The fun and friendly guide to mastering IBM’s Statistical Package for the Social Sciences Written by an author team with a combined 55 years of experience using SPSS, this updated guide takes the guesswork out of the subject and helps you get the most out of using the leader in predictive analysis. Covering the latest release and updates to SPSS 27.0, and including more than 150 pages of basic statistical theory, it helps you understand the mechanics behind the calculations, perform predictive analysis, produce informative graphs, and more. You’ll even dabble in programming as you expand SPSS functionality to suit your specific needs. Master the fundamental mechanics of SPSS Learn how to get data into and out of the program Graph and analyze your data more accurately and efficiently Program SPSS with Command Syntax Get ready to start handling data like a pro—with step-by-step instruction and expert advice!

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Abstract Hosted by Al Martin, VP, Data and AI Expert Services and Learning at IBM, Making Data Simple provides the latest thinking on big data, A.I., and the implications for the enterprise from a range of experts.

This week on Making Data Simple, we have Wennie Allen Business Director, Data Science and AI Elite Team and Carlo Appugliese Program Director – Data &AI, Data Science Elite Team. This week we talk about agile AI and remote data science. Carlo discusses his book, while Wennie talks about the secret sauce.

Show Notes 2:56 – How do we get people to adopt AI? 4:49 – Carlo’s book 6:15 – Why do we call it agile AI? 11:12 – Six weeks to get it done! 15:07 – Where are we at with AI? 16:54 - Problems with AI today 22:05 – Secret sauce 26:31 - Process and methodology  30:22 – Talk data 34:19 – Integration, trust, and quick deployment 36:10 – Working remote 39:40 – How do you engage? Remote Data Science Website: http://ibm.biz/RemoteDataScience Agile AI Blog: http://ibm.biz/DSE-AgileAI-Blog Agile AI Book:   http://ibm.biz/DSE-AgileAI Community: http://ibm.biz/DSE-Community Chat with the Lab: http://ibm.biz/DSE-ChatWithTheLab Consultation: http://ibm.biz/DSE-Consultation Blogs:  Virtual Data Science can rise to the challenge in unprecedented times by Wennie Allen Data Science and AI from anywhere... by Carlo Appugliese Wennie on LinkedIn linkedin.com/in/wennie-allen Carlo on LinkedIn linkedin.com/in/carloappugliese    Connect with the Team Producer Kate Brown - LinkedIn. Producer Steve Templeton - LinkedIn. Host Al Martin - LinkedIn and Twitter.  Want to be featured as a guest on Making Data Simple? Reach out to us at [email protected] and tell us why you should be next. The Making Data Simple Podcast is hosted by Al Martin, WW VP Technical Sales, IBM, where we explore trending technologies, business innovation, and leadership ... while keeping it simple & fun.

Send us a text Want to be featured as a guest on Making Data Simple? Reach out to us at [[email protected]] and tell us why you should be next.

Abstract Hosted by Al Martin, VP, Data and AI Expert Services and Learning at IBM, Making Data Simple provides the latest thinking on big data, A.I., and the implications for the enterprise from a range of experts.

This week on Making Data Simple, we have Scott Taylor. Scott is the Data Whisperer, a thought leader, consultant on the strategic value of data management, Principal Consultant of MetaMeta Consulting and he practices data evangelism as a service. Scott discusses helping people understand the value and strategic importance of simple data.

Show Notes 1:25 – Scott’s back ground 4:30 – Does Scott talk to data? 5:20 – How long has Scott been in data? 6:50 - Data Management 13:12 - Data Story telling 17:05 – Structured data 25:08 - Core manifesto  25:48 – Bad data ideas Connect with Scott Taylor Scott Taylor - LinkedIn Scott Taylor - Twitter Scott Taylor – The Data Whisperer YouTube channel    Connect with the Team Producer Kate Brown - LinkedIn. Producer Steve Templeton - LinkedIn. Host Al Martin - LinkedIn and Twitter.  Want to be featured as a guest on Making Data Simple? Reach out to us at [email protected] and tell us why you should be next. The Making Data Simple Podcast is hosted by Al Martin, WW VP Technical Sales, IBM, where we explore trending technologies, business innovation, and leadership ... while keeping it simple & fun.

Send us a text Adam Weinstein is currently CEO and Co-Founder of Cursor, having worked at LinkedIn as a Senior Manager of Business Development and having founded enGreet, a print-on-demand greeting card company that merged crowd-sourcing with social expressions. In this episode, he describes his data analytics company and provides insight into creating a successful startup.

Shownotes

00:00 - Check us out on YouTube and SoundCloud!   

00:10 - Connect with Producer Steve Moore on LinkedIn & Twitter   

00:15 - Connect with Producer Liam Seston on LinkedIn & Twitter.   

00:20 - Connect with Producer Rachit Sharma on LinkedIn.

00:25 - Connect with Host Al Martin on LinkedIn & Twitter.   

00:55 - Connect with Adam Weinstein on LinkedIn.

03:55 - Find out more about Cursor.

06:45 - Learn more about Cursor's Co-Founder and CEO Adam Weinstein.

13:10 - Learn more about Big Data Analytics.

19:20 - What is Python/Jupyter Notebooks?

26:35 - Learn more about Data Fluency.

35:30 - What is a startup?  Want to be featured as a guest on Making Data Simple? Reach out to us at [email protected] and tell us why you should be next. The Making Data Simple Podcast is hosted by Al Martin, WW VP Technical Sales, IBM, where we explore trending technologies, business innovation, and leadership ... while keeping it simple & fun.

Send us a text Want to be featured as a guest on Making Data Simple? Reach out to us at [[email protected]] and tell us why you should be next.

Abstract Hosted by Al Martin, VP, Data and AI Expert Services and Learning at IBM, Making Data Simple provides the latest thinking on big data, A.I., and the implications for the enterprise from a range of experts.

This week on Making Data Simple, we have Ritika Gunnar. Ritika is currently VP, Data and AI Expert Labs Services and Learning and has worked with IBM in various roles within development, support and technical sales. She started her career developing and supporting systems management warehousing and reporting solutions. She worked in various development projects across IBMs brands to create appliances and solutions for clients cloud and virtualization needs. Ritika also managed Tivoli’s world-wide technical sales teams driving solution selling within the portfolio and increasing overall revenue and client satisfaction for the brand.

Show Notes 2:41 – Ritika discusses her background 6:07 – Ritika’s current role 9:09 – Successes of Data and AI 15:21 - Important things to company’s around AI 21:39 – What do you see as great principals of a service business  25:56 – Ritika’s proudest moment at IBM 29:20 – How much time do you spend working with clients? Ritika Gunnar – LinkedIn and Twitter    Connect with the Team Producer Kate Brown - LinkedIn. Producer Steve Templeton - LinkedIn. Host Al Martin - LinkedIn and Twitter.  Want to be featured as a guest on Making Data Simple? Reach out to us at [email protected] and tell us why you should be next. The Making Data Simple Podcast is hosted by Al Martin, WW VP Technical Sales, IBM, where we explore trending technologies, business innovation, and leadership ... while keeping it simple & fun.

Send us a text Want to be featured as a guest on Making Data Simple? Reach out to us at [[email protected]] and tell us why you should be next.

Abstract Hosted by Al Martin, VP, Data and AI Expert Services and Learning at IBM, Making Data Simple provides the latest thinking on big data, A.I., and the implications for the enterprise from a range of experts. This week on Making Data Simple, we have Debbie Berebichez she is the first Mexican woman to graduate from Stanford University with a PhD in Physics, and she uses her education and background to make science approachable to a wide range of audiences. Debbie co-hosts numerous TV shows, where she uses her knowledge of physics to explain the science behind extraordinary engineering feats. Deborah is the Chief Data Scientist at Metis where she leads the creation and growth of exceptional data science training opportunities. Deborah completed two postdoctoral fellowships at Columbia University's Applied Math and Physics Department and at NYU's Courant Institute for Mathematical Sciences where she carried out research in the area of acoustic waves. She invented a highly effective technique in the field of wireless communications whereby a cell phone user can communicate with a desired target user in a location far away.  Show Notes 2:10 – Debbie’s mission statement 8:58 – Mentorship 11:25 - Debbie talks about Discovery TV shows 15:04 – Debbie discusses her Ted Talk 19:20 - Data literacy discussion 30:35 – Physicist to data science  33:22 – Training and data scientist  38:43 - What makes the perfect data science implementation in a company? 41:53 – Debbie’s advice for young girls Debbie Berebichez - Instagram Debbie Berebichez - Twitter Debbie Berebichez - LinkedIn Debbie Berebichez - Facebook Statistic and the art of deception  Connect with the Team Producer Kate Brown - LinkedIn. Producer Steve Templeton - LinkedIn. Host Al Martin - LinkedIn and Twitter.  Want to be featured as a guest on Making Data Simple? Reach out to us at [email protected] and tell us why you should be next. The Making Data Simple Podcast is hosted by Al Martin, WW VP Technical Sales, IBM, where we explore trending technologies, business innovation, and leadership ... while keeping it simple & fun.

This IBM® Redbooks® publication helps you install, configure, and maintain the IBM z15™ (machine types 8561 and 8562) systems. The z15 systems offers new functions that require a comprehensive understanding of the available configuration options. This book presents configuration setup scenarios, and describes implementation examples in detail. This publication is intended for systems engineers, hardware planners, and anyone who needs to understand IBM Z® configuration and implementation. Readers should be familiar with IBM Z technology and terminology. For more information about the functions of the z15 systems, see IBM z15 Technical Introduction, SG24-8850, IBM z15 (8561) Technical Guide, SG24-8851 and IBM z15 (8562) Technical Guide, SG24-8852.

IBM® Spectrum Archive Enterprise Edition for the IBM TS4500, IBM TS3500, IBM TS4300, and IBM TS3310 tape libraries provides seamless integration of IBM Linear Tape File System (LTFS) with IBM Spectrum® Scale by creating an LTFS tape tier. You can run any application that is designed for disk files on tape by using IBM Spectrum Archive. IBM Spectrum Archive can play an important role in reducing the cost of storage for data that does not need the access performance of primary disk. The IBM Spectrum Archive Virtual Appliance can be deployed in minutes and key features can be tried along with this user guide. The virtual machine (VM) has a pre-configured IBM Spectrum Scale and a virtual tape library that allows to quickly test the IBM Spectrum Archive features without connecting to a physical tape library. The virtual appliance is provided as a VirtualBox .ova file.

The purpose of this document is to show how to install RedHat OpenShift Container Platform (OCP) on Amazon web services (AWS) public cloud with OpenShift installer, a method that is known as Installer-provisioned infrastructure (IPI). We also describe how to validate the installation of IBM container storage interface (CSI) driver on OCP 4.2 that is installed on AWS. This document also describes the installation of OCP 4.x on AWS with customization and OCP 4.x installation on IBM cloud. This document discusses how to provision internet small computer system interface (iSCSI) storage that is made available by IBM Spectrum® Virtualize for Public Cloud (SVPC) that is deployed on AWS. Finally, the document discusses the use of Red Hat OpenShift command line interface (CLI), OCP web console graphical user interface (GUI), and AWS console.

Send us a text Want to be featured as a guest on Making Data Simple? Reach out to us at [[email protected]] and tell us why you should be next.

Abstract Hosted by Al Martin, VP, Data and AI Expert Services and Learning at IBM, Making Data Simple provides the latest thinking on big data, A.I., and the implications for the enterprise from a range of experts. This week on Making Data Simple, we have Ayal Steinberg, Global Sales VP, Data and AI at IBM. Ayal Steinberg is the Vice President of Global Sales for IBM's Data and AI business unit.  In his capacity Ayal oversees IBM's largest and one of the most strategic business units with over 1,500 people and several billion dollars of annual revenue.  Ayal has proven success in managing complex and global sales organizations. Throughout his career, Ayal has created and led high-performing sales teams focused on selling complex software solutions to some of the world’s most well-known brands in more then 50 countries. Prior to IBM, Ayal successfully led sales teams through transformation and hyper growth at IBM Netezza, Oracle, Datastax (the open source provider of Apache Cassandra), and other enterprise software companies.  Earlier in his career, Ayal was a pioneer in selling software for several start-ups in price optimization and advanced analytics. Ayal majored in Economics from Binghamton University, State University of New York.

Show Notes 4:00 – Ayal’s back ground 15:33 – IBM strategy  18:45 – Moving to cloud 21:23 – Why IBM 23:24 - Value Selling 27:58 – Value vs. price 29:57 - Skills set 31:20 – How do you bring someone back around Solution Selling Challenger Sale Strengths Finder 2.0 Connect with the Team Producer Kate Brown - LinkedIn. Producer Steve Templeton - LinkedIn. Host Al Martin - LinkedIn and Twitter.    Want to be featured as a guest on Making Data Simple? Reach out to us at [email protected] and tell us why you should be next. The Making Data Simple Podcast is hosted by Al Martin, WW VP Technical Sales, IBM, where we explore trending technologies, business innovation, and leadership ... while keeping it simple & fun.

Send us a text Want to be featured as a guest on Making Data Simple? Reach out to us at [[email protected]] and tell us why you should be next.

Abstract Hosted by Al Martin, VP, Data and AI Expert Services and Learning at IBM, Making Data Simple provides the latest thinking on big data, A.I., and the implications for the enterprise from a range of experts. This week on Making Data Simple, we have Nick Caldwell. Nick is the Chief Product Officer at Looker now Google, with careers at Reddit as VP of Engineering, and various positions at Microsoft. Nick holds a degree in computer science and electrical engineering from MIT and an MBA from UC Berkeley. He’s a native of P.G. County, Maryland but is happy to call San Francisco home. Show Notes 6:07 - Nick’s background 9:10 – Nick discusses leadership 16:45 - Building trust with product team 18:55 – Great leaders 21:05 – Water fall 24:25 – Discussion on data 25:38 – Nick explains Looker

Nick Caldwell - Twitter Nick Caldwell - Medium Nick Caldwell - LinkedIn ColorCode  https://www.youtube.com/watch?v=n8WwwWLdgTQ https://www.youtube.com/watch?v=lfxW4hC9a0U Blue Flame Devcolor.org Nick Caldwell

Connect with the Team Producer Kate Brown - LinkedIn. Producer Steve Templeton - LinkedIn. Host Al Martin - LinkedIn and Twitter.    Want to be featured as a guest on Making Data Simple? Reach out to us at [email protected] and tell us why you should be next. The Making Data Simple Podcast is hosted by Al Martin, WW VP Technical Sales, IBM, where we explore trending technologies, business innovation, and leadership ... while keeping it simple & fun.

This IBM® Redpaper™ publication is intended as an architecture and configuration guide to set up the IBM System Storage™ for the SAP HANA tailored data center integration (SAP HANA TDI) within a storage area network (SAN) environment. SAP HANA TDI allows the SAP customer to attach external storage to the SAP HANA server. The paper also describes the setup and configuration of SAP Landscape Management for SAP HANA systems on IBM infrastructure components: IBM Power Systems and IBM Storage based on IBM Spectrum® Virtualize. This document is written for IT technical specialists and architects with advanced skill levels on SUSE Linux Enterprise Server or Red Hat Enterprise Linux (RHEL) and IBM System Storage. This document provides the necessary information to select, verify, and connect IBM System Storage to the SAP HANA server through a Fibre Channel-based SAN. The recommendations in this Blueprint apply to single-node and scale-out configurations, and Intel and IBM Power based SAP HANA systems.

This IBM® Blueprint is intended to facilitate the deployment of IBM Storage for Red Hat OpenShift Container Platform by using detailed hardware specifications to build a system. It describes the associated parameters for configuring persistent storage within a Red Hat OpenShift Container Platform environment. To complete the tasks, you should understand Red Hat OpenShift, IBM Storage, the IBM block storage Container Storage Interface (CSI) driver and the IBM Spectrum Scale CSI driver. The information in this document is distributed on an "as is" basis without any warranty that is either expressed or implied. Support assistance for the use of this material is limited to situations where IBM Storwize® or IBM FlashSystem® storage devices, ESS and Spectrum Scale are supported and entitled, and where the issues are not specific to a blueprint implementation. IBM Storage Suite for IBM Cloud® Paks is an offering bundle that includes software-defined storage from both IBM and Red Hat. Use this document for details on how to deploy IBM Storage product licenses obtained through Storage Suite for Cloud Paks (IBM Spectrum® Virtualize and IBM Spectrum Scale).

Send us a text Want to be featured as a guest on Making Data Simple? Reach out to us at [[email protected]] and tell us why you should be next.

Abstract Hosted by Al Martin, VP, Data and AI Expert Services and Learning at IBM, Making Data Simple provides the latest thinking on big data, A.I., and the implications for the enterprise from a range of experts.

This week on Making Data Simple, we have Hadley Wickham is Chief Scientist at RStudio, and an Adjunct Professor of Statistics at the University of Auckland, Stanford University, and Rice University. He builds tools that make data science easier and faster, including the famous tidy verse packages for the R programming language. He was named a Fellow by the American Statistical Association for "pivotal contributions to statistical practice through innovative and pioneering research in statistical graphics and computing".

Show Notes 2:39 – Hadley talks about his journey  5:22 – Hadley talks about his American Statistical Association for "pivotal contributions to statistical practice" 8:00 – Tidy data concept 9:02 - How Hadley became interested in big data and R 10:12 – Python and R 12:30 – What Hadley is doing now 13:47 – Top 3 packages that help data scientists  17:47 – Hadley discusses his book  22:48 – Writing a book vs. code 29:40 – What language is going to take over 31:01 – What’s next for data 31:54 – What’s cool for Hadley 36:26 – Hadley’s Role model Hadley Wickham’s books Ggplot2 R for Data Science Advanced R R Packages Hadl Want to be featured as a guest on Making Data Simple? Reach out to us at [email protected] and tell us why you should be next. The Making Data Simple Podcast is hosted by Al Martin, WW VP Technical Sales, IBM, where we explore trending technologies, business innovation, and leadership ... while keeping it simple & fun.

Send us a text Want to be featured as a guest on Making Data Simple? Reach out to us at [[email protected]] and tell us why you should be next.

Abstract Hosted by Al Martin, VP, Data and AI Expert Services and Learning at IBM, Making Data Simple provides the latest thinking on big data, A.I., and the implications for the enterprise from a range of experts. This week on Making Data Simple, we have Ross Mauri General Manager, IBM Z & LinuxONE IBM Systems. Ross has expertise in strategy, technology, engineering, marketing, and sales. This week we discuss his career at IBM, the people and CEOs of IBM, Mainframes, Databases, Cloud, and Datastores, the myth of Z, and IBM's Z15.

Show Notes 3:43 - Ross Mauri's career 8:22 – People of IBM and CEOs 12:11 – Working with CEOs 14:34 – Ross talks legacy  17:20 – What does the mainframe do that no one else can? 18:28 – Z myth 21:22 – LinuxONE 24:29 – RedHat 25:15 – What does Z not do well? 26:00 – Z15 Ross Mauri - LinkedIn Connect with the Team Producer Kate Brown - LinkedIn. Producer Meighann Helene - LinkedIn. Producer Michael Sestak - LinkedIn. Producer Steve Templeton - LinkedIn. Host Al Martin - LinkedIn and Twitter.    Want to be featured as a guest on Making Data Simple? Reach out to us at [email protected] and tell us why you should be next. The Making Data Simple Podcast is hosted by Al Martin, WW VP Technical Sales, IBM, where we explore trending technologies, business innovation, and leadership ... while keeping it simple & fun.

Send us a text Want to be featured as a guest on Making Data Simple? Reach out to us at [[email protected]] and tell us why you should be next.

Abstract Hosted by Al Martin, VP, Data and AI Expert Services and Learning at IBM, Making Data Simple provides the latest thinking on big data, A.I., and the implications for the enterprise from a range of experts. This week on Making Data Simple, we have Jim Ruston Managing Director of Armeta Analytics. Al and Jim discuss monetizing data, prescriptive and descriptive approaches, and sealing the deal. Show Notes 4:45 - How do you monetize data 6:20 - Common actions 8:50 - Prescriptive approach 11:15 – Gap in data warehouse 13:05 – Cleanup  17:40 – Overhead costs 19:22 - Prescriptive and descriptive approach 20:56 – Preferred technology 23:07 - Who are the decision makers   24:56 – Sealing the deal 27:10 – Why do I need Armeta Armeta  Armeta Linkedin Guaranteed Analytics  The Challenger Sale Connect with the Team Producer Kate Brown - LinkedIn. Producer Meighann Helene - LinkedIn. Producer Michael Sestak - LinkedIn. Producer Steve Templeton - LinkedIn. Host Al Martin - LinkedIn and Twitter.  Want to be featured as a guest on Making Data Simple? Reach out to us at [email protected] and tell us why you should be next. The Making Data Simple Podcast is hosted by Al Martin, WW VP Technical Sales, IBM, where we explore trending technologies, business innovation, and leadership ... while keeping it simple & fun.

Send us a text Want to be featured as a guest on Making Data Simple? Reach out to us at [[email protected]] and tell us why you should be next.

Abstract Hosted by Al Martin, VP, Data and AI Expert Services and Learning at IBM, Making Data Simple provides the latest thinking on big data, A.I., and the implications for the enterprise from a range of experts. This week on Making Data Simple, we have Peter Wang Co Founder and CEO of Anaconda and Shadi Copty VP of Offering Manager. Al, Peter, and Shadi discuss Data Science and IBMs partnership with Anaconda. Show Notes 6:11 - Corporate Mission 8:00 - Use Case 9:20 - IBM and Anaconda partnership 14:04 - Cloud Pak for Data what is it? 15:43 – Python vs R 17:15 – Anaconda’s Future 23:25 – Shadi takes over from Al 25:05 – Data Science Community 33:40 – Centre of Humane Technology   Anaconda - https://www.linkedin.com/company/anacondainc/

Connect with the Team Producer Kate Brown - LinkedIn. Producer Meighann Helene - LinkedIn. Producer Michael Sestak - LinkedIn. Producer Steve Templeton - LinkedIn. Host Al Martin - LinkedIn and Twitter.  Want to be featured as a guest on Making Data Simple? Reach out to us at [email protected] and tell us why you should be next. The Making Data Simple Podcast is hosted by Al Martin, WW VP Technical Sales, IBM, where we explore trending technologies, business innovation, and leadership ... while keeping it simple & fun.

Send us a text Want to be featured as a guest on Making Data Simple? Reach out to us at [[email protected]] and tell us why you should be next.

Abstract Hosted by Al Martin, VP, Data and AI Expert Services and Learning at IBM, Making Data Simple provides the latest thinking on big data, A.I., and the implications for the enterprise from a range of experts. This week on Making Data Simple, we have Andy Youniss President and CEO of Rocket Software, co-founded in 1990 with products across the Ladder to AI, Hybrid Cloud and businesses in Technology partnerships. This week we discuss Covid and its personal and professional affects on business.   Show Notes 3:00 - Rockets core values  7:17 – Life and times  10:25 – Portfolio 11:26 - Vision  15:07 - Legacy tagline 20:26 - Rockets responds to Covid 27:17 – Secure file transfer business 28:53 – Where did the name Rocket come from? 30:05 – What does leadership mean to you? IBM Assistance - https://www.ibm.com/watson/covid-response Rocket Software - https://www.rocketsoftware.com/ Linkedin - https://www.linkedin.com/company/rocket-software Twitter - https://twitter.com/rocket Facebook - https://www.facebook.com/RocketSoftwareInc Brene Brown - https://brenebrown.com/ Arvind Krishna - https://www.linkedin.com/in/arvindkrishna/ Spillover – https://www.amazon.com/Spillover-Animal-Infections-Human-Pandemic/dp/0393066800#reader_0393066800 Bruce Springsteen - https://www.goodreads.com/book/show/29072594-born-to-run Connect with the Team Producer Kate Brown - LinkedIn. Producer Meighann Helene - LinkedIn. Producer Michael Sestak - LinkedIn. Producer Steve Templeton - LinkedIn. Host Al Martin - LinkedIn and Twitter.    Want to be featured as a guest on Making Data Simple? Reach out to us at [email protected] and tell us why you should be next. The Making Data Simple Podcast is hosted by Al Martin, WW VP Technical Sales, IBM, where we explore trending technologies, business innovation, and leadership ... while keeping it simple & fun.

Send us a text Want to be featured as a guest on Making Data Simple? Reach out to us at [[email protected]] and tell us why you should be next.

Abstract Hosted by Al Martin, VP, Data and AI Expert Services and Learning at IBM, Making Data Simple provides the latest thinking on big data, A.I., and the implications for the enterprise from a range of experts. This week on Making Data Simple, we have Rishal Hurbans author of Grokking AI Algorithms, Solution Architect at Intellect, and founder at Prolific Idea in 2015. Al and Rishal talk about Rishal’s book Grokking AI Algorithms and its effect on ants and understanding algorithms.  Show Notes 4:04 – Bio Rhythmic Using Ants  8:04 – Knapsack Problem vs Algorithms 9:02 – Mother and Father DNA 10:29 – Silver Bullet 12:42 – Real World Examples Algorithms 17:20 – Genetic Algorithms 28:30 – Rishal’s Best Podcasts ·       Ted Radio Hour - https://www.npr.org/programs/ted-radio-hour/ ·       Hidden Brian - https://www.npr.org/series/423302056/hidden-brain ·       Masters of Scale - https://mastersofscale.com/ ·       Tim Irvine Blog Wait But Why - https://waitbutwhy.com/ Connect with Rishal Hurbans Rishal Hurbans - https://rhurbans.com/ Grokking AI Algorithms - https://www.manning.com/

Connect with the Team Producer Kate Brown - LinkedIn. Producer Meighann Helene - LinkedIn. Producer Michael Sestak - LinkedIn. Producer Steve Templeton - LinkedIn. Host Al Martin - LinkedIn and Twitter.  Want to be featured as a guest on Making Data Simple? Reach out to us at [email protected] and tell us why you should be next. The Making Data Simple Podcast is hosted by Al Martin, WW VP Technical Sales, IBM, where we explore trending technologies, business innovation, and leadership ... while keeping it simple & fun.

The Spark distributed data processing platform provides an easy-to-implement tool for ingesting, streaming, and processing data from any source. In Spark in Action, Second Edition, you’ll learn to take advantage of Spark’s core features and incredible processing speed, with applications including real-time computation, delayed evaluation, and machine learning. Spark skills are a hot commodity in enterprises worldwide, and with Spark’s powerful and flexible Java APIs, you can reap all the benefits without first learning Scala or Hadoop. About the Technology Analyzing enterprise data starts by reading, filtering, and merging files and streams from many sources. The Spark data processing engine handles this varied volume like a champ, delivering speeds 100 times faster than Hadoop systems. Thanks to SQL support, an intuitive interface, and a straightforward multilanguage API, you can use Spark without learning a complex new ecosystem. About the Book Spark in Action, Second Edition, teaches you to create end-to-end analytics applications. In this entirely new book, you’ll learn from interesting Java-based examples, including a complete data pipeline for processing NASA satellite data. And you’ll discover Java, Python, and Scala code samples hosted on GitHub that you can explore and adapt, plus appendixes that give you a cheat sheet for installing tools and understanding Spark-specific terms. What's Inside Writing Spark applications in Java Spark application architecture Ingestion through files, databases, streaming, and Elasticsearch Querying distributed datasets with Spark SQL About the Reader This book does not assume previous experience with Spark, Scala, or Hadoop. About the Author Jean-Georges Perrin is an experienced data and software architect. He is France’s first IBM Champion and has been honored for 12 consecutive years. Quotes This book reveals the tools and secrets you need to drive innovation in your company or community. - Rob Thomas, IBM An indispensable, well-paced, and in-depth guide. A must-have for anyone into big data and real-time stream processing. - Anupam Sengupta, GuardHat Inc. This book will help spark a love affair with distributed processing. - Conor Redmond, InComm Product Control Currently the best book on the subject! - Markus Breuer, Materna IPS