooks® publication is aimed at experienced storage administrators that are tasked with deploying a VersaStack solution with IBM DB2® High Availability (DB2 HA), IBM Spectrum™ Protect, and IBM Spectrum Control™.

Stéphane stirs up trouble (again) and reveals why your analytics are going nowhere. After years of investigating the strengths and weaknesses demonstrated by digitally mature (and mostly immature) organizations, Stéphane reveals the naked truth of the latest results of the Digital Analytics Maturity self-assessment, spiced up with useful tips and thought provoking anecdotes. Make sure to complete your own digital analytics maturity self-assessment before the session!

In this workshop, Stéphane will present the five key areas of maturity and share a tremendous amount of tips and pitfalls gleaned from hundreds of practitioners and managers who gave the model the test of fire.

For years, the advertising industry has relied on so called creative campaigns to boost GRPs and attribute marketing program effectiveness to end of funnel sales. Digital, and more specifically analytics, has brought about promises of transparency through numbers while remaining confined to the realm of measurability. Actors, battling for budgets, are all trying to technologically trace back and attribute the spark that made that very purchase happen, call it attribution or direct, last click, first click, what ever... conversion. After years of experience in the Digital sector, René has joined Neo@Ogilvy, Ogilvy & Mather’s global media agency and performance network where he’s building an Analytics team from scratch. René will share what he’s building, moving beyond traditional site centric Digital Analytics. His challenges encompass data integrations, bringing together CRM data to fuel campaigns, being able to measure the impact of the online channel in offline sales. It’s about helping clients transform the way they use technology and transform their business.

Data quality is often taken for granted. Many organizations fall into complacency with tools like Google Analytics, where tracking is installed but rarely optimized, configured, or scrutinized. As it turns out, this type of plug-and-play analytics can be detrimental to your measurement strategy. In this talk, Simo will show his experiences of working with vastly different organizations and methodologies for tag management, highlighting the format with which he's had most success. He will also showcase how a basic setup of Google Analytics (or any other popular web analytics platform) is simply not enough, together with a case study or two of how to turn the limitations of these platforms to your advantage.

Demonstrate any Digital Analytics solutions or method of your own that is way beyond the defaults. Who decides who’s gonna win? The audience. Send your nomination to [email protected]!