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Dataiku Demo Days: Automate Your Data-to-Insights Process

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.
Recorded Aug 25 2020 37 mins
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Presented by
Blanden Chisum, Solutions Engineer, Dataiku
Presentation preview: Dataiku Demo Days: Automate Your Data-to-Insights Process

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  • Channel
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  • The Human Role in AutoML Nov 12 2020 6:00 am UTC 44 mins
    Timm Grosser, Senior Analyst, Business Applications Research Center (BARC)
    Will AI replace the Data Scientist?

    AI promises a lot of potential for speeding up processes and making tools, functions, even entire workflows easier to use. This is valid throughout the entire analytics process, from model creation to model operation.

    During the webinar, we will learn:
    1) Potential and impacts of AI
    2) Illustrate this using the example of the Advanced Analytics process.
    3) Outlook on future application scenarios of AI
  • Hype und Realität von KI und Data Science in datengesteuerten Unternehmen Nov 5 2020 1:00 pm UTC 60 mins
    Manuel Nitzsche/ Dataiku, Clarissa Vogelbacher/ ITM Predictive GmbH, Frank Oechsle/ Esentri
    Wie sieht die Transformation zu einem datengesteuerten Unternehmen aus? Wie wird ein Data Science Projekt umgesetzt und für welche Anwendungsfälle? Nach der 1-stündigen Vorstellung mit Experten zu diesen Themen zeigen wir Ihnen exklusiv den Film "Data Science Pioneers" über die Realität und Herausforderungen eines Data Scientists und die Chancen von Data Science für Unternehmen und unseren Alltag.
  • Roll out insights to the whole business using Data Science Platform Nov 5 2020 6:00 am UTC 53 mins
    Slava Razbash
    You might have an excellent data science team, but how do they productionalize their insights so that they are accessible by all stakeholders, all the time? If your team is emailing spreadsheets with confidential information around the company, it's time for a better solution.
     
    Slava will present how teams can use Dataiku DSS to securely share insights with stakeholders via a centralized platform.
  • Dataiku Demo Days Ep.3: Sales Forecasting and Geocoding Oct 28 2020 6:00 pm UTC 45 mins
    Emma Irwin, Sales Engineer, Dataiku & Claude Perdigou, Senior Product Manager, Dataiku
    Understanding the location data of sales and having the ability to accurately forecast revenue are critical components for a business’s success. Join us for Demo Days where we’ll show you how you can build predictive models to predict revenue for the coming days or weeks, and understand, optimize, and visualize your data by location in order to optimize business practices and streamline your day-to-day operations.

    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.
  • Fraud Detection- How to Operationalize your Models? Oct 27 2020 6:00 am UTC 49 mins
    Alexandre Hubert, Sales Engineering Director
    We are pleased to bring the second installment of a two-part webinar series on Fraud Detection. During the 1st webinar, we addressed why fraud hasn’t been solved yet. Addressed the need to move beyond a rule-based approach and how to navigate the creative thinking of fraudsters.

    During this webinar, we will look at fraud detection from a platform perspective and discover how to integrate ML techniques to the existing rule-based approach within an ML Framework and how to feed your fraud detection pipeline with right set of algorithms in order to ease the implementation of your use cases.
  • Fraud Detection: Why It Hasn't Been Solved Yet? Oct 20 2020 6:00 am UTC 26 mins
    Alexandre Hubert, Sales Engineering Director
    Global fraud in 2019 was nearly $60 billion, demonstrating how it is a global problem and not siloed to one industry. Fraudsters 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.

    During the first installment of this two-part webinar series, you will discover why there is a need to move beyond a rules-based approach for fraud detection, how to navigate the creative thinking of fraudsters, and the many factors that go into a machine learning fraud detection model
  • Foundational Data Science for Personalized Communications w/ Nike Oct 19 2020 11:00 pm UTC 75 mins
    Ankit Gupta (Sr. Data Scientist @ Nike)
    Tentative Schedule: (EST)

    7:00pm: Intro
    7:05pm: Foundational Data Science for Personalized Communications w/ Nike
    7:45pm: Q&A

    Talk Abstract:

    Email communication is one of the most common activities on PCs and mobile devices and this holds true now more than ever. Nike invests a lot of effort into Email communication. Although the cost of sending one email may be small, the cost builds up as the number of emails aggregates. Also, the user engagement governs the reputation of Nike IP addresses and the KPIs. Therefore, it is important to identify the campaigns relevant to consumers with a high propensity of engagement.
    The goal of the Personalized Communications team is to serve the Nike consumers with the most relevant campaign emails at the right time with the right frequency. In this talk, Ankit will address important questions/topics relevant to the Personalization Communications team. He will also answer questions that explain how Nike is currently handling personalized communications, what’s working well and what’s not, and how to build the data foundation for Personalized Communications. Finally, Ankit will do a deep-dive into some of the data science models that the team is currently working on.

    Speaker bio:

    Ankit has 4+ years of experience informing business decisions through data science and statistical modeling. He is currently working as Sr. Data Scientist at Personalization and Data Science team at Nike. His previous experiences include working in Ad Tech and Finance industry.
  • Improve Supply Chain and Marketing Data Science Models with Weather Data Oct 8 2020 9:00 pm UTC 60 mins
    Christian Schneider (wetter.com), France Hureaux (wetter.com)
    From production to customer behavior, weather is a powerful parameter to monitor and master. Meteonomiqs data science team will share with you some of the technical requirements to build the best-in-class models including weather data. We demonstrate together with Dataiku DSS the usage of the plugin and illustrate how easy it is for citizen data scientists to build data flows.

    Speakers:
    - Christian Schneider, Senior Data Scientist at wetter.com
    - France Hureaux, Senior Strategy Manager at wetter.com

    Please be aware that by registering for this webinar, you agree to have your personal information shared with Dataiku's partner wetter.com. They may contact you with information that could be of interest to you.
  • Completing the Demand Planning Cycle with Data Science Oct 1 2020 9:00 am UTC 60 mins
    Dan Roozemond (EyeOn), Martin Daudey (EyeOn)
    The steps for a typical demand planning cycle are: review & correct historical data, statistical base line forecast, enrichment by marketing/sales, consolidate and consensus meeting, validate results & improve.

    Learn in this session how data science can help you completing the cycle in shorter intervals and with higher quality by integrating a data science platform into the planning cycle.

    Speakers:
    - Dan Roozemond, Data Science Team Lead at EyeOn
    - Martin Daudey, Sr. Business and Solutions Consultant at EyeOn

    Please be aware that by registering for this webinar, you agree to have your personal information shared with Dataiku's partner EyeOn. They may contact you with information that could be of interest to you.
  • Large Scale Machine Learning via SQL on Google BigQuery with BQML w/ Google Recorded: Sep 29 2020 58 mins
    Sanjay Agravat (Machine Learning Specialist @ Google Cloud)
    Tentative Schedule: (EST)

    2:00pm: Intro
    2:05pm: Large Scale Machine Learning via SQL on Google BigQuery with BQML w/ Google
    2:45pm: Q&A

    Talk Abstract:

    In this talk, Sanjay will discuss how to perform machine learning using SQL for a variety of model types and the flexibility of using BQML to import and export models.

    Speaker bio:

    Sanjay Agravat is a Machine Learning Specialist for Google Cloud based out of Atlanta, GA. Sanjay started his career in Software Engineering and later pursued an academic calling as he completed his PhD in Biomedical Informatics at Emory University and went on to do a fellowship at Harvard Medical School. Now at Google Cloud, he helps educate customers on how to leverage Google Cloud Platform for ML/AI solutions and support them in their journey along the way.

    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.
  • Dataiku Demo Days Ep.2: ML-Based Marketing Attribution Models Recorded: Sep 29 2020 50 mins
    Greg Cashman, Senior Sales Engineer, Dataiku
    Historically, marketing attribution has been a painstakingly manual process based on heuristic models that often turn out to be more difficult (and less effective) than necessary. And unfortunately, due to their perceived simplicity, many marketing teams turn to outdated techniques such as the last click heuristic, where all the conversion merits are attributed to the last media contact or channel the customer was exposed to. This does not adequately capture user engagement, and risks undervaluing campaigns and content that are critical to conversion. Fortunately, the significant advances in marketing AI and machine learning (ML) in recent years allow organizations to solve perennial problems in new, more efficient ways. Join us for Demo Days and in just 30 minutes we will show you how to build, deploy, monitor and optimize ML-based attribution models.

    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.
  • Making Deep Learning Solutions Accessible with Dataiku DSS Apps Recorded: Sep 29 2020 36 mins
    Dr. Robert Coop
    The Dataiku DSS 8.0 release introduces Apps, the ability to distribute your analytic project to a much broader audience such as subject matter experts and business analysts.


    In this session, Dr. Robert Coop, phData’s General Manager of Machine Learning, will demonstrate how apps can be used to allow end-users to classify emotions expressed by people in videos using deep learning. This talk will demonstrate how to take a complex project and to package it into an application that enables users to benefit from the results of deep-learning emotion classification without having to understand the analytic process.
  • Leveraging data science for financial forecasting Recorded: Sep 24 2020 34 mins
    Jesus Oliva, Sr Data Scientists, Marie Vollmar, Enterprise AI Strategist
    Take a closer look at the use of data science in financial forecasting with European Association of Corporate Treasurers Award Winners JTI and learn how they improved forecast accuracy by 20%, while reducing their workload as much as 80%!
  • How to Successfully Deploy Data Science Projects in Production? Recorded: Sep 24 2020 47 mins
    Vincent De Stoecklin, Customer Success Director, APAC
    Building a data science (DS) project and training a model is only the first step. Getting that model to run in the production environment is where companies often fail: according to McKinsey, less than 10% of DS projects are deployed into production with an average deployment time of 9 to 12 months.

    Vincent De Stoecklin, Customer Success Director at Dataiku, will talk about best practices and key learnings to make this crucial step of the data science process easier.

    During the session, we will cover:
    1) How organisations deploy AI, ML, DS projects in production
    2) What are some key challenges and learnings
    3) Real-life examples of companies who have successfully deployed data science products.
  • End-To-End Operational ML with Dataiku and HPE Ezmeral ML Ops Recorded: Sep 17 2020 58 mins
    Sandeep Deshmukh (HPE), Dietrich Zinsou (HPE), Daniel Hladky (Dataiku)
    Enterprises are facing challenges with operationalizing their ML models as they move from PoCs to production.

    The emerging field of ML Ops – machine learning operations – aims to deliver agility and speed to the ML lifecycle similar to what DevOps processes have done for the software development lifecycle.

    In this webinar, we will discuss how to:
    - Overcome the barriers of deploying and operationalizing ML models
    - Gain faster time-to-value, increase productivity, and reduce risk with a flexible end-to-end ML Ops solution
    - Deploy and access data more efficiently whether on premises, in the cloud, or a hybrid environment

    Join this webinar to learn how Dataiku and HPE are bringing speed and agility to the ML lifecycle.

    Speakers:
    - Sandeep Deshmukh, Product Manager ML Ops at Hewlett Packard Enterprise
    - Dietrich Zinsou, Senior Solutions Architect at Hewlett Packard Enterprise
    - Daniel Hladky, Senior Partner Manager at Dataiku

    Please be aware that by registering for this webinar, you agree to have your personal information shared with both partners Dataiku and Hewlett Packard Enterprise. They may contact you with information that could be of interest to you.
  • Your Path to NLP Mastery in Dataiku DSS Recorded: Sep 17 2020 61 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 - To replay this first webinar: https://www.brighttalk.com/webcast/17108/421893.
  • How to Combat Healthcare Fraud Using Machine-Learning Techniques Recorded: Sep 10 2020 66 mins
    Grant Case, Solution Engineering Director
    Fraud in the healthcare industry is on the rise globally and APAC is no exception. Accurate fraud detection in healthcare has the potential to make medicine better, more affordable, and more accessible.

    Join our webinar where we will discuss how to detect and prevent fraud and see how to combine traditional and machine learning-based methods within a fraud detection framework.

    The webinar will be presented by Grant Case, Director of Sales Engineering for APAC at Dataiku, and will feature a data science showcase followed by a Q&A.
  • Chartering Success Within Analytics Teams w/ Poshmark Recorded: Aug 31 2020 48 mins
    Ankur Uttam (Senior Director, Analytics at Poshmark)
    Tentative Schedule: (EST)

    7:00pm: Intro
    7:05pm: Chartering Success Within Analytics Teams w/ Poshmark
    7:45pm: Q&A

    Do you or your analytics team struggle to have your voices heard? Are a lot of your ideas overlooked and/or credited to someone else? Do you want a seat on the business table? In this session, Ankur will talk about how you can change the charter of your analytics team from being a service organization to getting a seat on the table for strategic planning and decision making. He will talk about how to build and groom your team, how to create an environment to foster innovation and motivation, how you can go about navigating the organization structure and hierarchy to have your voices (ideas) heard and how to maintain your seat on the table (once you have it.)
  • Die Macht von KI für Data & Analytics Recorded: Aug 27 2020 34 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 Recorded: Aug 25 2020 37 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.
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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  • Live at: Aug 25 2020 6:00 pm
  • Presented by: Blanden Chisum, Solutions Engineer, Dataiku
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