Master the Big Data Capabilities of Oracle R Enterprise Effectively manage your enterprise’s big data and keep complex processes running smoothly using the hands-on information contained in this Oracle Press guide. Oracle R Enterprise: Harnessing the Power of R in Oracle Database shows, step-by-step, how to create and execute large-scale predictive analytics and maintain superior performance. Discover how to explore and prepare your data, accurately model business processes, generate sophisticated graphics, and write and deploy powerful scripts. You will also find out how to effectively incorporate Oracle R Enterprise features in APEX applications, OBIEE dashboards, and Apache Hadoop systems. Learn to: • Install, configure, and administer Oracle R Enterprise • Establish connections and move data to the database • Create Oracle R Enterprise packages and functions • Use the R language to work with data in Oracle Database • Build models using ODM, ORE, and other algorithms • Develop and deploy R scripts and use the R script repository • Execute embedded R scripts and employ ORE SQL API functions • Map and manipulate data using Oracle R Advanced Analytics for Hadoop • Use ORE in Oracle Data Miner, OBIEE, and other applications

Spark in Action teaches you the theory and skills you need to effectively handle batch and streaming data using Spark. Fully updated for Spark 2.0. About the Technology Big data systems distribute datasets across clusters of machines, making it a challenge to efficiently query, stream, and interpret them. Spark can help. It is a processing system designed specifically for distributed data. It provides easy-to-use interfaces, along with the performance you need for production-quality analytics and machine learning. Spark 2 also adds improved programming APIs, better performance, and countless other upgrades. About the Book Spark in Action teaches you the theory and skills you need to effectively handle batch and streaming data using Spark. You'll get comfortable with the Spark CLI as you work through a few introductory examples. Then, you'll start programming Spark using its core APIs. Along the way, you'll work with structured data using Spark SQL, process near-real-time streaming data, apply machine learning algorithms, and munge graph data using Spark GraphX. For a zero-effort startup, you can download the preconfigured virtual machine ready for you to try the book's code. What's Inside Updated for Spark 2.0 Real-life case studies Spark DevOps with Docker Examples in Scala, and online in Java and Python About the Reader Written for experienced programmers with some background in big data or machine learning. About the Authors Petar Zečević and Marko Bonaći are seasoned developers heavily involved in the Spark community. Quotes Dig in and get your hands dirty with one of the hottest data processing engines today. A great guide. - Jonathan Sharley, Pandora Media Must-have! Speed up your learning of Spark as a distributed computing framework. - Robert Ormandi, Yahoo! An easy-to-follow, step-by-step guide. - Gaurav Bhardwaj, 3Pillar Global An ambitiously comprehensive overview of Spark and its diverse ecosystem. - Jonathan Miller, Optensity

Real-world tips for creating business value Details on modeling, data clustering, and more Enterprise use cases to help you get started Learn to predict the future! Business today relies on effectively using data to predict trends and sales. Predictive analytics is the tool that can make it happen, and this book eliminates the tricks and shows you how to use it. You'll learn to prepare and process your data, create goals, build a predictive model, get your organization's stakeholders on board, and more. Inside... How to start a project Identifying data types Modeling tips Working with algorithms How data clustering works How data classification works How deep learning works Advice on presentations Step-by-step predictive modeling

You know what season it is? Well, in the United States, we're closing out a 4-year, never-ending cycle of electing a president. The tweets are getting tweeted and retweeted, the Facebook posts are getting posted and reacted to, and the video! Oh, the video! So, what better time to dive into social media ANALYTICS than today? Join Michael and Tim as they dive into this topic -- which they both love to hate -- with Hayes Davis, co-founder and CEO of Union Metrics. You might even want to Snapchat a filtered picture of yourself listening to it to someone! Miscellany mentioned in this episode include: Union Metrics, Great Lakes Brewery Christmas Ale, The Innovator's Dilemma, Oreo's Super Bowl Blackout tweet, WhatsApp, Scott Brinker on People vs. Data/Strategy/Technology, csvkit, SQLite, medium.com, and Is this my interface or yours?

Fast Data Processing with Spark 2 takes you through the essentials of leveraging Spark for big data analysis. You will learn how to install and set up Spark, handle data using its APIs, and apply advanced functionality like machine learning and graph processing. By the end of the book, you will be well-equipped to use Spark in real-world data processing tasks. What this Book will help me do Install and configure Apache Spark for optimal performance. Interact with distributed datasets using the resilient distributed dataset (RDD) API. Leverage the flexibility of DataFrame API for efficient big data analytics. Apply machine learning models using Spark MLlib to solve complex problems. Perform graph analysis using GraphX to uncover structural insights in data. Author(s) Krishna Sankar is an experienced data scientist and thought leader in big data technologies. With a deep understanding of machine learning, distributed systems, and Apache Spark, Krishna has guided numerous projects in data engineering and big data processing. Matei Zaharia, the co-author, is also widely recognized in the field of distributed systems and cloud computing, contributing to Apache Spark development. Who is it for? This book is catered to software developers and data engineers with a foundational understanding of Scala or Java programming. Beginner to medium-level understanding of big data processing concepts is recommended for readers. If you are aspiring to solve big data problems using scalable distributed computing frameworks, this book is perfect for you. By the end, you will be confident in building Spark-powered applications and analyzing data efficiently.

IBM® DB2® Query Management Facility™ for z/OS® provides a zero-footprint, mobile-enabled, highly secure business analytics solution. IBM QMF™ V11.2.1 offers many significant new features and functions in keeping with the ongoing effort to broaden its usage and value to a wider set of users and business areas. In this IBM Redbooks® publication, we explore several of the new features and options that are available within this new release. This publication introduces TSO enhancements for QMF Analytics for TSO and QMF Enhanced Editor. A chapter describes how the QMF Data Service component connects to multiple mainframe data sources to accomplish the consolidation and delivery of data. This publication describes how self-service business intelligence can be achieved by using QMF Vision to enable self-service dashboards and data exploration. A chapter is dedicated to JavaScript support, demonstrating how application developers can use JavaScript to extend the capabilities of QMF. Additionally, this book describes methods to take advantage of caching for reduced CPU consumption, wider access to information, and faster performance. This publication is of interest to anyone who wants to better understand how QMF can enable in-place analytics with live enterprise data.

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 today require an IT infrastructure that is easy, efficient, and versatile. The VersaStack solution by Cisco and IBM® can help you accelerate the deployment of your data centers. 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 UCS Integrated Infrastructure with the efficiency of the IBM Storwize® storage system. The Cisco UCS Integrated Infrastructure includes the Cisco Unified Computing System (Cisco UCS), Cisco Nexus and Cisco MDS switches, and Cisco UCS Director. The IBM FlashSystem® V9000 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 (CVD) to provide faster delivery of applications, greater IT efficiency, and less risk. This IBM Redbooks® publication is aimed at experienced storage administrators who are tasked with deploying a VersaStack solution with Oracle Real Application Clusters (RAC) and IBM Spectrum™ Protect.

In this session, Dr. Nipa Basu, Chief Analytics Officer, Dun&Bradstreet, sat with Vishal Kumar, CEO AnalyticsWeek and shared her journey as Chief Analytics Officer, life @ D&B, Future of Credit Scoring, and some challenges/opportunities she's observing as an industry observer, executive, and practitioner.

Timeline: 0:29 Nipa's background. 4:14 What is D&B? 7:40 Depth and breadth of decision making at D&B. 9:36 Matching security with technological evolution. 13:42 Anticipatory analytics. 16:00 CAO's role in D&B: in facing or outfacing? 18:32 Future of credit scoring. 21:36 Challenges in dealing with clients. 24:08 Cultural challenges. 28:42 Good use cases in security data. 31:51 CDO, CAO, and CTO. 33:56 Optimistic trends data analytics businesses. 36:44 Social data monitoring. 39:18 Creating a holistic model for data monitoring. 41:02 Overused terms in data analytics. 42:10 Best practices for small businesses to get started with data analytics. 44:33 Indicators that indicate the need for analytics for businesses. 47:06 Advice for data-driven leaders. 49:30 Art of doing business and science of doing business.

Podcast link: https://futureofdata.org/analyticsweek-leadership-podcast-with-dr-nipa-basu-dun-bradstreet/

Here's Nipa's Bio: Dr. Nipa Basu is the Chief Analytics Officer at Dun & Bradstreet. Nipa is the main source of inspiration and leadership for Dun & Bradstreet’s extensive team of data modelers and scientists that partner with the world’s leading Fortune 500 companies to create innovative, analytic solutions to drive business growth and results. The team is highly skilled in solving a wide range of business challenges with unique, basic, and advanced analytic applications.

Nipa joined Dun & Bradstreet in 2000 and since then has held key leadership roles focused on driving the success of Dun & Bradstreet’s Analytics practice. In 2012, Nipa was named Leader, Analytic Development, and in March 2015, Nipa was named Chief Analytics Officer and appointed to Dun & Bradstreet’s executive team.

Nipa began her professional career as an Economist with the New York State Legislative Tax Study Commission. She then joined Sandia National Laboratories, a national defense laboratory where she built a Microsimulation Model of the U.S. Economy. Prior to joining Dun & Bradstreet, Nipa was a database marketing statistician for AT&T with responsibility for building predictive marketing models.

Nipa received her Ph. D. in Economics from the State University of New York at Albany, specializing in Econometrics.

Follow @nipabasu

The podcast is sponsored by: TAO.ai(https://tao.ai), Artificial Intelligence Driven Career Coach

About #Podcast:

FutureOfData podcast is a conversation starter to bring leaders, influencers, and lead practitioners to discuss their journey to create the data-driven future.

Want to Join? If you or any you know wants to join in, Register your interest @ http://play.analyticsweek.com/guest/

Want to sponsor? Email us @ [email protected]

Keywords:

FutureOfData #DataAnalytics #Leadership #Podcast #BigData #Strategy

In this session, Joe DeCosmo, Chief Analytics Officer, Enova International, sat with Vishal Kumar, CEO AnalyticsWeek and shared his journey to Chief Analytics Officer, life @ Enova, and some challenges/opportunities as he is observing as an executive, industry observer, and a Chief Analytics Officer.

Timeline: 0:29 Joe's journey. 5:05 Credit risk and fraud prevention models. 6:27 Enova: in facing or outfacing? 9:12 Enova area of expertise. 10:47 Enova decisions: Center of Excellence? 12:36 Depths and breadths of decision making at Enova. 14:51 CDO, CAO, and CTO. 17:24 Who owns the data at Enova? 19:55 Challenges in building a data culture. 25:52 Convincing leaders towards data science. 31:24 Business challenges that analytics is solving. 34:15 Getting started with data analytics as a business. 38:11 Exciting trends in data analytics. 41:09 Art of doing business and science of doing business. 44:00 Advice for budding CAOs.

Podcast link: https://futureofdata.org/analyticsweek-leadership-podcast-with-joe-decosmo-enova-international/

Here's Joe's Bio: Joe DeCosmo is the CAO of Enova International, where he leads a multi-disciplinary analytics team, providing end-to-end data and analytic services to Enova’s global online financial service brands and delivering real-time predictive analytics services to clients through Enova Decisions. Prior to Enova, Joe served as Director and Practice Leader of Advanced Analytics for West Monroe Partners and held a number of executive positions at HAVI Global Solutions and the Allant Group. He is also Immediate Past-President of the Chicago Chapter of the American Statistical Association and serves on the Advisory Board of the University of Illinois at Chicago's College of Business.

The podcast is sponsored by: TAO.ai(https://tao.ai), Artificial Intelligence Driven Career Coach

About #Podcast:

FutureOfData podcast is a conversation starter to bring leaders, influencers, and lead practitioners to discuss their journey to create the data-driven future.

Want to Join? If you or any you know wants to join in, Register your interest @ http://play.analyticsweek.com/guest/

Want to sponsor? Email us @ [email protected]

Keywords:

FutureOfData #DataAnalytics #Leadership #Podcast #BigData #Strategy

Have you ever read an analytics job description? Have you found yourself wondering, "Is it just me, or is there something fishy going on here?" Who better to verbally cogitate this question writ large than a couple of guys who haven't actually applied for a job in a few years? Join Michael and Tim as they dive into the world of analytics job descriptions and chat about the red flags they find...and the various tangential thoughts that the exercise itself sparks. Resources mentioned in this episode include: the Digital Analytics Association, Google Tag Manager Updates: Workspaces and User Manager by Amanda Schroeder from LunaMetrics, Revamped User Interface in Google Tag Manager by Simo Ahava.

Resolve data-heavy retail marketing questions through key analytic steps, with expert guidance in a direct and conceptual style.

Explore how to leverage Apache Spark for efficient big data analytics and machine learning solutions in "Spark for Data Science". This detailed guide provides you with the skills to process massive datasets, perform data analytics, and build predictive models using Spark's powerful tools like RDDs, DataFrames, and Datasets. What this Book will help me do Gain expertise in data processing and transformation with Spark. Perform advanced statistical analysis to uncover insights. Master machine learning techniques to create predictive models using Spark. Utilize Spark's APIs to process and visualize big data. Build scalable and efficient data science solutions. Author(s) This book is co-authored by None Singhal and None Duvvuri, both accomplished data scientists with extensive experience in Apache Spark and big data technologies. They bring their practical industry expertise to explain complex topics in a straightforward manner. Their writing emphasizes real-world applications and step-by-step procedural guidance, making this a valuable resource for learners. Who is it for? This book is ideally suited for technologists seeking to incorporate data science capabilities into their work with Apache Spark, data scientists interested in machine learning algorithms implemented in Spark, and beginners aiming to step into the field of big data analytics. Whether you are familiar with Spark or completely new, this book offers valuable insights and practical knowledge.

Dive into the world of big data with "Big Data Analytics: Real Time Analytics Using Apache Spark and Hadoop." This comprehensive guide introduces readers to the fundamentals and practical applications of Apache Spark and Hadoop, covering essential topics like Spark SQL, DataFrames, structured streaming, and more. Learn how to harness the power of real-time analytics and big data tools effectively. What this Book will help me do Master the key components of Apache Spark and Hadoop ecosystems, including Spark SQL and MapReduce. Gain an understanding of DataFrames, DataSets, and structured streaming for seamless data handling. Develop skills in real-time analytics using Spark Streaming and technologies like Kafka and HBase. Learn to implement machine learning models using Spark's MLlib and ML Pipelines. Explore graph analytics with GraphX and leverage data visualization tools like Jupyter and Zeppelin. Author(s) Venkat Ankam, an expert in big data technologies, has years of experience working with Apache Hadoop and Spark. As an educator and technical consultant, Venkat has enabled numerous professionals to gain critical insights into big data ecosystems. With a pragmatic approach, his writings aim to guide readers through complex systems in a structured and easy-to-follow manner. Who is it for? This book is perfect for data analysts, data scientists, software architects, and programmers aiming to expand their knowledge of big data analytics. Readers should ideally have a basic programming background in languages like Python, Scala, R, or SQL. Prior hands-on experience with big data environments is not necessary but is an added advantage. This guide is created to cater to a range of skill levels, from beginners to intermediate learners.

Do you listen to podcasts? Well, of course you do! Are you working in or involved with analytics? If you listen to this podcast, you almost certainly are! Where do those two interests intersect? On this episode! Steve Mulder, Senior Director of Audience Insights at National Public Radio (NPR), joins Michael and Tim to discuss podcast measurement...and audience measurement...and the evolution of analytics...and standards (well...guidelines)...and more! Tim fanboys out in a way that would be embarrassing if he was sufficiently self-aware to be embarrassed. In other words, it's a rollicking good romp through public media. Resources and the like mentioned in this episode are many and varied: The User Is Always Right, Podtrac, Public Broadcasting Podcast Measurement Guidelines (bit.ly/podcastguidelines), Comscore, DFP, Splunk, NPR One, Panoply Network, Gimlet Media, IAB, MediaShift: Bulgarian Analytics Startup Aims to Fix How Publishers Use Data, Smart Choices: A Practical Guide to Making Better Decisions, the NPR Politics Podcast, and Planet Money #669: A or B.

In this session, Beena Ammanath, Data Science Products at General Electric, sat with Vishal Kumar, CEO AnalyticsWeek and shared her journey as an analytics executive, life @ GE, future of analytics in the industrial sector, how Predix is helping other industrial companies cope up with growing data, and some challenges/Opportunities she's observing as an analytics executive.

Timeline: 0:29 Beena's journey. 5:19 Data science in the manufacturing sector. 7:03 Driving data science in the manufacturing sector. 9:39 Bringing in the data culture into the manufacturing sector. 11:35 Upskilling and being relevant as a data scientist. 13:27 Hacks to managing data teams well. 16:08 What's Predix? 19:06 Investment opportunities for data science in manufacturing. 21:07 Challenges manufacturing businesses in data. 24:46 IoT and manufacturing. 25:18 Dealing with IoT vendors at Predix. 26:24 Ontology of data at Predix. 29:43 Dealing with the new rules and laws in the IoT sector. 31:30 Interesting use cases in the manufacturing industry. 34:37 Open source vs. enterprise. 35:35 Getting recruited as a data scientist in manufacturing. 40:07 Pitching your product for a manufacturing company.

Podcast link: https://futureofdata.org/leadership-playbook-with-beena-ammanath-ge/

Here's Beena's Bio: Beena Ammanath is Board Director at ChickTech and Head of Data Science Products at General Electric. She is a seasoned technology leader with over 24 years of a proven track record of building, and leading high-performance teams from the ground-up focused on strategy and successful execution of industrial scale technology products and services. She has an impressive track record, having worked at recognized international organizations British Telecom, E*trade, Thomson Reuters, Bank of America, and Silicon Valley startups in engineering and management positions.

She is also helping build the next-gen of computer scientists through her role on the Industry Advisory Board for Cal Poly. She holds a Masters in Computer Science and an MBA in Finance. She has been a featured speaker on the topics of data science, big data, technology transformation, and women in leadership at numerous industry conferences.

Throughout her career in technology, Beena has been a strong advocate for women in positions of technology leadership and has established herself as a voice for resolving gender disparities.

Follow @beena_ammanath

The podcast is sponsored by: TAO.ai(https://tao.ai), Artificial Intelligence Driven Career Coach

About #Podcast:

FutureOfData podcast is a conversation starter to bring leaders, influencers, and lead practitioners to discuss their journey to create the data-driven future.

Want to Join? If you or any you know wants to join in, Register your interest @ http://play.analyticsweek.com/guest/

Want to sponsor? Email us @ [email protected]

Keywords:

FutureOfData #DataAnalytics #Leadership #Podcast #BigData #Strategy

Use aggregate data to answer high-level business questions!

Data miners, data scientists, analytic managers, and analysts who work in all industries will find the insights in Randy Collica's Strategic Analytics and SAS: Using Aggregate Data to Drive Organizational Initiatives invaluable in their work. This book shows you how to use your existing data at aggregate levels to answer high-level business questions. Written in a detailed, step-by-step format, the multi-industry use cases begin with a high-level question that a C-level executive might ask. Collica then progresses through the steps to perform the analysis, including many tables and screenshots to guide you along the way. He then ends each use case with the solution to the high-level question. Topics covered include logistic analysis, models developed from surveys, survival analysis, confidence intervals, text mining and analysis, visual analytics, hypothesis tests, and size and magnitude of analytic effects. Connect the dots between detailed data on your customers and the high-level business goals of your organization with Strategic Analytics and SAS!

User experience monitoring is essential for enhancing the usability and performance of your mobile native app. How are your customers using your product? Which features do they prefer? How can you spot trouble before it adversely affects your product? This O’Reilly report provides an overview of several metrics you can apply, based on different use-cases. Author Wolfgang Beer explains the typical instrumentation and publishing process of mobile apps, and takes you through different instrumentation approaches. With screenshots from popular tools such as Google Analytics, Ruxit, Fabric, and Flurry Analytics, this report helps you choose the metrics that will help you improve your product’s performance. Monitor performance to understand your app’s stability and usability Measure app user engagement by identifying active and new users, and determining median session length Determine your app’s current retention and churn rates Gather business intelligence by defining users according to personas and lifetime value Oversee the service and infrastructure dependencies of your app in real time Visually track user behavior with heat maps and navigational paths Add automated or manual instrumentation before you publish your app

How to lead the change Analytics are driving big changes, not only in what marketing departments do but in how they are organized, staffed, led, and run. Leaders are grappling with issues that range from building an analytically driven marketing organization and determining the kinds of structure and talent that are needed to leading interactions with IT, finance, and sales and creating a unified view of the customer. The Analytical Marketer provides critical insight into the changing marketing organization—digital, agile, and analytical—and the tools for reinventing it. Written by the head of global marketing for SAS, The Analytical Marketer is based on the author’s firsthand experience of transforming a marketing organization from “art” to “art and science.” Challenged and inspired by their company’s own analytics products, the SAS marketing team was forced to rethink itself in order to take advantage of the new capabilities that those tools offer the modern marketer. Key marketers and managers at SAS tell their stories alongside the author’s candid lessons learned as she led the marketing organization’s transformation. With additional examples from other leading companies, this book is a practical guide and set of best practices for creating a new marketing culture that thrives on and adds value through data and analytics.

A complete, start-to-finish guide to Google Analytics instrumentation and reporting Google Analytics Breakthrough is a much-needed comprehensive resource for the world's most widely adopted analytics tool. Designed to provide a complete, best-practices foundation in measurement strategy, implementation, reporting, and optimization, this book systematically demystifies the broad range of Google Analytics features and configurations. Throughout the end-to-end learning experience, you'll sharpen your core competencies, discover hidden functionality, learn to avoid common pitfalls, and develop next-generation tracking and analysis strategies so you can understand what is helping or hindering your digital performance and begin driving more success. Google Analytics Breakthrough offers practical instruction and expert perspectives on the full range of implementation and reporting skills: Learn how to campaign-tag inbound links to uncover the email, social, PPC, and banner/remarketing traffic hiding as other traffic sources and to confidently measure the ROI of each marketing channel Add event tracking to capture the many important user interactions that Google Analytics does not record by default, such as video plays, PDF downloads, scrolling, and AJAX updates Master Google Tag Manager for greater flexibility and process control in implementation Set up goals and Enhanced Ecommerce tracking to measure performance against organizational KPIs and configure conversion funnels to isolate drop-off Create audience segments that map to your audience constituencies, amplify trends, and help identify optimization opportunities Populate custom dimensions that reflect your organization, your content, and your visitors so Google Analytics can speak your language Gain a more complete view of customer behavior with mobile app and cross-device tracking Incorporate related tools and techniques: third-party data visualization, CRM integration for long-term value and lead qualification, marketing automation, phone conversion tracking, usability, and A/B testing Improve data storytelling and foster analytics adoption in the enterprise As many as 10-25 million organizations have installed Google Analytics, including an estimated 67 percent of Fortune 500 companies, but deficiencies plague most implementations, and inadequate reporting practices continue to hinder meaningful analysis. By following the strategies and techniques in Google Analytics Breakthrough, you can address the gaps in your own still set, transcend the common limitations, and begin using Google Analytics for real competitive advantage. Critical contributions from industry luminaries such as Brian Clifton, Tim Ash, Bryan and Jeffrey Eisenberg, and Jim Sterne – and a foreword by Avinash Kaushik – enhance the learning experience and empower you to drive consistent, real-world improvement through analytics.

Targeted analytics to address the unique opportunities in hospitality and gaming The Analytic Hospitality Executive helps decision makers understand big data and how it can drive value in the industry. Written by a leading business analytics expert who specializes in hospitality and travel, this book draws a direct link between big data and hospitality, and shows you how to incorporate analytics into your strategic management initiative. You'll learn which data types are critical, how to identify productive data sources, and how to integrate analytics into multiple business processes to create an overall analytic culture that turns information into insight. The discussion includes the tools and tips that help make it happen, and points you toward the specific places in your business that could benefit from advanced analytics. The hospitality and gaming industry has unique needs and opportunities, and this book's targeted guidance provides a roadmap to big data benefits. Like most industries, the hospitality and gaming industry is experiencing a rapid increase in data volume, variety, and velocity. This book shows you how to corral this growing current, and channel it into productive avenues that drive better business. Understand big data and analytics Incorporate analytics into existing business processes Identify the most valuable data sources Create a strategic analytic culture that drives value Although the industry is just beginning to recognize the value of big data, it's important to get up to speed quickly or risk losing out on benefits that could drive business to greater heights. The Analytic Hospitality Executive provides a targeted game plan from an expert on the inside, so you can start making your data work for you.