Dynamic Talks Seattle/Redmond: “Big Data Analytics”

Join us at the next event of our free technical meetup series, “Dynamic Talks”, in Redmond!

Dynamic Talks is an ongoing meetup series featuring technical talks from some of the leading experts in tech in major cities around the US. Enjoy talks about the most innovative subjects in AI, ML, analytics, voice platforms, the Cloud, and search. Enjoy a night of technical talks and networking opportunities at the Microsoft Reactor space in Redmond. We hope to see you there!

Topic: “Big Data Analytics”

Agenda

: Guests arrive, food and drinks are served.

: The first talk will be presented by Max Martynov on “Implementing data quality automation with open source stack,” followed by a Q&A

: Networking break

: The second talk will be presented by Chitra Rath on “Data Analytics at adidas: Success stories, challenges and opportunities,” followed by a Q&A

: Networking break

: Third talk by Maria Jeannette Sanabria on “The Human and the AI:  How Artificial Intelligence (AI) can make us better Humans and that is good for Business and You!,” followed by a Q&A.

: Networking, closing remarks, and event conclusion.

Talk Details:

Max Martynov talk details:

Title: “Implementing data quality automation with open source stack.”

Abstract: The quality of business decisions, machine learning insights, and executive reports depend on the quality and integrity of the underlying data. There are many ways that data can get corrupted in an analytical data platform from de-synchronization with the system-of-record to defects in data pipelines. We will show how to detect and prevent data corruption with automation, open-source tools, and machine learning.

About Max Martynov:

Max Martynov is the VP of Technology at Grid Dynamics, leading High-Performance Computing practices for enterprises. Over the last decade, his technical focus evolved from HPC and scalable distributed platforms to Cloud, BigData, DevOps, and Microservices architecture. He is also an author of the book “Continuous Delivery Blueprint: Software change management for enterprises in the era of cloud, microservices, DevOps, and automation”, which is now available on Amazon.

Chitra Rath talk details:

Title: “Data Analytics at Adidas: Success stories, challenges and opportunities”

Abstract: The talk would revolve around the initiatives taken in recent times by Adidas to integrate data and analytics rigorously in the decision-making process. I would talk about the broad efforts taken towards building predictive models in forecasting, estimation of ROI, pricing, etc. The talk would also touch upon the applications of Machine Learning in our analytic efforts, challenges we faced, and the opportunities going forward.

About Chitra Rath: 

Chitra works as the Senior Manager of data analytics and manages a data analytic team at Adidas. Her team partners with stakeholders in finance, supply chain, digital analytics, and other departments to build predictive models, conduct advanced analytics, perform data wrangling, and improve processes. Their tech stack includes SQL, R, Python, Alteryx for analytics. Their team is part of a larger and recent initiative within Adidas to use data as the building block of decision-making processes. Her background is in Economics, and she finished her doctoral work from the University of Wisconsin at Milwaukee. Prior to Adidas, she worked at comScore and First Tech and worked in data analytics, risk management, and model building. She lives with my husband and my six-year-old Boston Terrier (who is the boss of the family) in Hillsboro, OR.

Maria Jeannette Sanabria talk details:

Title: “The Human and the AI:  How Artificial Intelligence (AI) can make us better Humans and that is good for Business and You!“

Abstract: Businesses can harness AI to augment and enhance human’s capabilities to bridge customer expectations/satisfaction with employee efficiency. With AI this can be easily accomplished while creating a personalized and tailored Customer Experience (CX) at a larger scale than was previously possible.  In an era where organizations are transforming to a people-centricity focus to stay solvent and relevant to customers, it will require some “soul” searching and discipline on the behalf of businesses, to understand the right use cases, application, and balance of AI to actual human intervention in order to ensure that they do not lose sight of the authentic human experience they are trying to foster.  

This talk will explore the following topics:

• The case for why the human and AI symbiotic relationship is a good thing when applied appropriately
• Brief history of AI, what is creating the surge in interest and adoption, and what other market factors are converging
• Use cases and real examples of where AI is being used to improve Customer Experience (CX) in the Customer Buying Journey
• Transitioning of careers from the old traditional roles to new AI business roles and how they will interact with Data Scientists and Business Intelligent Analysts

About Maria Jeannette Sanabria: 

Maria Sanabria is a Transformation Leader in Operations for Philips Healthcare, where she is spearheading projects to infuse AI into digital customer platforms to enhance the Customer Experience (CX) and Employee Experience (EX). She has 24+ years’ experience implementing cutting-edge, emerging, disruptive technologies for End-to-End Marketing 2 Cash Transformation Programs.  She is a Citizen Data Scientist, who was one of the first people globally to be certified in 2019 as a Salesforce Einstein Analytics and Discovery Consultant. She was recognized in the Salesforce Dreamforce 2019 Einstein Keynote as one of the first Einstein Analytics Champions for the Salesforce AI product. She launched a program with local Georgia small businesses to match them with junior salesforce administrators and plans to extend this program in 2020 to include entry level AI roles. She is currently in the process of writing a book about Career Transitions – No Degree Required: How to transition to a Citizen Data Scientist Career in the Era of AI.