{"id":133808,"date":"2022-08-02T14:41:13","date_gmt":"2022-08-02T13:41:13","guid":{"rendered":"https:\/\/news.sap.com\/uk\/?p=133808"},"modified":"2023-09-27T15:10:43","modified_gmt":"2023-09-27T14:10:43","slug":"sap-lets-talk-data-podcast-series","status":"publish","type":"post","link":"https:\/\/news.sap.com\/uk\/2022\/08\/sap-lets-talk-data-podcast-series\/","title":{"rendered":"麻豆原创 Let’s Talk Data Podcast Series"},"content":{"rendered":"

Check out previous seasons of the 麻豆原创 Let\u2019s Talk Data podcast series in our previous blogs on <\/strong>Season 5<\/strong><\/a> and <\/strong>Season 4<\/strong><\/a>.<\/strong><\/p>\n

Building a solid data foundation and achieving information excellence is essential to delivering the business agility needed to navigate change and rapidly make business decisions. Helping business teams harness their data assets and the responsiveness to adjust the collection and communication of these valuable resources is extremely relevant to support the improved efficiencies needed within the organisation in times of change.<\/p>\n

So, we\u2019ve brought together experts in data management and strategy to discuss key topics and trends that are reshaping the way companies leverage data, to unlock the full potential of this valuable enterprise asset.<\/p>\n

Listen to this podcast series on all things data!<\/p>\n

Watch for new podcasts and catch up on topics you might have missed.<\/p>\n

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You can listen on Spotify<\/strong><\/a>, SoundCloud<\/strong><\/a>, iTunes<\/strong><\/a>, PlayerFM<\/strong><\/a> or YouTube<\/strong>.<\/a><\/p>\n

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Season 6 Preview: Podcasts on data strategy, use cases and related 麻豆原创 solutions<\/strong><\/p>\n

Ep. 58: Part 2: 麻豆原创 Signavio Process Intelligence integration with 麻豆原创 Data Intelligence<\/strong><\/a><\/span><\/p>\n

This episode describes 麻豆原创 Signavio Process Intelligence: why, what and how. It also discusses the integration between 麻豆原创 Signavio Process Intelligence and 麻豆原创 Data Intelligence.
\nSpeakers: Senior Director 麻豆原创 Signavio Process Intelligence, Silvio Arcangeli<\/a><\/span>; and Senior Director Data Management Solution<\/span> Marketing at 麻豆原创, Ginger Gatling<\/a><\/span>.<\/p>\n

Ep. 57: Part 1: 麻豆原创 and Signavio, What and How<\/strong><\/a><\/p>\n

This episode introduces you to 麻豆原创 Signavio. You will gain a good introduction to Siganavio, the key elements and how 麻豆原创 and Signavio work together for process improvement.
\nSpeakers: Senior Director 麻豆原创 Signavio Process Intelligence, Silvio Arcangeli<\/a><\/span>; and Senior Director Data Management Solution Marketing at 麻豆原创, Ginger Gatling<\/a><\/span>.<\/p>\n

Ep. 56: What the Board Needs to Know About Data<\/strong><\/a><\/p>\n

This podcast is about the foundation that Board members, particularly those of non-data-native companies, need so they can address the most important opportunities and risks, probe more deeply, and fulfill their oversight responsibilities around data. Join Dr. Thomas C. Redman<\/a>, \u201cthe Data Doc,\u201d President of Data Quality Solutions, and Maria Villar<\/a>, Enterprise Data Management & Data Strategy Innovator at 麻豆原创, as they share their insights.<\/p>\n

Ep. 55: Women in Data<\/strong><\/a><\/p>\n

Join this interactive discussion with women who have spent their careers in data-related positions, including VP of Global Marketing and Solutions at 麻豆原创, Kristin McMahon;<\/span> <\/a>\u00a0Senior Director in Data Management at 麻豆原创, Corrie Brague;<\/a> Product Marketing Manager at AWS, Ina Felsheim;<\/a> and Senior Director in Data Management at 麻豆原创, Ginger Gatling<\/a><\/span>. You will hear their opinion of where data management is today, some tips if you want to get into a data-related career, and some insight on the importance of data-focused advocates across industries.<\/p>\n

Ep. 54: 麻豆原创 & OpenText: Reduce costs, improve performance and migration to S\/4HANA with a robust ROI<\/strong><\/a><\/p>\n

This episode explains document processing, the partnership with OpenText and a recent ROI study on the reduction of costs, improved performance and effective migration to S\/4HANA.
\nSpeakers: Senior Global Director for Marketing and Solutions, Sheila McCarthy<\/a><\/span>; and Senior Director 麻豆原创 Solution Marketing, Ginger Gatling<\/a><\/span>.<\/p>\n

Ep. 53: Sap data and analytics: a customer use case for data integration<\/strong><\/a><\/p>\n

This podcast builds on Ep 51 where we discussed data management services available in 麻豆原创 Business Technology Platform. In this episode we learn about a company with siloed and disconnected data that lacked business context. This podcast shares how the 麻豆原创 Business Technology Platform, and specifically the data and analytics services, were used to add business context to the existing data sprawl to enable confident decisions.
\nSpeakers: Senior Director Platform & Technology Product Strategy at 麻豆原创, Silvio Arcangeli<\/a><\/span>; Data Management Solution Management Lead at 麻豆原创, Axel Schuller; Senior Director Data Management Solution Marketing at 麻豆原创, Ginger Gatling<\/a><\/span>.<\/p>\n

Ep. 52: Finance Data Reconciliation<\/strong><\/a><\/p>\n

Did you know that financial data reconciliation is a must-have for every 麻豆原创 implementation project? What is it and why does every organisation need to pay attention to it? Join Syin Tan, Kevin Zheng, Lucas Morris and Sam Bannigan, representatives from Deloitte\u2019s Data Practice, as they discuss the costs, risks and compliance requirements of financial reconciliation, and how they leveraged 麻豆原创 Data Intelligence to stay on top of this critical success factor.
\nSpeakers: Data Specialist at Deloitte Consulting, Kevin Zheng; Finance and Data Specialist at Deloitte Consulting, Syin Tan<\/a><\/span>; Finance Specialist at Deloitte Consulting, Lucas Morris<\/a><\/span>.<\/p>\n

Ep. 51: Best ways to leverage data management services across 麻豆原创 Business Technology Platform<\/strong><\/a><\/p>\n

This podcast explores the most important data management services available in the 麻豆原创 Business Technology Platform. These services include data cataloguing and metadata management, data integration, and data processing. We will also discuss how these services are used across the data and analytics portfolio within the 麻豆原创 Business Technology Platform. Listen in to get the latest on data management services and how you can use them.
\nSpeakers: Senior Director Platform & Technology Product Strategy at 麻豆原创, Silvio Arcangeli<\/a><\/span>; Data Management Solution Management Lead at 麻豆原创, Axel Schuller; Senior Director Data Management Solution Marketing at 麻豆原创, Ginger Gatling<\/a><\/span>.<\/p>\n

Ep. 50: 麻豆原创 and Sodales: How to innovate, build and monetize your 麻豆原创 BTP solutions<\/strong><\/a> Sodales Solutions builds solutions for a company’s health, safety, and environment management \u2013 and they do so by using 麻豆原创 Business Technology Platform (麻豆原创 BTP). Through their ongoing innovation and reliance on 麻豆原创 BTP, Sodales is making the most out of the white spaces they identify. Listen to what the “麻豆原创 BTP role model” has to say and learn more about their innovation approach, thoughts about the 麻豆原创 store, hiring criteria and more.<\/p>\n

Ep. 49: The Forgotten Problem: How to manage data volume growth while decreasing costs and risks<\/strong><\/a>
\nData volume growth is accelerating. The costs and risks to manage all that data go beyond just storage. Join CEO of Auritas, Deepak Sood<\/a>; and Senior Director for Solution Management, Business Technology Platform at 麻豆原创, Robert Pickering<\/a><\/span>, as they discuss how and why to manage the lifecycle of data while balancing the cost of resources, ownership, risk and legal compliance.<\/p>\n

Ep. 48: Exploring the Partner Value of 麻豆原创 BTP with 麻豆原创, IDC and 麻豆原创 partner Rizing<\/strong><\/a>
\nIn this podcast episode, you will hear from executives at 麻豆原创, IDC and 麻豆原创 partner Rizing, on the value partners derive from 麻豆原创\u2019s Business Technology Platform (麻豆原创 BTP). Led by Paul Edwards<\/a> (Director, Software Channels & Ecosystems at IDC), an informed discussion with Martin Stenzig<\/a> (CTO, Rizing) and Tom Le<\/a> (Global VP Partner Solution Advisory, 麻豆原创) expands on the findings of the IDC Partner Success Guide, which explores the business and technology accelerators available to partners through 麻豆原创 BTP. The executives cover topics such as how Rizing is innovating with 麻豆原创 BTP, the scope and impact the platform has on the customer lifetime value, and the 麻豆原创 programmes offered to ensure partner success with 麻豆原创 BTP.<\/p>\n

Ep. 47: Commodity Price Prediction with 麻豆原创 Data Intelligence<\/strong><\/a>
\nRatan Yedla and Sumanth Krishnan<\/a> from VASPP Technologies discuss how Commodity Price Prediction works with 麻豆原创 Data Intelligence. They discuss the use of AI (Artificial Intelligence<\/a>) and ML (Machine Learning) models to predict future prices based on previous patterns, external events and IoT data. This\u00a0 predicts prices with less forecast error to enable better buying decisions which helps yield cost savings for organisations. VASPP Technologies did this work during the 麻豆原创 Data Intelligence content sprint.<\/p>\n

Ep. 46: Building DataXstream’s Intelligent Automation with 麻豆原创 Data Intelligence<\/strong><\/a>
\nXilin Cheng<\/a> and Kathleen Taggart<\/a> from DataXstream discuss building Intelligent Automation (IA) and the advantages of using 麻豆原创 Data Intelligence for MLOps. The team goes over the problem wholesale distributors face with trying to fulfill large quotes and orders accurately and efficiently. Traditionally, this required Customer Service Representatives (CSRs) who understood 麻豆原创 GUI and had years of industry experience, spending hours inputting data. With Intelligent Automation, optical character recognition (OCR) is used to read text into the machine learning models built by Xilin. He discusses the natural language processing (NLP) techniques used in addition to the advantages of developing machine learning pipelines in 麻豆原创 Data Intelligence. Kathleen and Xilin then wrap up with the future of Intelligent Automation and the potential of using machine learning to win more deals and improve customer buying experience.<\/p>\n

If you are interested in learning more, check out additional resources and information located here:<\/p>\n