Big Data Europe Onsite and online on 22-25 November in 2022 Learn more about the conference: https://bit.ly/3BlUk9q

Join our next Big Data Europe conference on 22-25 November in 2022 where you will be able to learn from global experts giving technical talks and hand-on workshops in the fields of Big Data, High Load, Data Science, Machine Learning and AI. This time, the conference will be held in a hybrid setting allowing you to attend workshops and listen to expert talks on-site or online.

Big Data Europe Onsite and online on 22-25 November in 2022 Learn more about the conference: https://bit.ly/3BlUk9q

Join our next Big Data Europe conference on 22-25 November in 2022 where you will be able to learn from global experts giving technical talks and hand-on workshops in the fields of Big Data, High Load, Data Science, Machine Learning and AI. This time, the conference will be held in a hybrid setting allowing you to attend workshops and listen to expert talks on-site or online.

Big Data Europe Onsite and online on 22-25 November in 2022 Learn more about the conference: https://bit.ly/3BlUk9q

Join our next Big Data Europe conference on 22-25 November in 2022 where you will be able to learn from global experts giving technical talks and hand-on workshops in the fields of Big Data, High Load, Data Science, Machine Learning and AI. This time, the conference will be held in a hybrid setting allowing you to attend workshops and listen to expert talks on-site or online.

Big Data Europe Onsite and online on 22-25 November in 2022 Learn more about the conference: https://bit.ly/3BlUk9q

Join our next Big Data Europe conference on 22-25 November in 2022 where you will be able to learn from global experts giving technical talks and hand-on workshops in the fields of Big Data, High Load, Data Science, Machine Learning and AI. This time, the conference will be held in a hybrid setting allowing you to attend workshops and listen to expert talks on-site or online.

Big Data Days Онсайт и онлайн 22-25 ноября, 2022 Узнать больше о конференции: https://bit.ly/30YNt99 Присоединяйтесь к нашей следующей конференции Big Data Days 22-25 ноября в 2022 г. Здесь вы сможете получить знания от мировых экспертов, выступающих с техническими докладами и практическими мастер-классами в области Big Data, High Load, Data Science, Machine Learning и AI. В этом году конференция будет проходить в гибридной форме, это позволит вам послушать доклады и посетить мастер-классы онсайт и онлайн.

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, IBM Expert Services Delivery, 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 Cactus Raazi is the founder and former CEO of Elefant Inc., now a part of Exos Financial, which focused on building smarter marketplaces through AI-powered pricing. Cactus led Elefant Inc. to success working with a brilliant team of engineers and marketplace experts focused on improving the pricing, transparency, and efficiency of the bond market. In more than thirty years in sales, Cactus has developed an acute sense of how price affects the commercial transaction (and how we get it wrong). He has a graduate degree in business analytics from NYU, and lives with his family in Salt Lake City, Utah.

Show Notes 5:45 – How do you make the connection and go start to Price? 9:20 – What should I be doing differently 16:25 – Topic of price 17:38  - How do you define price? 19:53 – How are prices set today? 26:27 – How do you track customers? 27:39 – Personalized pricing Cactus Raazi - LinkedIn Cactus Raazi’s book Price

Connect with the Team Producer Kate Mayne- 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, IBM Expert Services Delivery, 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 Michel Tricot. Michel is the Co-Founder of Airbyte an open source ELT standard for replicating data for applications, API and databases. Michel has been working in data engineering for 15 years, head of integration and engineering at LiveRamp, he has been involved with data ingestion and data connectors. Airbyte has raised over 5 million in seed money.  

Show Notes 3:30 – Why start a company in 2020? 5:23 – Is this company centered around ETL? 9:56 – Why is ELT more attractive than ETL? 15:09 – Give us your definition of data engineering and talk about Airbyte 20:19 – What’s the business plan around open source? 23:49 – Walk us through a use case 29:17 – Moving data can be difficult  31:09 – What makes Airbyte different? 33:31 – What is the biggest lesson you’ve learned? Slack GitHub Airbyte

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.

Get started using Apache Spark via C# or F# and the .NET for Apache Spark bindings. This book is an introduction to both Apache Spark and the .NET bindings. Readers new to Apache Spark will get up to speed quickly using Spark for data processing tasks performed against large and very large datasets. You will learn how to combine your knowledge of .NET with Apache Spark to bring massive computing power to bear by distributed processing of extremely large datasets across multiple servers. This book covers how to get a local instance of Apache Spark running on your developer machine and shows you how to create your first .NET program that uses the Microsoft .NET bindings for Apache Spark. Techniques shown in the book allow you to use Apache Spark to distribute your data processing tasks over multiple compute nodes. You will learn to process data using both batch mode and streaming mode so you can make the right choice depending on whether you are processing an existing dataset or are working against new records in micro-batches as they arrive. The goal of the book is leave you comfortable in bringing the power of Apache Spark to your favorite .NET language. What You Will Learn Install and configure Spark .NET on Windows, Linux, and macOS Write Apache Spark programs in C# and F# using the .NET bindings Access and invoke the Apache Spark APIs from .NET with the same high performance as Python, Scala, and R Encapsulate functionality in user-defined functions Transform and aggregate large datasets Execute SQL queries against files through Apache Hive Distribute processing of large datasets across multiple servers Create your own batch, streaming, and machine learning programs Who This Book Is For .NETdevelopers who want to perform big data processing without having to migrate to Python, Scala, or R; and Apache Spark developers who want to run natively on .NET and take advantage of the C# and F# ecosystems

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, IBM Expert Services Delivery, 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 Ahmed Elsamadisi. Ahmed started his career at Cornell’s Autonomous Systems Laboratory focusing on human-robot interaction and Bayesian data fusion as well as building algorithms for autonomous cars. He then joined Raytheon to develop tactical AI algorithms for missile defense, four of which are still in use today by the US Military. Eventually he moved on to Raytheon’s Advanced Technology division to focus on building human exoskeletons--like the Iron Man suit but made of rubber because it’s way more energy efficient and not a fictional concept ignoring proper scientific practices-- and algorithms for adaptive decision making. In 2015 Ahmed joined We Work, and over the next two years Ahmed built We Work’s standard data infrastructure and grew its data team from one to forty Data Engineers and Data Analysts. After implementing a single time series table data model at We Work and seeing the immediate results, Ahmed wanted to figure out a way to bring this new found knowledge to the world. Ahmed founded Narrator to allow startups to leverage this new approach, ask questions, understand customer behavior, and analyze data across all their systems from a simple Universal Data Model.  Show Notes 3:26 – Tell us about algorithms for autonomous cars 6:26 – Anything you can say around missile defense? 8:58 – Tell us about human exoskeletons 13:18 – What kind of data were you using to make decisions around the Iron Man suit? 16:02 – What did you learn at We Work? 25:00 – How we answer a question in the world of Narrator 32:24 – Does Narrator sit between the application and the database? 33:28 – Walk us through a Use Case Website: Narrator AI.com Books:  The Power of Bad Never Split The Difference Ahmed Elsamadisi - LinkedIn    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 Dr. Kayla Lee Growth Product Manager, Community Partnerships at IBM Quantum & Qiskit. Dr. Kayla Lee works with innovation teams across industries to understand how they can using new and emerging technologies to solve their business challenges. In her role, she serves as a bridge between business and science to help drive value for enterprise clients. Her primary focus is the new model of computation, quantum computing, working with clients to understand potential applications, prioritize use cases, and build a business strategy to prepare for the future of computing.

Al and Dr. Lee try and help us understand Quantum Computing as a new technology.   

Show Notes 3:03 - Dr. Lee talks about her day to day job 4:40 – The challenge  6:12 - Dr. Lee describes quantum  8:03 – What is quantum computing going to do for us that we can’t do today? 9:30 – How does this work? 17:50 – What kind of problem is quantum computing suited to answer? 19:40 – Will quantum computing replace traditional computing? 23:36 – Who can use quantum computing? 32:30 – Security and quantum 33:50 – Dr. Lee’s team Dr. Kayla Lee - LinkedIn Ten More Universities Join The IBM-HBCU Quantum Center IBM Quantum Computing  Qiskit HBCU Center Driving Diversity and Inclusion in Quantum Computing IBM’s Roadmap For Scaling Quantum Technology

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, IBM Expert Services Delivery, 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 Robin Hernandez, Robin is the VP of Offering Management Cloud Data for Watson AI Ops. Robin started out in software development, and then worked in Technical Sales, IBM Cloud Garage, and then Product Management.

Show Notes 3:46 – What is AI Ops? 6:31 – What is the ROI? 12:00 – What does it take to setup AI? 17:48 – How does this really work? 21:34 – I am in Services what do I get? 26:06 – What king of grantees does AI offer? 28:12 – Who is monitoring AI? IBM AI Ops    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, IBM Expert Services Delivery, Making Data Simple provides the latest thinking on big data, A.I., and the implications for the enterprise from a range of experts.

Interested in learning what it takes to operate a start-up? On this episode of Making Data Simple, host Al Martin sits down with Simon Lightstone, IBM offering manager, to discuss what it took to get his startup off the ground. Simon offers tips to those facing a similar experience and describes how the decision to pursue a dream ultimately affected his career.

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, IBM Expert Services Delivery, 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 Ana Echeverri. Ana leads Expert Labs Learning, experience in sales, client success, owned her own business. Has a computer engineering degree from Columbia, formerly worked at Informix, and has been in the technology industry for about 30 years, also worked at Microsoft Citrix, and then started her own business focused on Education.

Show Notes 8:25 – Are there different industry facts driving learning? 11:58 – How do you find the time to learn? 17:24 – What the best way to get education? 20:06 - Do we learn differently? 22:49 – We want expert’s what are you going to do? 28:40 – What is IBM doing around learning? 33:08 – Biggest misconception in learning? Adam Grant Power of Learning Conversational Intelligence  Cooking Blog (Recetas de Merci)

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, IBM Expert Services Delivery, 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 Rob Thomas. Rob is Senior VP of IBM Cloud and Data Platform, a Coach and has a Mentor newsletter, an author, and a Blogger. Rob has been at IBM his whole career, started in consulting moved to microelectronics then moved to software in 2006.

Show Notes 3:26 – What are your learning's from 2020? 7:42 – What’s your vision and objectives for Cloud and Data platform?  11:44 – Discuss the rules of your organization 14:08 - What’s your view on hybrid cloud? 18:30 – What does IBM Cloud and data platform do that nobody else can do? 21:51 – What should companies be looking at to build their competitiveness? 28:18 – What was your reason for writing about “Just Show Up”? The Mentor Newsletter It Takes What It Takes    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.

Ambyr Amen-Ra joins Data Brunch to talk about data that covers decades worth of international travel and performances by legendary dancer, choreographer, and activist Katherine Dunham. Ambyr shares stories of the data's journey to ICPSR, as well as her own personal connection to Dunham and the communities she built.

Links from this episode:

Dunham’s Data: Katherine Dunham and Digital Methods for Dance Historical Inquiry: https://www.dunhamsdata.org/

Dunham's Data: Katherine Dunham and Digital Methods for Dance Historical Inquiry, Everyday Itinerary, 1950-1953: https://doi.org/10.3886/ICPSR37698 (ICPSR 37698)

Dunham’s Data webinar recording: Digital Methods for Dance History: Finding Arts and Culture Data in Unexpected Places: https://youtu.be/gJaICwWtIy4

ICPSR jobs: https://myumi.ch/7ZxmB

Joining the Data Revolution: Big Data in Education and Social Science Research (applications due March 22) https://myumi.ch/BoQmo

Rewind: Love Data Week 2021: https://cms.icpsr.umich.edu/love-data-week-2021-international-events

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, IBM Expert Services Delivery, 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 Jeff Richardson. Jeff has a history of database data, information management, and he is now the Chief Information Officer at Accelerated Enrollment Solutions. Jeff was also at Bentley Systems for 17 ½ years as Chief Data Officer.

Show Notes 5:41 – What does it mean to be a technology nerd? 6:53 – What technologies as a CDO or CIO are you addressing on a regular bases? 13:04 – How are you going to tackle the culture and the politics? 17:25 – Is it Cloud or Hybrid to drive the new data lake? 24:03 – What is your plan to get to desired state? 27:04 – Does AI have a role in your new position? 31:44 – Fighting the Infodemic what made you write this article?  Fighting the Infodemic Jeff’s podcast list Analytics on Fire Dissecting popular IT Nerds The Data Chief Data Crunch 

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, IBM Expert Services Delivery, 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 Yancey Strickler. Yancey is a writer and entrepreneur, founder of the Bento Society, Co-Founder of Kick Starter, a Distinguished Fellow at the Drucker Institute, Author of This Could Be Our Future: A Manifesto for a More, Generous World and The Idea Space, Co-Founded the Artist Resource The Creative Independent, the Record label eMusic Selects, and Angel Investor.

Show Notes 3:43 - Yancey’s Brand 8:39 - How in Kick Started did you define success? 13:06 – Creating the Bento Society 21:00 – Reframing values into the new world 23:48 – Tips and tricks 27:48 – Data as fire 30:48 – What the next 5 – 10 years going to look like

This Could Be Our Future: A Manifesto for a More, Generous World YStrickler.com Bentoism.org The ideaspace    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, IBM Expert Services Delivery, 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 Kristen Summers and John Thomas. Kristen is a Distinguished Engineer in Cloud and Cognitive Expert Labs. Kristen has worked in Artificial Intelligence and Data Science, PHD in Computer Science, and leads Data Science within our Expert Labs. John is a Distinguished Engineer in Data and Expert Labs, John leads Services that helps clients establish the AI factory.

Show Notes 3:24 – What is the AI academy and how does it all fit together? 4:34 – AI Ladder and AI Maturity 8:32 – How does the AI Factory make it easier to accomplish the AI Ladder? 12:00 – Why does your team do it better? 17:03 – How do you know your data is ready? 21:22 – What is the most practical use case? 23:02 – What does it really mean to infuse AI? 25:15 – Definition of AI maturity curve 28:25 – How do you know it’s trustworthy? 29:14 – What the most important lesson you’ve learned with AI and what is AI not very good at? In the Dream House  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, IBM Expert Services Delivery, 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 Suj Perepa and Richard Darden. Suj is a distinguished engineer and specializes AI, machine learning technology in the financial sector.  Suj also has been a lead for security programs and a member of the IBM Academy of Technology leadership team. Richard is a distinguished engineer in digital human evangelism for North America government and a distinguished engineer at IBM in Cloud and Cognitive for the public sector and a former chief architect on federal government agencies.  

Show Notes 6:30 – What is a data framework? 9:16 – What is framework? 11:00 – Governance and people 14:15 – Process and architecture 19:15 – Bringing it all into a playbook   22:56 – Who is the client? 24:36 – How does bias play into it? 27:02 – What products are you using? 27:54 – Explainability 30:44 – Ethics of AI 37:13 Suj and Richard’s most important lessons in AI The Discipline of Technology    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.

Learn from state-of-the-art examples in robotics, motors, detection filters, chemical processes, aircraft, and spacecraft. With this book you will review contemporary MATLAB coding including the latest MATLAB language features and use MATLAB as a software development environment including code organization, GUI development, and algorithm design and testing. Features now covered include the new graph and digraph classes for charts and networks; interactive documents that combine text, code, and output; a new development environment for building apps; locally defined functions in scripts; automatic expansion of dimensions; tall arrays for big data; the new string type; new functions to encode/decode JSON; handling non-English languages; the new class architecture; the Mocking framework; an engine API for Java; the cloud-based MATLAB desktop; the memoize function; and heatmap charts. MATLAB Recipes: A Problem-Solution Approach, Second Edition provides practical, hands-on code snippets and guidance for using MATLAB to build a body of code you can turn to time and again for solving technical problems in your work. Develop algorithms, test them, visualize the results, and pass the code along to others to create a functional code base for your firm. What You Will Learn Get up to date with the latest MATLAB up to and including MATLAB 2020b Code in MATLAB Write applications in MATLAB Build your own toolbox of MATLAB code to increase your efficiency and effectiveness Who This Book Is For Engineers, data scientists, and students wanting a book rich in examples using MATLAB.