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Lightning Fast Value from Data Science with Dataiku on Google Cloud Platform

Join our upcoming webinar with MandM Direct, UK's second-largest online fashion retailer, to find out how working with Dataiku and Google Cloud Platform has created value from data science in no amount of time.

Learn more about:
- MandM Direct's workflow before Dataiku and Google Cloud Platform and the things that held them back.
- Why they selected Dataiku as their ML platform partner.
- How they deployed DSS on Google Cloud Platform (quickly) and the benefits that come from this partnership - speed, ability to scale, and cost control.

Speakers:
- Ben Powis (Data Science Manager, MandM Direct)
- Becky Postlethwaite (Industry Manager Retail, Google Cloud)
- Stephen Franks (Sales Engineer, Dataiku)

Please be aware that by registering for this webinar, you agree to have your personal information shared with Dataiku's partner Google Cloud.
Recorded Jul 2 2020 56 mins
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Presented by
Ben Powis (MandM Direct), Becky Postlethwaite (Google Cloud), Stephen Franks (Dataiku)
Presentation preview: Lightning Fast Value from Data Science with Dataiku on Google Cloud Platform

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  • Channel
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  • Die Macht von KI für Data & Analytics Aug 27 2020 8:00 am UTC 30 mins
    Timm Grosser, BARC Head of Consulting & Sr Analyst
    Das 3. Webinar unserer BARC Serie zum Thema der Rolle von KI für Data und Analytics
  • Dataiku Demo Days: Automate Your Data-to-Insights Process Aug 25 2020 6:00 pm UTC 45 mins
    Blanden Chisum, Solutions Engineer, Dataiku
    Ready to accelerate your time to insight? In just 30 minutes, we will show you how to turn your biggest data problem into that business-changing report to continually put the power of AI in the hands of your stakeholders. Join this session to discover how you can breeze through the monotonous yet necessary data prep steps in Dataiku's interactive spreadsheet-like recipe experience.

    Dataiku Demo Days is a series of expert-led demos on various high-value AI use cases, such as driving efficiencies in the data-to-insights process and maximizing campaign impact with AutoML. These digestible sessions are designed to help jumpstart your organizations’ data efforts and inject agility at every step of the process.
  • Predict & Prevent Customer Churn with Machine Learning Aug 25 2020 6:00 am UTC 42 mins
    Vincent De Stoecklin
    Given that it costs 5-10 times more to acquire a new customer than to retain an existing one, it seems obvious that all businesses should engage in some level of churn prevention.

    Because of its business impact and its relative ease in execution, for many types of business, churn prediction is a great first project to tackle with machine learning and AI.

    In this webinar, Vincent De Stoecklin, Customer Success Director at Dataiku, will:
    > Explain how data science and machine learning can help leverage churn prevention
    > Deep-dive into a churn prediction project (from design to production)
    > and demo a churn analysis on Dataiku DSS.
  • Data Governance & Regulating Data Privacy w/ NYT Aug 24 2020 6:00 pm UTC 64 mins
    Max Gendler (NYT)
    Talk abstract:

    Privacy, data governance, and ethics have all become essential topics in a modern data-driven company. But what does all this truly mean and how do you get started with them?

    As a data governance manager, you regularly get asked what data governance is. By definition, it’s a combination of three things: formalizing behaviors, holding people accountable, and supporting ethics at scale. But what does that really mean and how do you put it into practice? It's easier to think of it as the standardization of work, both the setting of standards and testing for them to ensure that they are applied, while simultaneously getting people to want to do the right thing. In a number of ways, governance is a giant design problem. How can we make the right thing easy? We'll dive into this question and more in this Zoom webinar.

    Speaker bios:

    Max Gendler is a manager on the Data Governance Team at The New York Times. He started his career working in business intelligence at an ad-tech startup before moving to the New York Times as a member of the advertising analytics team. He joined the Data Governance team at the beginning of this year after having collaborated with them in his previous role. His main work is focused on helping bridge the gap between tech and policy teams within the organization.

    Disclaimer: All views, thoughts, & opinions expressed in the webinar belong solely to the panelists, & not to the panelists’ employer, organization, committee, other group or individual.
  • Your Path to NLP Mastery in Dataiku DSS Aug 20 2020 4:00 pm UTC 75 mins
    Katie Gross, Lead Data Scientist @ Dataiku
    Are you looking to leverage natural language processing (NLP) for your projects, but aren’t sure where exactly to start? This webinar will show you how with one single tool you can go from raw data to a fully operationalized NLP model, using the Dataiku DSS NLP features and plugins.

    It will go over:
    > Text Cleaning (normalization, stop word removal, stemming, and using regular expressions for custom text cleaning tasks)
    > Text Vectorization (conversion to numeric features) via traditional vectorization (TF-IDF, Count Vectorization, SVD) and word embeddings (Word2Vec, GloVe, FastText, ELMo)
    > Deep dive into using Dataiku DSS for key NLP techniques, such as text classification, topic modeling, and sentiment analysis.

    The webinar will be presented by Katie Gross, Lead Data Scientist at Dataiku.

    ** This webinar is the second in a 2-part series on NLP. Don't forget to check out the first webinar on NLP basics, which covers what it is, how it can be used, main algorithms, and more. **
  • Recommendation Systems & Personalization Models w/ NBCUniversal Aug 19 2020 11:00 pm UTC 75 mins
    Misael Manjarres (Senior Director of Data Science @ NBC Universal)
    Tentative Schedule: (EST)

    7:00pm: Intro
    7:05pm: Recommendation Systems & Personalization Models w/ NBCUniversal
    7:45pm: Q&A

    Talk Abstract:

    The “Streaming Wars” have reached their peak in the last few months as several new streaming services have launched, including NBCU’s Peacock. As a consequence, user’s have thousands of hours of content to choose from on multiple platforms. Recommendation systems and personalization models have therefore never been more important. Unfortunately, in the race to develop the best recommendation system, the models in industry are sinking further and further into “black boxes”. Our team will discuss how Peacock is building a personalization framework that not only delivers accurate models, but also provides actionable insights to other relevant business units.
  • Leveraging AI in Manufacturing: Cross-functional Process Optimization Aug 19 2020 3:00 pm UTC 60 mins
    Aashish Majethia
    Every process throughout manufacturing from design, production, to supply chain logistics can be optimized with AI. Collaborative modeling across the various stages of production can lead to significantly higher returns in the form of optimized machine settings and fault detection to innovate faster and improve yield.

    Join us as we walk through inter-process collaboration, team orchestration, and dive into iterative cross-team modeling to see how your organization can leverage the power of AI to optimize the full lifecycle of bringing a product to life.
  • Governance and Security of Data Preparation: Use Case Deep Dive & Q&A Aug 18 2020 6:00 pm UTC 45 mins
    Will Nowak
    Governance and security are some of the biggest challenges facing financial institutions - and even more so now in a time of remote work. Risk of isolated, desktop-based development, versioning and auditing of data prep, and governed and secure collaboration are issues on the minds of many in the data and analytics space. Enter Dataiku as a solution.

    In this session, our financial services expert and solutions engineer, Will Nowak, will address this key challenge through use cases, notable examples, and industry observations from our customers in the space.
  • Fake News!? A Single platform for Data & Analytics Aug 18 2020 6:00 am UTC 44 mins
    The Business Application Research Center (BARC) - Timm Grosser, Senior Analyst
    What does it really mean to have a unified data and analytics platform? Today’s organizations are faced with the task of providing integrated data for analytics, which can be quite challenging due to the fragmented data landscape and numerous data silos on top of previously existing organizational and technological challenges.

    This talk will discuss how data platforms offer the chance to encapsulate the complexity in data management, simplify data use, and/or functionally support different types of users in their tasks. It will cover the challenges a unified data and analytics platform should solve, what added value users can expect, and explain that, even with data science tools, integration goes beyond the platform — data and analytics need to be woven into the fabric of the organization across people, processes, and technology.
  • Optimizing Personalization Using Machine Learning & AI w/ Accenture Aug 13 2020 6:00 pm UTC 75 mins
    Charles Hack, Kate Cunningham, Hector Parmantier
    Tentative Schedule: (EST)

    2:00pm: Intro
    2:05pm: Optimizing Personalization Using Machine Learning & AI w/ Accenture
    2:45pm: Q&A

    Talk Abstract:

    Retail has long pursued the “holy grail” of product offers and deals which result in both happier customers, and net sales or margin lift. For customers, this equates to Personalization – getting the products they want, for a better price, easier and faster. For the Retailer, this equates to an optimization problem. The Accenture team will talk about how we recently solved this challenge in production for a major US Pharmacy, using Machine Learning and AI.

    Speaker bios:

    Charlie is Accenture’s Capability Lead for Data Science in the Northeast Region, driving data science innovation at the intersection of data science, engineering, industry, and government. He works with clients across Health, the Public Sector, Communications, Media and Technology, Products, and Resources on data science and machine learning projects, with 6 years of experience in the firm. He is based out of NYC, where he also studied Mathematics at Columbia University. In coding, Charlie is strongest in Python, pandas, and numpy.

    Hector is a data science consultant at Accenture NE region. Throughout his consulting years between Europe and the US, he has built and led data-driven solutions using cutting-edge techniques in the fields of machine learning & big data in various industries such as Healthcare, Banking, & Retail.

    Kate is an Accenture Data Science Senior Analyst in the Northeast Region. She is motivated by developing rigorous answers to complex quantitative questions and excels in tackling problems from a multi-faceted understanding. Kate holds an undergraduate degree in Mathematics and an M.S. in Analytics.

    Disclaimer: All views, thoughts, & opinions expressed in the webinar belong solely to the panelists, & not to the panelists’ employer, organization, committee, other group or individual.
  • How to improve your Forecasting by adopting a Data Science approach? Aug 11 2020 6:00 am UTC 64 mins
    Alexandre Hubert, Sales Engineering Director
    Take part in the webinar to discover what are the benefits of a Data Science approach in Forecasting.

    Forecasting has been used since the 1950s in anticipating risks and making decisions. But in the era of AI and algorithms, older modeling techniques fail to integrate the amounts of data sources needed to produce results that are accurate enough for modern business.

    This webinar provides an overview of Forecasting addressed through Dataiku. You will be shown the example of sales forecasting to illustrate, in a concrete way, the steps to follow to combine business expertise with Data Science techniques. You will then be able to understand how to refine your forecasts, automate them, and multiply them in many use cases applicable to Forecasting.
  • The Power of AI in the Insurance Industry | With Dataiku and Aviva Recorded: Aug 6 2020 57 mins
    Sophie Dionnet, VP Strategy at Dataiku and Elena Furlan, Senior Data Scientist at Aviva
    The insurance industry is often characterized as traditional and slow-moving, or worse, one that is not as customer-centric as it should be — making getting data science and AI initiatives off the ground a challenging undertaking. However, when done properly and with thoughtful alignment of people, processes, and technology, insurance companies can transform the way they work with data, generating value across a variety of use cases.

    In this talk, Dataiku’s VP of Strategy Sophie Dionnet will be joined by Elena Furlan, Senior Data Scientist at Aviva, the U.K.’s largest multi-line insurer, to discuss the vast potential for AI in the insurance space, from theoretical insights to practical implementations. Specifically, Elena will give an example of an advanced AI project that her team worked on — the business problem Aviva wanted to address, what worked well, challenges involved, tangible results, and more — and how they will continue to push forward on their journey to Enterprise AI.
  • The Scope of Data Science in the Sports World Recorded: Aug 3 2020 74 mins
    Paul Sabin (ESPN), Ruchir Pandya (NBA)
    Tentative Schedule: (EST)

    7:00pm: Intro
    7:05pm: The Scope of Data Science in the Sports World
    7:45pm: Q&A

    Talk Abstract:

    Sports analytics is generally defined as using data related to any sports or game and has only recently come into the limelight . Despite the sports industry being so rich in data, adoption of analytics in sports has been rather bumpy and ambiguous and there remains plenty of room for penetration. In this fireside chat, we’ll be discussing how impactful advanced analysis and predictive modeling can outperform regular custom/legacy analysis in the sports world. We’ll also dive into conversation surrounding how state of art models outperform old analysts methods and the resulting consequences that have reshaped sports business.
  • Data Governance & Regulating Data Privacy w/ NYT Recorded: Jul 30 2020 65 mins
    Max Gendler (NYT)
    Talk abstract:

    Privacy, data governance, and ethics have all become essential topics in a modern data-driven company. But what does all this truly mean and how do you get started with them?

    As a data governance manager, you regularly get asked what data governance is. By definition, it’s a combination of three things: formalizing behaviors, holding people accountable, and supporting ethics at scale. But what does that really mean and how do you put it into practice? It's easier to think of it as the standardization of work, both the setting of standards and testing for them to ensure that they are applied, while simultaneously getting people to want to do the right thing. In a number of ways, governance is a giant design problem. How can we make the right thing easy? We'll dive into this question and more in this Zoom webinar.

    Speaker bios:

    Max Gendler is a manager on the Data Governance Team at The New York Times. He started his career working in business intelligence at an ad-tech startup before moving to the New York Times as a member of the advertising analytics team. He joined the Data Governance team at the beginning of this year after having collaborated with them in his previous role. His main work is focused on helping bridge the gap between tech and policy teams within the organization.

    Disclaimer: All views, thoughts, & opinions expressed in the webinar belong solely to the panelists, & not to the panelists’ employer, organization, committee, other group or individual.
  • Better Pricing, Happier Customers: Changing Insurance with Data Recorded: Jul 30 2020 49 mins
    Caroline Worboys - COO & Founder @ Outra, David Spencer - Sales Director @ Outra
    Insurance is changing, consumers are more selective and new entrants are creating significant change with quick disruption. Much of this is happening because of great use of data science and technology. Most insurance decisions are about probabilities and managing risk. Often, these decisions are based on historic models and a limited view of the customer. However, many organizations are now changing and starting to use data, and data science to drive real value from multiple disparate data sources to make more informed decisions.

    In this webinar, we talk about how we are working with key insurers to deliver value. This will include examples like confidence scores on data attributes to aide quick form fill and aggregating data from multiple sources to become not just product driven but customer driven.
  • ML-Driven Operations Optimization in Healthcare and Patient Forecasting Recorded: Jul 29 2020 46 mins
    Emma Irwin, Sales Engineer at Dataiku
    AI applications that reduce human labour have already become mainstays of the medical world. Virtual nursing assistants, automatic patient booking and other AI-enabled tools have helped providers, pharmacies and insurers reduce costs.

    A major use case for ML in operations is predicting hospital bed or emergency room availability in hospitals. Emergency room overcrowding is an expensive and dangerous problem that predictive modeling can help address. If a surge in need is predicted, hospitals can prioritize discharging patients to free up space or redirect incoming cases to nearby hospitals. Emma Irwin will present use cases, best practices and then show how to build and optimize ML models in Dataiku's Data Science Studio.
  • How to Get Started With NLP Recorded: Jul 28 2020 64 mins
    Katie Gross, Lead Data Scientist @ Dataiku
    Natural Language Processing (NLP), the branch of machine learning and AI which deals with bridging the gap between human language and computer understanding, is all the rage right now. Once a relatively niche topic, in the past few years landmark new models and applications have brought NLP to the center-stage of real-world enterprise data science and AI.

    This webinar will give data scientists a framework for getting started with NLP projects. It will go over:
    • What exactly NLP is and how it’s used
    • How to clean and pre-process text for machine learning projects
    • An overview of some of the main NLP algorithms and how they work
  • Leverage AI in Manufacturing: Predictive Maintenance Recorded: Jul 27 2020 42 mins
    Aashish Majethia & Mindi Grissom
    Leveraging AI is an efficient way to provide real-time visibility into the production process to reduce downtime for maintenance and costs for efficient operations. Join us as we walk through how sensor data can be transformed to timely insights via predictive maintenance with automated insight improvement.

    During this webinar, we will:
    - Look at how to define the values for the warranty of owned products
    - Determine when purchased equipment might fail to deploy resources to service customers
    - Look at root cause analysis and model drift.
  • Driving Diversity in Data Science & Analytics Recorded: Jul 24 2020 89 mins
    Polly Mitchell-Guthrie, Vanessa C. Martin, Afyia Miller, Fay Cobb Payton
    Tentative Schedule:

    2:00pm: Intro
    2:05pm: Driving Diversity in Data Science & Analytics
    2:45pm: Q&A

    How diverse is the lucrative, growing field of data science & analytics? Does the current demographics composition of this field prognosticate a promising future of diversity? In this panel, we’ll look at the current state of diversity in data science, why these historic inequities matter, & what we can all do to do better. We will draw from the experiences of our panelists who can speak from the point of view of an underrepresented group (female &/or POC) in STEM. We will elicit our speakers’ viewpoints on a number of issues including a lack of STEM education for minority groups early on in life, opportunities of mentorship for women / POC in data science, & how we can better catch up to gender balance policies. Our aim is to move the needle & broaden the data science & analytics field to include more women & people of all kinds who don’t fit the narrow stereotypes of the time.
  • Mit Data & AI durch die Krise Recorded: Jul 23 2020 57 mins
    Jörg Bienert, Partner und CPO, Alexander Thamm/ Daniel Hladky, Partner Manager, Dataiku
    Die aktuelle Situation ist für die gesamte Weltwirtschaft eine Krise, jedoch können Daten und Künstliche Intelligenz helfen, dieser entgegenzuwirken. Registrieren Sie sich jetzt für einen exklusiven Austausch über die Herausforderungen und Potentialen einer aktiven Datennutzung - und Auswertung mit den AI Experten der Alexander Thamm GmbH und Dataiku!
Your Path to Enterprise AI
Dataiku is the centralized data platform that moves businesses along their data journey from analytics at scale to enterprise AI. By providing a common ground for data experts and explorers, a repository of best practices, shortcuts to machine learning and AI deployment/management, and a centralized, controlled environment, Dataiku is the catalyst for data-powered companies.

Customers like Unilever, GE, BNP Paribas, Santander use Dataiku to ensure they are moving quickly and growing exponentially along with the amount of data they’re collecting. By removing roadblocks, Dataiku ensures more opportunity for business-impacting models and creative solutions, allowing teams to work faster and smarter.

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  • Title: Lightning Fast Value from Data Science with Dataiku on Google Cloud Platform
  • Live at: Jul 2 2020 3:00 pm
  • Presented by: Ben Powis (MandM Direct), Becky Postlethwaite (Google Cloud), Stephen Franks (Dataiku)
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