Hi [[ session.user.profile.firstName ]]

Der Übergang von Business Intelligence zu Analytics

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.
Recorded Feb 26 2020 34 mins
Your place is confirmed,
we'll send you email reminders
Presented by
Timm Grosser, BARC Head of Consulting & Sr Analyst
Presentation preview: Der Übergang von Business Intelligence zu Analytics

Network with like-minded attendees

  • [[ session.user.profile.displayName ]]
    Add a photo
    • [[ session.user.profile.displayName ]]
    • [[ session.user.profile.jobTitle ]]
    • [[ session.user.profile.companyName ]]
    • [[ userProfileTemplateHelper.getLocation(session.user.profile) ]]
  • [[ card.displayName ]]
    • [[ card.displayName ]]
    • [[ card.jobTitle ]]
    • [[ card.companyName ]]
    • [[ userProfileTemplateHelper.getLocation(card) ]]
  • Channel
  • Channel profile
  • Data Science Pioneers: Conquering the Next Frontier - 8PM AEDT (Sydney) Apr 8 2020 10:00 am UTC 63 mins
    Dataiku
    With humor and humanity, Data Science Pioneers presents a fireside chat-style documentary about the passionate data scientists driving us towards technological revolution.

    Cut through the hype with Data Science Pioneers and see what it really means to be a data scientist.

    Even though the name is new, the role has a long lineage in statistics and information sciences. And while the challenges data scientists now face occur on an unprecedented scale today, they stand on the shoulders of technical and ethical quandaries that came before.

    Dataiku will release the documentary online soon, watch it now in avant-premiere
  • Data Science Pioneers: Conquering the Next Frontier - 8PM NZDT (AUCKLAND) Apr 8 2020 8:00 am UTC 63 mins
    Dataiku
    With humor and humanity, Data Science Pioneers presents a fireside chat-style documentary about the passionate data scientists driving us towards technological revolution.

    Cut through the hype with Data Science Pioneers and see what it really means to be a data scientist.

    Even though the name is new, the role has a long lineage in statistics and information sciences. And while the challenges data scientists now face occur on an unprecedented scale today, they stand on the shoulders of technical and ethical quandaries that came before.

    Dataiku will release the documentary online soon watch it now in avant-premiere
  • Enterprise AI, from Cost to Revenue Center Apr 7 2020 6:00 am UTC 64 mins
    Alexis Fournier
    In the coming years, the ability of organizations to pivot their activities around Enterprise AI will fundamentally determine their fate. Those able to efficiently leverage ML techniques to improve business operations and processes will get ahead of the competition. Of course, the key word here is efficiently; it’s not enough for organizations to simply leverage ML techniques at any price. Eventually, in order for Enterprise AI strategy to be truly sustainable, one must consider the economics: not just gains, but cost.

    Common sense and economics tell us not to start from scratch every time you have a new idea, new use case to be tested/implemented. Reuse is the simple concept of avoiding too much rework in AI projects and the concept of capitalization in Enterprise AI takes reuse to another level.

    This session will explain how Dataiku enables every organization to benefit from AI by allowing people within the organization to scale, providing transparency and reproducibility throughout - and across - teams.
  • How to Process Tons of Data for Cheap with Spark + Kubernetes Apr 6 2020 6:00 pm UTC 75 mins
    Gus Cavanaugh, Sales Engineer @ Dataiku
    This webinar has something for everyone, whether technical or not. On the business side, you’ll get an overview of how to better manage your infrastructure spend while providing the compute your analysts and data scientists need as well as a practical demonstration of how autoscaling your data processing infrastructure provides the horsepower you need without breaking the bank.

    On the technical side, if you like Spark for processing big data and Kubernetes for scaling and managing containers but you haven’t run Spark on Kubernetes yet, this is the webinar for you. In this one hour session, you’ll learn:

    - Why Kubernetes is a great scheduler for Spark jobs
    - How to quickly spin up a managed Kubernetes cluster on AWS and run you first Spark job from your environment
    - How Dataiku lets data scientists spin up Kubernetes clusters and run Spark jobs with just a few mouse clicks
  • Auto-ML : qu’est-ce que c’est et comment en tirer parti ? Recorded: Apr 2 2020 26 mins
    Nicolas Omont, Product Manager, Dataiku
    Dataiku vous propose un webinar sur le thème de l'Automated Machine Learning. L'AutoML a en effet été très utilisé en 2019, et reste un sujet incontournable à aborder par les entreprises en 2020 afin d'intensifier les efforts de l'IA. En effet, l'AutoML permet aux entreprises d'économiser énormément de temps et de ressources.

    Ce webinar abordera :

    - Ce qu'est exactement l'AutoML (et ce qu'elle n'est pas).
    - Pourquoi les entreprises ont besoin d'AutoML pour réussir dans la course à l'IA.
    - Quels sont les meilleurs cas d'utilisation d'AutoML et comment en tirer le meilleur bénéfice.

    Dataiku vous accompagne à travers ce webinar, afin que vous puissiez découvrir pourquoi et comment l'automatisation du Machine Learning devient de plus en plus un élément clé du succès de l'IA.
  • Data Science for Supply Chain Recorded: Apr 1 2020 58 mins
    Jesus Oliva (JTI), Mohamad Ali Mahfouz (Microsoft), Marie Vollmar (Dataiku)
    Supply chain optimization impacts every industry, from retail to manufacturing, transportation to warehousing. Machine learning and AI bring additional opportunities to tighten supply chain logistics using new sources of data and new techniques that can radically improve operations, most notably at the hyper-local level.

    In January 2018, Business Insider found that 42% of organizations surveyed identified supply chain and operations as driving revenue from AI capabilities today.

    During this webinar, Japan Tobacco International shares insights on what data science did for their company's logistics & stock optimization:
    In direct selling operation models, logistic optimizations play a key role since the internal organization is fully responsible for the end to end distribution chain. Optimizing the daily van loading means minimizing load/unload operations, optimize the time spent in the warehouse, still keeping under control out of stock potential losses.

    We will cover the following:
    - Jesus Oliva, Data Science & AI Expert at Japan Tobacco International, shares insights on what data science did for his company's logistics & stock optimization
    - How Dataiku can help organizations to introduce AI-driven processes into the supply chain
    - How the Microsoft Data Platform and partner ecosystem can help enterprises to transform into data-driven organizations and what is the needed culture change to build a data gravity culture

    Please be aware that by registering for this webinar, you agree to have your information shared with Dataiku's partner Microsoft.
  • Beyond Human Labeling and Supervised Learning w/ Google Recorded: Mar 26 2020 93 mins
    Karthik Ramasamy (Google) and Ned Martorell (Dataiku)
    Typically most companies have been using supervised learning with human labeled dataset. However, thirst for more labels is never satisfied, especially for deep learning models. In this talk, Karthik will talk about technologies to overcome lack of abundance of human labeled dataset with specific examples in computer vision and NLP domains. The talk will explain how synthetic dataset can be used to train a model that can be generalized to operate on real world data. Then, Karthik will cover self-supervised learning that is becoming an emerging trend in large scale deep learning tasks. The talk will focus on a couple of use cases of self-supervised learning techniques that are general enough to be applicable in the majority of computer vision tasks.
  • Pourquoi et Comment Passer du Design à l’Automation ? Recorded: Mar 26 2020 55 mins
    Antoine Vokleber (Chief Architect), Sébastien Decaudain (Delivery Practice Manager), Eric Carbonel (Implementation Manager)
    Conscientes de la valeur de leur capital de données, les entreprises accélèrent chaque jour leurs initiatives Datascience.
    Utiliser Dataiku permet à des profils techniques et/ou Métiers de créer rapidement et simplement des projets de data science pour explorer, manipuler et restituer de la valeur à partir de données brutes.

    Au fil du temps, ces projets peuvent rapidement s’accumuler et se posent alors une multitude de questions :

    - Comment identifier un projet récurrent d’un POC ou d’un simple test ?
    - Comment prioriser l’exécution d’un batch pour reporting au Comex versus le projet d’un stagiaire ?
    - Comment maintenir des performances de la plateforme ?
    - Comment s’interfacer de façon fiable avec d’autres systèmes ?

    Dans ce webinaire, nous contextualiserons cela et vous présenterons les apports de l’environnement de production Dataiku (Automation et API).

    Nous détaillerons également les différentes approches possibles pour une fluidification des échanges entre un univers métiers et un univers IT.

    Présentateurs:
    - Antoine Vokleber (Chief Architect chez Lincoln)
    - Sébastien Decaudain (Delivery Pracitice Manager chez Lincoln)
    - Eric Carbonel (Implementation Manager chez Dataiku)

    En vous inscrivant à ce webinaire, vous acceptez que vos informations soient partagées avec les partenaires de Dataiku et Lincoln.
  • Enterprise AI, from Cost to Revenue Center Recorded: Mar 25 2020 65 mins
    Alexis Fournier
    In the coming years, the ability of organizations to pivot their activities around Enterprise AI will fundamentally determine their fate. Those able to efficiently leverage ML techniques to improve business operations and processes will get ahead of the competition. Of course, the key word here is efficiently; it’s not enough for organizations to simply leverage ML techniques at any price. Eventually, in order for Enterprise AI strategy to be truly sustainable, one must consider the economics: not just gains, but cost.

    Common sense and economics tell us not to start from scratch every time you have a new idea, new use case to be tested/implemented. Reuse is the simple concept of avoiding too much rework in AI projects and the concept of capitalization in Enterprise AI takes reuse to another level.

    This session will explain how Dataiku enables every organization to benefit from AI by allowing people within the organization to scale, providing transparency and reproducibility throughout - and across - teams.
  • Auf Dem Weg zu Enterprise AI- Kollaboration mit Dataiku DSS Recorded: Mar 25 2020 31 mins
    Nadine Schoene, Sales Engineer
    Wäre es nicht wunderbar, wenn in einem datengetriebenen Projekt alle Beteiligten transparent und im selben Tool Ihren Beitrag leisten könnten? Dataikus Data Science Studio (DSS) ermöglicht genau diese Kollaboration, indem es zum einen die passenden Werkzeuge sowohl für Coder als auch für Clicker im selben Projekt liefert, und zum anderen auch Informationsaustausch und Dokumentation in diesem Projekt vereinfacht. In unserem halbstündigen Webinar geben wir einen Überblick über diese neuen Möglichkeiten der Kollaboration.
  • Talking Seriously Powerful Data Analytics Recorded: Mar 24 2020 44 mins
    Lucio Floretta (GCP),Thomas Cabrol (Dataiku), Greg Willis (Dataiku)
    Running on the Google Cloud Platform offers a superior experience to Dataiku users, bringing the ability to create and operationalize AI applications at scale and speed. Dataiku has deep integrations with the GCP products, extending its compute and storage capacities, and allowing all users, coders or not, to leverage the GCP services from one place.

    Lucio Floretta from GCP, sits down with Thomas Cabrol 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.
  • Top 3 Use Cases für Data Science in Marketing Recorded: Mar 12 2020 34 mins
    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.
  • Accélérez vos projets de Data Science avec Dataiku, Snowflake & Eulidia Recorded: Feb 27 2020 57 mins
    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.
  • Ask the Experts: 2020 Data Science Trend Report Recorded: Feb 26 2020 19 mins
    Reda Affane, Joel Belafa, Jed Dougherty, Katie Gross, Will Novak | Dataiku
    What will be the hottest data science and machine learning trends in the new decade? Was 2019 really the year of NLP? Will we see more or less of deep learning and reinforcement learning in 2020? Five of Dataiku's very own data experts answer it all.
  • Der Übergang von Business Intelligence zu Analytics Recorded: Feb 26 2020 34 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 Recorded: Feb 25 2020 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. 

    REGISTER FOR FREE

    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

    Speakers:

    + 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. **
Enabling 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.

Embed in website or blog

Successfully added emails: 0
Remove all
  • Title: Der Übergang von Business Intelligence zu Analytics
  • Live at: Feb 26 2020 9:00 am
  • Presented by: Timm Grosser, BARC Head of Consulting & Sr Analyst
  • From:
Your email has been sent.
or close