In this episode, Microsoft's Corporate Vice President for Cloud Artificial Intelligence, Joseph Sirosh, joins host Kyle Polich to share some of the Microsoft's latest and most exciting innovations in AI development platforms. Last month, Microsoft launched a set of three powerful new capabilities in Azure Machine Learning for advanced developers to exploit big data, GPUs, data wrangling and container-based model deployment. Extended show notes found here. Thanks to our sponsor Springboard.  Check out Springboard's Data Science Career Track Bootcamp.

In this podcast, Pascal Marmier sat with Vishal Kumar to discuss challenges, opportunities, and nuances in running an innovation hub within regulated corporate culture settings and shared some best practices in promoting data driven innovation.

Timeline: 0:29 Pascal's journey. 6:12 Quitting law and getting into digital analytics. 10:44 Defining Head Analytics Catalyst. 13:46 Putting up an Analytics Catalyst team. 18:43 Steps to create a data lab. 22:02 Securing executive sponsorship. 25:45 Differences in creating lab in Europe in comparison to the USA. 29:43 Challenges in setting up a digital analytics catalyst. 32:27 Ideal team members to have in a digital analytics catalyst team. 35:14 Company culture interfering with lab innovation. 38:00 Lab innovation determining the company's future. 42:19 Important KPIs for setting up a lab. 46:55 Prophesy on the insurance company. 51:15 What can insurance do to secure themselves? 54:48 Insurance dealing with changing risk profiles. 59:26 Pascal's favorite read. 1:00:56 Closing remarks.

Podcast link: https://futureofdata.org/pascal-marmier-pmarmier-swissre-discuss-running-data-driven-innovation-catalyst/

About Pascal Marmier: After many years helping to build the swissnex network in Boston and in China, I recently joined Swiss Re in Boston to help the Digital Analytics Catalyst team identify and develop novel ideas/tech into a sustainable business. As part of the digital transformation of the insurance industry, our team in Boston and London is engaging with startups and academia in various fields of technology such as digital health, IoT, AI. We are working with the teams at Swiss Re to provide business solutions based on the transformative power of data innovation.

Pascal's Favorite Read: Sapiens: A Brief History of Humankind http://amzn.to/2yHvYGV 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.

Wanna 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 Data Analytics Leadership Podcast Big Data Strategy

In this Podcast, Charlie Berger from Oracle discussed some of the challenges of data-driven enterprises.

Timeline: 0:29 Charlie's journey. 6:12 Charlie's current role. 8:55 Oracle's role in the future of data. 13:20 The evolution of ML. 20:41 The need for revaluating mathematical models that data science is based on. 27:50 On the concept of appification of analytics. 36:17 On enterprise IT landscape changing. 43:17 Geekifying analytics. 47:15 Charlie's favorite read. 50:21 Closing remarks.

Charlie's favorite read suggestions: 1. The Naked Future: What Happens in a World That Anticipates Your Every Move?

Podcast link: https://futureofdata.org/futureofdata-charliedatamine-oracle-discussing-running-analytics-enterprise/

Charlie's BIO: Passionate technical professional skilled in building entrepreneurial, start-up initiatives, and environments. Strong technical, product management, communication, marketing, and leadership skills.

• Experienced product management professional with over 30 years of experience in leading-edge technologies in large corporations and entrepreneurial start-ups. • During 15 years at Oracle Corporation, developed an innovative portfolio of “big data analytics” products developed as in-database SQL data mining functions and integrated "predictive analytics" applications. • Strong technical, product management, communication, and leadership skills. • Responsible for product management and direction for the Oracle Database data mining and predictive analytics technology, including Oracle Data Mining, text mining, and statistical functions. • Strong product champion, evangelist, and frequent speaker in the field of predictive analytics and data mining. • Leveraged relationships with customers, development, and sales to communicate product capabilities and value proposition.

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.

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Keywords: FutureOfData Data Analytics Leadership Podcast Big Data Strategy

This book is your gateway to mastering machine learning with Apache Spark 2.x. Through detailed hands-on recipes, you'll delve into building scalable ML models, optimizing big data processes, and enhancing project efficiency. Gain practical knowledge and explore real-world applications of recommendations, clustering, analytics, and more with Spark's powerful capabilities. What this Book will help me do Understand how to integrate Scala and Spark for effective machine learning development. Learn to create scalable recommendation engines using Spark. Master the development of clustering systems to organize unlabelled data at scale. Explore Spark libraries to implement efficient text analytics and search engines. Optimize large-scale data operations, tackling high-dimensional issues with Spark. Author(s) The team of authors brings expertise in machine learning, data science, and Spark technologies. Their combined industry experience and academic knowledge ensure the book is grounded in practical applications while offering theoretical insights. With clear explanations and a step-by-step approach, they aim to simplify complex concepts for developers and data scientists. Who is it for? This book is crafted for Scala developers familiar with machine learning concepts but seeking practical applications with Spark. If you have been implementing models but want to scale them and leverage Spark's robust ecosystem, this guide will serve you well. It is ideal for professionals seeking to deepen their skills in Spark and data science.

In this Podcast, Jay talks about the landscape of Information Security and how businesses are preparing to address their cybersecurity challenges. This is a great podcast for anyone interested in learning about best practices when it comes to managing infrastructure security for their organization.

Timeline: 0:29 Jay's journey. 3:18 What's Scientia Institute? 8:28 The book Data-Driven Security. 10:42 The aha moment while writing the book. 11:53 High points of Jay's book. 14:08 Security level of a typical business today. 16:22 Thoughts on how companies can understand risk. 19:50 Balancing mitigation of threat vs. business continuity. 25:33 Treating security as a financial problem. 27:25 Security predictability and insurance. 28:44 Who should take responsibility for risk and security? 30:15 Measuring the risk of company infrastructure. 31:33 Tackling standards and regulations. 33:04 The concept of best practices. 34:38 The maturity of the model in the security side of businesses. 37:55 The lower limit and higher limit of security. 39:50 Resources to learn about security. 41:11 Who's a good security candidate? 42:20 Jay's favorite read. 43:36 Examples of companies who're doing well in security. 45:28 What's next in the world of security. 47:40 Closing remarks.

Podcast link: https://futureofdata.org/understanding-data-analytics-information-security-jayjarome-bitsight/

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.

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

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Keywords: FutureOfData Data Analytics Leadership Podcast Big Data Strategy

Every enterprise application creates data, whether it’s log messages, metrics, user activity, outgoing messages, or something else. And how to move all of this data becomes nearly as important as the data itself. If you’re an application architect, developer, or production engineer new to Apache Kafka, this practical guide shows you how to use this open source streaming platform to handle real-time data feeds. Engineers from Confluent and LinkedIn who are responsible for developing Kafka explain how to deploy production Kafka clusters, write reliable event-driven microservices, and build scalable stream-processing applications with this platform. Through detailed examples, you’ll learn Kafka’s design principles, reliability guarantees, key APIs, and architecture details, including the replication protocol, the controller, and the storage layer. Understand publish-subscribe messaging and how it fits in the big data ecosystem. Explore Kafka producers and consumers for writing and reading messages Understand Kafka patterns and use-case requirements to ensure reliable data delivery Get best practices for building data pipelines and applications with Kafka Manage Kafka in production, and learn to perform monitoring, tuning, and maintenance tasks Learn the most critical metrics among Kafka’s operational measurements Explore how Kafka’s stream delivery capabilities make it a perfect source for stream processing systems

In this Podcast Clayton, @theclaymethod from @TiVo sat with Vishal to talk about his experience running analytics group within media landscape and shed light on running analytics in media industry.

Timeline: 0:29 Clayton's journey. 2:50 Clayton's current role as the director of Tivo. 5:13 Clayton's path to become a data scientist. 9:10 Analytics in the media. 12:06 Data in the creative industry. 14:32 Interesting use cases of data in media industry. 17:03 Classifying data for different media platforms. 18:48 Defining a typical data scientist in the media industry. 22:12 Art of doing business and science of doing business. 25:02 Putting together a data science team. 29:26 Successful KPIs in the media industry. 32:47 Interesting companies and products and their data practice. 34:22 Knowing the requirement of an AI/ML model in a business. 37:02 Data science practice in bigger companies. 38:33 Clayton's choice of the media industry. 39:42 Advice for data analysts who want to enter the media industry. 41:42 Mentorship and buddy system. 44:06 Advice for those who are from non engineering background. 47:40 Clayton's favorite reads. 49:40 Clayton's next ideal hire. 51:15 Closing remarks.

Podcast link: https://futureofdata.org/futureofdata-with-theclaymethod-tivo-discussing-running-analytics-in-media-industry/

Bio: Clayton Kim is the Director of Data Science at TiVo, responsible for managing the applications of machine learning and statistical research on TV consumption data. Before TiVo, Clayton was the Sr. Manager of Data Science at Localytics, working on applying predictive intelligence to mobile app analytics and messaging.

About #Podcast:

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"Learning Spark SQL" takes you from data exploration to designing scalable applications with Apache Spark SQL. Through hands-on examples, you will comprehend real-world use cases and gain practical skills crucial for working with Spark SQL APIs, data frames, streaming data, and optimizing Spark applications. What this Book will help me do Understand the principles of Spark SQL and its APIs for building scalable distributed applications. Gain hands-on experience performing data wrangling and visualization using Spark SQL and real-world datasets. Learn how to design and optimize applications for performance and scalability with Spark SQL. Develop the skills to integrate Spark SQL with other frameworks like Apache Kafka for streaming analytics. Master the techniques required to architect machine learning and deep learning solutions using Spark SQL. Author(s) None Sarkar is an experienced technologist and trainer specializing in big data, streaming analytics, and scalable architectures using Apache Spark. With years of practical experience in implementing Spark solutions, Sarkar draws from real-world projects to provide readers with valuable insights. Sarkar's approachable and detailed writing style ensures readers grasp both the theory and the practice of Spark SQL. Who is it for? This book is ideal for software developers, data engineers, and architects aspiring to harness Apache Spark for robust, scalable applications. It suits readers with some SQL querying experience and a basic knowledge of programming in languages like Scala, Java, or Python. Whether you're a Spark newcomer or advancing your capabilities in scalable data processing, this resource will accelerate your learning journey.

Zillow is a leading real estate information and home-related marketplace. We interviewed Andrew Martin, a data science Research Manager at Zillow, to learn more about how Zillow uses data science and big data to make real estate predictions.

Data & Analytics Bi-Weekly Newsletter Cast Aug 31, 2017

Wanna chip-in to help #Houston? Here's the link: https://www.nytimes.com/2017/08/28/us/donate-harvey-charities-scams.html

About #Podcast:

FutureOfData podcast is a conversation starter to bring leaders, influencers and lead practitioners to come on show and discuss their journey in creating the data driven future.

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

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Keywords: FutureOfData Data Analytics Leadership Podcast Big Data Strategy

The New Edition of a Business Classic This landmark work, the first to introduce business leaders to analytics, reveals how analytics are rewriting the rules of competition. Updated with fresh content, Competing on Analytics provides the road map for becoming an analytical competitor, showing readers how to create new strategies for their organizations based on sophisticated analytics. Introducing a five-stage model of analytical competition, Davenport and Harris describe the typical behaviors, capabilities, and challenges of each stage. They explain how to assess your company’s capabilities and guide it toward the highest level of competition. With equal emphasis on two key resources, human and technological, this book reveals how even the most highly analytical companies can up their game. With an emphasis on predictive, prescriptive, and autonomous analytics for marketing, supply chain, finance, M&A, operations, R&D, and HR, the book contains numerous new examples from different industries and business functions, such as Disney’s vacation experience, Google’s HR, UPS’s logistics, the Chicago Cubs’ training methods, and Firewire Surfboards’ customization. Additional new topics and research include: Data scientists and what they do Big data and the changes it has wrought Hadoop and other open-source software for managing and analyzing data Data products—new products and services based on data and analytics Machine learning and other AI technologies The Internet of Things and its implications New computing architectures, including cloud computing Embedding analytics within operational systems Visual analytics The business classic that turned a generation of leaders into analytical competitors, Competing on Analytics is the definitive guide for transforming your company’s fortunes in the age of analytics and big data.

In this podcast, Rob Griffin from Almighty(X), a Connelly partner company, sat with Vishal Kumar to discuss running innovation in a media agency.

Timeline: 0:29 Rob's journey. 8:12 Marketing, the earliest adopter of analytics. 10:43 Defining transformational innovation. 22:05 Art of doing business and science of doing business. 26:12 Problems for an innovative analytics company. 31:00 Innovation in different size companies. 34:31 Common mistakes businesses make on innovation. 40:00 The future of the creative industry. 42:49 ML and AI impact on the digital market. 49:29 Don't be efficient, be creative. 57:39 Rob's recommended books.

Podcast link: https://futureofdata.org/futureofdata-robtelerob-connellyagency-running-innovation-agency/

Here's Rob's Bio: Driving transformational innovation in marketing and advertising. Pushing creative and media technology limits. Helping brands take ownership of their technology, data, and media for greater transparency and accountability. Putting the agent back in the agency. Been working in digital marketing and advertising since 1996. A Bostonian. A die-hard Celtics fan. Dad. Speaker. Writer. Advisor. Skier. Comic book fan. Lover of good eats.

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.

Wanna 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

Data & Analytics Bi-Weekly Newsletter Cast Aug 17, 2017

About #Podcast:

FutureOfData podcast is a conversation starter to bring leaders, influencers and lead practitioners to come on show and discuss their journey in creating the data driven future.

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

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Keywords: FutureOfData Data Analytics Leadership Podcast Big Data Strategy

Mastering Apache Storm is your step-by-step guide to mastering real-time data streaming with this robust framework. You'll learn how to process big data efficiently and integrate Apache Storm with popular technologies like Kafka, HBase, and Redis to maximize its potential. This book walks you through from basic concepts to advanced implementations of Apache Storm in real-world scenarios. What this Book will help me do Understand the core features and operation of Apache Storm for real-time data streaming. Integrate Apache Storm with other Big Data frameworks like Kafka, HBase, Redis, and Hadoop. Effectively deploy and manage multi-node Apache Storm clusters in real-world environments. Monitor and analyze your data streams and system health effectively using built-in and external tools. Learn to implement fault-tolerant, scalable, and distributed stream processing applications in Apache Storm. Author(s) None Jain is an experienced software developer and technical instructor specializing in distributed systems and real-time data processing. With years of experience working with Apache Storm and related technologies, their teachings focus on practical, hands-on learning to equip readers with actionable skills. Who is it for? This book is ideal for Java developers aspiring to build expertise in real-time data streaming and distributed processing applications using Apache Storm. Beginners can start with the fundamentals provided, while those with prior knowledge can delve into intermediate and advanced implementations.

In this conversation, Angela & Joshua from Booz Allen sat down with Vishal to discuss the Mathematical Corporation. They discussed some of the stories, challenges, and opportunities facing any corporation on their journey to a Mathematical corporation.

Timeline: 0:29 Angela and Josh's introduction. 4:00 Inspiration behind their book. 8:20 Machine Intelligence. 12:27 Ideal fit for a business to embrace mathematical organization. 14:54 Convincing executives towards data science. 19:20 Working with data science skeptics. 23:02 How much percent data-driven should a company be? 26:38 Mathematical models being predictable in an unpredictable environment. 30:25 Mathematical organization response to open sources. 34:14 AI the job enabler. 36:52 Advice for small businesses to be data-driven. 39:36 A fully mature mathematical corporation. 44:16 Sleeping on the wheel. 45:28 An ideal reader for the book "Mathematical Corporation". 48:37 The aha moment while writing the book. 50:40 Creating awareness for business to be data-driven. 54:18 Takeaways from "Mathematical Corporation".

Their Book: The Mathematical Organization is out to help the business stay data-driven and competitive. You could download the book @ http://amzn.to/2hNsoaH

THE MATHEMATICAL CORPORATION: Where Machine Intelligence and Human Ingenuity Achieve the Impossible (PublicAffairs; June 6, 2017), by Booz Allen Hamilton machine intelligence experts Joshua Sullivan and Angela Zutavern, is the first book to show business leaders how to compete in this new era: by combining the mathematical smarts of machines with the intellect of visionary leaders.

About the Guest DR. JOSH SULLIVAN is SVP at Booz Allen Hamilton. One of the world’s leading experts in data science and machine intelligence, he was among the first people to hold the title “data scientist.” He has appeared on CNBC.

ANGELA ZUTAVERN is VP at Booz Allen Hamilton and pioneered the application of machine intelligence to leadership and strategy. Together, they’re radically transforming how Fortune 500 companies, nonprofits, and major government agencies perform by helping leaders shatter long-held constraints and reveal hidden truths in their organizations. They live in Washington, D.C.

Podcast link: https://futureofdata.org/angelazutavern-joshdsullivan-boozallen-discussed-mathematical-corporation-futureofdata/

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.

Wanna 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

Data & Analytics Bi-Weekly Newsletter Cast Aug 03, 2017

About #Podcast:

FutureOfData podcast is a conversation starter to bring leaders, influencers and lead practitioners to come on show and discuss their journey in creating the data driven future.

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

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Keywords: FutureOfData Data Analytics Leadership Podcast Big Data Strategy

In this session, Brett McLaughlin, Chief Data Strategist at Akamai, discussed his journey to creating a forecasting solution. He sheds light on some limitations, some innovative thinking, and some hacks that one could use to structure a good forecasting model.

Timeline: 0:29 Brett's journey. 15:06 Data scientist fulling the vision of the CEO. 24:25 Art of doing business and science of doing business. 29:23 Data science and mathematics. 34:55 Salesforce defining the value of algorithms. 38:14 Capturing feedback to improve data models. 46:14 First steps in building a futuristic data model. 54:27 Using algorithms to forecast. 1:01 Tips for data leaders to build a team.

Podcast link: https://futureofdata.org/discussing-forecasting-brett-mclaughlin-akabret-akamai/

Here's Brett's Bio: Twenty-one years of experience transforming business operations through more intelligent use of data. Expertise in leading organizations in data transformation, predictive analytics (e.g., forecasting, linear programming, operational simulations, etc.), world-class visualizations and interfaces, and tight integration into existing operations.

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.

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Keywords:

FutureOfData #DataAnalytics #Leadership #Podcast #BigData #Strategy

Delve into mastering big data processing with 'Apache Spark 2.x for Java Developers.' This book provides a practical guide to implementing Apache Spark using the Java APIs, offering a unique opportunity for Java developers to leverage Spark's powerful framework without transitioning to Scala. What this Book will help me do Learn how to process data from formats like XML, JSON, CSV using Spark Core. Implement real-time analytics using Spark Streaming and third-party tools like Kafka. Understand data querying with Spark SQL and master SQL schema processing. Apply machine learning techniques with Spark MLlib to real-world scenarios. Explore graph processing and analytics using Spark GraphX. Author(s) None Kumar and None Gulati, experienced professionals in Java development and big data, bring their wealth of practical experience and passion for teaching to this book. With a clear and concise writing style, they aim to simplify Spark for Java developers, making big data approachable. Who is it for? This book is perfect for Java developers who are eager to expand their skillset into big data processing with Apache Spark. Whether you are a seasoned Spark user or first diving into big data concepts, this book meets you at your level. With practical examples and straightforward explanations, you can unlock the potential of Spark in real-world scenarios.

Mastering Apache Spark 2.x is the essential guide to harnessing the power of big data processing. Dive into real-time data analytics, machine learning, and cluster computing using Apache Spark's advanced features and modules like Spark SQL and MLlib. What this Book will help me do Gain proficiency in Spark's batch and real-time data processing with SparkSQL. Master techniques for machine learning and deep learning using SparkML and SystemML. Understand the principles of Spark's graph processing with GraphX and GraphFrames. Learn to deploy Apache Spark efficiently on platforms like Kubernetes and IBM Cloud. Optimize Spark cluster performance by configuring parameters effectively. Author(s) Romeo Kienzler is a seasoned professional in big data and machine learning technologies. With years of experience in cloud-based distributed systems, Romeo brings practical insights into leveraging Apache Spark. He combines his deep technical expertise with a clear and engaging writing style. Who is it for? This book is tailored for intermediate Apache Spark users eager to deepen their knowledge in Spark 2.x's advanced features. Ideal for data engineers and big data professionals seeking to enhance their analytics pipelines with Spark. A basic understanding of Spark and Scala is necessary. If you're aiming to optimize Spark for real-world applications, this book is crafted for you.

Book + Content Update Program SQL Server 2016 High Availability Unleashed provides start-to-finish coverage of SQL Server’s powerful high availability (HA) solutions for your traditional on-premise databases, cloud-based databases (Azure or AWS), hybrid databases (on-premise coupled with the cloud), and your emerging Big Data solutions. This complete guide introduces an easy-to-follow, formal HA methodology that has been refined over the past several years and helps you identity the right HA solution for your needs. There is also additional coverage of both disaster recovery and business continuity architectures and considerations. You are provided with step-by-step guides, examples, and sample code to help you set up, manage, and administer these highly available solutions. All examples are based on existing production deployments at major Fortune 500 companies around the globe. This book is for all intermediate-to-advanced SQL Server and Big Data professionals, but is also organized so that the first few chapters are great foundation reading for CIOs, CTOs, and even some tech-savvy CFOs. Learn a formal, high availability methodology for understanding and selecting the right HA solution for your needs Deep dive into Microsoft Cluster Services Use selective data replication topologies Explore thorough details on AlwaysOn and availability groups Learn about HA options with log shipping and database mirroring/ snapshots Get details on Microsoft Azure for Big Data and Azure SQL Explore business continuity and disaster recovery Learn about on-premise, cloud, and hybrid deployments Provide all types of database needs, including online transaction processing, data warehouse and business intelligence, and Big Data Explore the future of HA and disaster recovery In addition, this book is part of InformIT’s exciting Content Update Program, which provides content updates for major technology improvements! As significant updates are made to SQL Server, sections of this book will be updated or new sections will be added to match the updates to the technologies. As updates become available, they will be delivered to you via a free Web Edition of this book, which can be accessed with any Internet connection. To learn more, visit informit.com/cup. How to access the Web Edition: Follow the instructions inside to learn how to register your book to access the FREE Web Edition. * The companion material is not available with the online edition on O'Reilly Learning