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2020 AI Trends in the Enterprise

This non-technical webinar will go in-depth on the trends that will dominate Enterprise AI for the decade, particularly when it comes to organizational changes in businesses.

Conor will discuss the larger organizational and operational changes to come in 2020, including:

- The 2nd Generation of Data Scientists
- Managing Cloud Costs
- Shifting Data Education
- The Move Toward Initiative-Driven Teams
- The Rise of MLOps
- Continued Focus on Explainability

...and more!
Recorded Feb 4 2020 41 mins
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Presented by
Conor Jensen, Customer Success Lead @ Dataiku
Presentation preview: 2020 AI Trends in the Enterprise

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  • Talking Seriously Powerful Data Analytics Mar 24 2020 4:00 pm UTC 60 mins
    David Gordon (GCP), Hillorie Farace di Villaforesta (Dataiku), Greg Willis (Dataiku)
    David Gordon, ISV Alliances at GCP, sits down with Hillorie Farace di Villaforesta and Greg Willis of the Dataiku Technology Alliances team to talk about the shift from a start-up to bonafide leading AI Software Platform for the Enterprise.

    During this webinar, they discuss Dataiku's take on inclusivity, collaboration, and elastic AI, as well as the GCP Partnership for 2020 and beyond.
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    Manuel Nitzsche, Account Executive, Dataiku
    Welche Möglichkeiten bietet Data Science zur Unterstützung von Marketingprojekten? Wie lässt sich der Erfolg von Kampagnen und Marketingaktivitäten anhand von Daten messen und stetig verbessern?
    In diesem Webinar zeigen wir die Top 3 Use Cases “Churn Prediction”, “Segmentation” und “Recommendation Engine” anhand echter Beispiele von Unternehmen, die datengetriebene Entscheidungen treffen.
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    Arnaud Canu (CTO chez Eulidia), Nicolas Lerose (Sales Engineer chez Snowflake), Pierre Carrere (Partner Manager chez Dataiku)
    Aujourd’hui nombreuses sont les entreprises déconnectées des environnements de production et de développement, les données sont en silos et les différents profils engagés souffrent du manque de collaboration, générant retards, voire échecs, des projets.

    Dataiku, Snowflake et Eulidia vous invite à un webinaire en français, où nous verrons ensemble comment construire et déployer simplement des projets Data Science sur Dataiku DSS avec Snowflake : le Data Warehouse construit pour le Cloud.

    Vous découvrirez les avantages que vous apportent les deux solutions combinées :
    - La capacité à gérer plusieurs pétaoctets de données grâce à l’élasticité & la puissance de calcul requises pour les projets de Machine Learning
    - Une interface graphique intuitive pour analyser et visualiser toutes vos données, et ainsi supporter vos projets de data science de bout en bout
    - Une plateforme simplifiant la collaboration dans vos projets data, permettant aux équipes de toutes tailles d’exécuter simultanément plusieurs workloads exigeants

    En vous inscrivant à ce webinaire, vous acceptez que vos informations soient partagées avec les partenaires de Dataiku, Snowflake et Eulidia.
  • Der Übergang von Business Intelligence zu Analytics Feb 26 2020 9:00 am UTC 30 mins
    Timm Grosser, BARC Head of Consulting & Sr Analyst
    Was ist Business Intelligence und wie geht man von BI zu Analytics? BARC Head of Consulting und Senior Analyst Timm Grosser wird beide data-centric Disziplinen in diesem Dataiku Webinar besprechen.
  • Machine Learning Based Fraud Detection: A Use Case Demo Feb 25 2020 3:00 am UTC 43 mins
    Kevin Graham, Advanced Technology Strategist for Financial Services, and Will Nowak, Solutions Architect
    Fraudulent actors are always looking for new ways to subvert legitimate transaction systems; traditional rules-based approaches are no longer sufficient (or efficient enough) to combat fraud. In this webinar, we’ll discuss best practices and examples on how machine learning can improve fraud detection capabilities.

    Data Scientists, Quants, and Analysts in the banking sector can benefit from expert best practices on tackling fraud detection. We’ll include a brief use case demo to concretely ground the discussion and discuss real-time considerations for detection. Kevin’s financial expertise and Will’s diverse implementation experience make them the perfect team to explore the host of factors that go into a machine learning fraud detection model.

    Kevin Graham is a Dataiku Account Executive with nearly 10 years of experience across financial services and technology. He started his career in Sales & Trading before moving into a technology sales capacity at Oracle and Merlon Intelligence. At Merlon, Kevin focused on how AI and machine learning could help solve complex challenges within financial crime compliance. He currently is part of a financial services focused sales team across the Eastern United States and Canada at Dataiku.

    Will Nowak is a solutions architect at Dataiku, where he helps Fortune 500 companies improve data science operations. Previously, he engineered machine learning models for several Y Combinator startups, learning the pitfalls and challenges to productionalizing machine learning. Will holds a bachelor’s in Math and Economics from Northwestern University and a Master’s in Organizational Leadership from Columbia University.
  • AutoML with Dataiku: An End-to-End Demo Recorded: Feb 5 2020 46 mins
    Nicolas Omont, Product Manager @ Dataiku
    If you're looking to leverage AutoML in your enterprise, this webinar will show you how with one tool, you can easily go from raw data to machine learning model in production using Dataiku's visual AutoML features.

    Nicolas Omont is a Product Manager at Dataiku. He holds a PhD in Computer Science, and he's been working in operations research and statistics for the past 15 years.

    ** This webinar is the second in a 2-part series on AutoML. Don't forget to check out the first webinar on AutoML basics, which covers what it is, how it can be used, challenges, and more. **
  • 2020 AI Trends in the Enterprise Recorded: Feb 4 2020 41 mins
    Conor Jensen, Customer Success Lead @ Dataiku
    This non-technical webinar will go in-depth on the trends that will dominate Enterprise AI for the decade, particularly when it comes to organizational changes in businesses.

    Conor will discuss the larger organizational and operational changes to come in 2020, including:

    - The 2nd Generation of Data Scientists
    - Managing Cloud Costs
    - Shifting Data Education
    - The Move Toward Initiative-Driven Teams
    - The Rise of MLOps
    - Continued Focus on Explainability

    ...and more!
  • 3 keys to moving toward white-box, explainable AI Recorded: Jan 29 2020 61 mins
    Dataiku x VentureBeat
    With black-box AI, people are refused or given loans, accepted or denied university admission, offered a lower or higher price on car insurance, and more, all at the hands of AI systems that usually offer no explanations. In many cases, humans who work for those companies can’t even explain the decisions.
    That’s why white-box AI is now getting heaps of attention. But what does it mean in practice? And how can businesses start moving away from black-box systems to more explainable AI? 
    We’ll delve into the three key components needed for white-box AI success: more collaborative data science, involving all teams from lines of business through IT; trust in data at all levels, including tools that
    can be used to increase transparency in data processes; and the role of education and the democratization of data. 
    And we’ll address why white-box AI brings business value in the first place and how it’s a necessary evolution for AI. Not only do customers care about explainable results of AI systems, but internally, white-
    box AI is less risky. Don’t miss this VB Live event on how to move towards explainable AI. 


    Key Takeaways:
    + How to make the data science process collaborative across the organization 
    + How to establish trust from the data all the way through the model
    + How to move your business toward data democratization


    + Triveni Gandhi, Data Scientist, Dataiku
    + David Fagnan, Director, Applied Science, Zillow Offers
    + Rumman Chowdhury, Global Lead for Responsible AI, Accenture Applied Intelligence
    + Seth Colaner, AI Editor, VentureBeat
  • AutoML Basics: What It Is and How Best to Leverage It Recorded: Jan 28 2020 34 mins
    Nicolas Omont, Product Manager @ Dataiku
    Automated Machine Learning, or AutoML, was all the rage in 2019, and it remains a huge topic for enterprises to tackle in 2020 in order to scale AI efforts.

    This webinar will cover:

    - What exactly AutoML is (and what it isn't).
    - Why organizations need AutoML in order to succeed in the race to AI.
    - What the best use cases are for AutoML and when it can best be leveraged.

    Nicolas Omont holds a PhD in Computer Science, and he's been working in operations research and statistics for the past 15 years.

    The session will include a Q&A session at the end, so come with your questions about AutoML!

    ** This webinar is the first in a 2-part series on AutoML. Don't forget to sign up for the follow-up session on AutoML in Dataiku - an end-to-end demo. **
  • 2020 Machine Learning Trends: A Look at Up-and-Coming Technology & Techniques Recorded: Jan 23 2020 29 mins
    The AI Lab team @ Dataiku - Alexandre Abraham, Aimee Coelho, and Leo Dreyfus-Schmidt
    This technical discussion of what's to come in 2020 will take a closer look at the hottest topics in machine learning research, including:

    - Active learning and semi-supervised learning
    - Reproducibility in ML
    - ...and much more

    Three research scientists will discuss what they're most excited about as well as possible practical applications of ML research. This webinar will be presented by The Lab research team at Dataiku, which seeks to contribute to the academic machine learning community as well as develop tools to assist everyone on their data journey.
  • 2020 AI Trends in the Enterprise Recorded: Jan 8 2020 42 mins
    Conor Jensen, Customer Success Lead @ Dataiku
    This non-technical webinar will go in-depth on the trends that will dominate Enterprise AI for the decade, particularly when it comes to organizational changes in businesses.

    Conor will discuss the larger organizational and operational changes to come in 2020, including:

    - The 2nd Generation of Data Scientists
    - Managing Cloud Costs
    - Shifting Data Education
    - The Move Toward Initiative-Driven Teams
    - The Rise of MLOps
    - Continued Focus on Explainability

    ...and more!
  • Crash Course in Data Architecture Recorded: Dec 17 2019 44 mins
    Jesse Bishop, Solutions Architect, Dataiku & Christina Hsiao, Tech Evangelist, Dataiku
    Data architecture is the foundation of every organization’s data strategy, but it's not just something for CIOs and data architects either - everyone at data-powered organizations can benefit from understanding the ways data moves between teams and flows into data projects to yield insights. In our Crash Course, we’ll cover key architecture terms and highlight different priorities regarding security and scalability. Additionally, we’ll discuss ways to strategize and align architectural concerns with business priorities.

    Jesse Bishop works with a wide variety of Fortune 500 clients and specializes in helping large organizations operationalize their AI workflow. Jesse is an Insight Data Science Fellow in New York City. He previously worked for the Federal Trade Commission developing models to predict the impact of mergers in a wide variety of industries including Energy, Semiconductors, and E-commerce. Jesse earned his Ph.D. in Applied Microeconomics from the University of Minnesota.

    Christina Hsiao is a technical evangelist for Dataiku based in the US. In her role, Christina is able to share her passion for applied data science through writing and by speaking with customers, partners, and organizations interested in solving business problems with the powerful combination of people, data, and technology. Prior to joining Dataiku, she spent nearly a decade at SAS, mainly specializing in Natural Language Processing and text analytics. Christina holds a bachelor’s degree in Mechanical Engineering from Stanford University.
  • AI in Finance: The Current Landscape, What the Future Holds, the Role of Fintech Recorded: Dec 12 2019 56 mins
    Alexandre Hubert, Lead Data Scientist at Dataiku
    Enterprise AI is at peak hype, yet AI has yet to fundamentally change most businesses - BFSI market is no exception.

    Fintech has swept in and remains on the cutting-edge of the AI and the finance spaces simultaneously, offering tough competition for those savvy enough to try and catch up. Yet there are some success stories beginning to emerge in large, traditional organizations (outside the fintech space) with learnings and takeaways for others ready to dive in.

    Specifically, this webinar will cover:

    - What fintechs bring to the table that makes them successful.
    - Recent use cases and successes in AI by traditional financial institutions.
    - What, on a wider level, has proved successful for traditional players and how it can be leveraged by your organization.
  • 5 Steps to Building Responsible AI Systems (featuring Forrester) Recorded: Dec 2 2019 63 mins
    Kurt Muehmel, VP of Sales Engineering at Dataiku, and guest Mike Gualtieri, VP and Principal Analyst at Forrester
    Responsible AI is essential for any company that wants to have robust AI systems in place in the future.

    This webinar will cover the essential steps to building AI systems that are responsible. But what does responsible AI mean? For a start, it’s about:

    - Making sure that systems are centralized for control over data yet flexible enough to allow for innovation.
    - Ensuring that robust monitoring is in place for all models.
    - Establishing trust in people and in data.
    - A company-wide dedication to models that are interpretable, unbiased, and ultimately won’t cause PR and trust issues for the company down the line.
    ...and more.

    Kurt Muehmel, VP of Sales Engineering at Dataiku, and guest Mike Gualtieri, VP and Principal Analyst at Forrester, will discuss the ins and outs of all of these topics (and more) for the first portion followed by a Q & A at the conclusion of the presentation. You’ll want to make sure to catch this webinar live for a chance to ask your questions about bringing responsible AI to your enterprise.
  • How to Achieve Big Data Insights Without Sacrificing Privacy Recorded: Nov 26 2019 43 mins
    Anjan Roy & Jamil Siddiqui of Deloitte Consulting | Jeremy Greze of Dataiku
    In today’s landscape with data privacy laws cropping up worldwide, some data teams have become paralyzed by uncertainty in how to navigate this new world. But armed with a productive governance strategy, organizations and individuals (from the data analyst to data scientist and IT professional) can continue to move forward in getting value out of data without compromising individuals’ privacy.

    This webinar will answer the following questions:

    - What are the biggest challenges of today’s data privacy landscape (and how can they be addressed)?
    - What are the best practices for using data while also remaining compliant?
    - How can organizations create access-controlled environments and easily handle right-to-erasure requests?

    Anjan Roy and Jamil Siddiqui, Managing Director and Specialist Leader at Deloitte consulting, along with Dataiku product manager Jeremy Greze will answer these questions by offering strategies for leveraging people, processes, and technology.
  • Top 5 data science challenges & opportunities in Financial Services Recorded: Nov 19 2019 48 mins
    Grant Case of Dataiku interviews Victor Tewari of BMO Capital and Jimmy Steinmetz of Interworks
    We surveyed more than 50 global data & analytics leaders about their top challenges for 2019.

    The results reveal that there are still fundamental challenges to leveraging AI and machine learning at scale.

    In this webinar, we sit down with banking data leaders to cut through the hype and discuss the real barriers and opportunities towards discovering value in data in 2019.

    We reveal and discuss those opportunities and challenges with Victor Tewari, Technology Officer in Predictive Analytics at BMO Capital and Jimmy Steinmetz, Solution Lead at InterWorks.

    This live event will be ideal for technical and non-technical audiences alike. If you can’t make the live time, register anyways and the recording will be sent to your inbox.
  • How Machine Learning Helps Levi’s Leverage Data to Enhance E-Commerce Experience Recorded: Nov 18 2019 71 mins
    An AWS and Dataiku Partnership
    Levi Strauss & Co. (Levi’s) had already migrated its store and data science applications to the cloud. It needed a way to quickly create prototypes and put them into production to create different meaningful customer experiences on the website.

    Levi’s used Dataiku Data Science Studio (DSS) and Amazon Web Services (AWS) to create a recommendation system that aligns to a customer journey, such as showing best-selling products in their region to new customers or displaying complementary items to complete an outfit to returning purchasing customers.

    Watch this webinar to learn how machine learning enables Levi’s to easily and quickly leverage its data to create new products for its customers.

    Watch to learn how to:

    - Try different algorithms and ways of connecting data together through data pipelines to move beyond experimentation into operations
    - Use Amazon SageMaker for model training
    - Create prototypes in Dataiku DSS and use AWS to put them into production
    - Run multiple processes in parallel
  • Discover Applied Deep Learning Basics Recorded: Nov 14 2019 51 mins
    Andrey Avtomonov, R&D Engineer at Dataiku & Rodrigo Agundez, Data Scientist at GoDataDriven
    Deep Learning models can be exceedingly powerful and accurate if you are willing to invest the time to train them. However, there’s no need to waste energy on poorly framed problems or building model architecture from the ground up. In this webinar, with GoDataDriven, we’ll reveal the best practices we’ve learned from leveraging Deep Learning in a variety of real-world systems, in addition to showing you how to access Deep Learning quickly, so that you can spend time personalizing your model to provide the best business value for your unique needs.

    Per registering to this webinar, you agree to get one email from GoDataDriven afterwards
  • Deployment and Operationalisation of Data Science Recorded: Nov 12 2019 31 mins
    Alexandre Hubert, Lead Data Scientist, Dataiku
    How to build production-ready data science projects?
    How to transition from a design to a production environment?

    Designing and validating models is only one part of a whole data science project.

    And today production issues are the main reason many companies fail to see real benefits come from their data science efforts.

    During this webinar, we will first understand what « to go into production » means and then consider actionable steps to build production-ready data science projects:

    1. Operationalisation: why is it important?
    2. Challenges from design to production
    3. Building production-ready AI projects
  • Machine Learning Basics: Algorithms Are Your Friend Recorded: Nov 5 2019 45 mins
    Katie Gross, Data Scientist
    Machine learning (ML) isn’t just for data scientists anymore; it’s in the mainstream for analytics and business teams who want to get ahead, but it can feel impenetrable. Where to start? Join Dataiku Data Scientist Katie Gross as she outlines key machine learning terms and the applications of different ML algorithms. See how you can build and evaluate an ML model with or without coding. Watch live and ask questions at our Q&A at the end of the talk.

    Katie Gross is a Data Scientist at Dataiku, where she helps clients build out Enterprise AI solutions and develops new product features. Previously, she worked as a data scientist at a marketing science firm, Schireson, and did freelance data science work for a host of companies including IBM. Prior to her data science life, Katie spent three years as a CPG consultant to Wall Street analysts at Nielsen. Katie holds a BA in Economics from Colgate University and also completed the Galvanize Data Science Bootcamp program in New York City.
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: 2020 AI Trends in the Enterprise
  • Live at: Feb 4 2020 3:00 am
  • Presented by: Conor Jensen, Customer Success Lead @ Dataiku
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