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Datasentics 08.04.2022

DataSentics webinars

Latest webinars

Content highlights:

The importance of dynamic pricing solutions
Common challenges in pricing
Traditional vs AI approaches
Our AI dynamic pricing solution: data processing, demand estimation, and optimization
Implementation and customization of our solutions

Content highlights:

Key Use Cases in FSI: Automating complex tasks, from extracting data in contracts to building chatbots that streamline internal operations.
Databricks as a GenAI Platform: Tools like Vector Search, LLMs, and Serverless Serving that enable faster, smarter decision-making.
Limitations of GenAI: Understand the challenges, including potential inaccuracies (“hallucinations”), and how to evaluate these solutions effectively.

Content highlights:

Basics and advantages of the Data Lakehouse models.
Strategies for effective data integration and management.
Best practices for reducing costs and increasing efficiency in your data projects.

In this session, we will focus on:

Explore the latest state-of-the-art tools and techniques, with insights into their unique benefits and applications.
Learn how genAI tools can help reducing time & costs of product photoshoots.
Gain a technical understanding of data requirements, training processes, and automation for scalable visual generation.
Security and compliance questions regarding patient data in the cloud
Explore the images we've created for various companies to demonstrate genAI capabilities.

Topics we will cover:

Shopping experience funnel: Identifying the problems in the consideration phase and understanding why addressing them is crucial.
Enhancing consideration phase with GenerativeAI: Transitioning from typical solutions like blog posts to Generative AI technologies.
Real-world Case study: Our client, Heureka - the largest price comparison website and shopping guide in Central Europe.

In this session, we will focus on:

The benefits of migrating your data from on-premises to the cloud
The main advantages and capabilities of Databricks’ Data & Intelligence platform
How to transition from your current architecture to a more advanced state
Security and compliance questions regarding patient data in the cloud
Success stories: Best practices and lessons learned

Main topics:

Identify new leads and opportunities in customer interactions.
Enrich models by extracting data from customer communications.
Automatically scan and monitor banker-client interactions for regulatory violations and performance.
Automate the extraction of information from documents.

Main topics:

Production-like data for development: how to make security happy
Governing Generative AI use-cases
The hard part of using virtual networks to keep data separated
Maximal security vs. reasonable costs - what the options are on Azure
Environments & development process best-practices (Platform, Sandbox, Test, Prod, LAB)
Scaling Unity Catalog to hundreds of users and TBs of data using terraform
Q&A session

Main topics:

Understand how Digital Twin and Predictive Maintenance help you spot anomalies effectively.
Strategies for processing and efficiently managing the extensive data generated by Digital Twins.
Learn how this technology can cut down on operational expenses by proactively preventing breakdowns.
Hear our latest success story of our client, Acond.

With Digital Pathology Pipeline, you can:

Measure size of tumors
Visualize tumors using heatmaps
Segment and highlight functional units of tissues
Cluster samples into groups based on their visual characteristics
Detect anomalies in pathology, radiology and other modalities of images

Topics to be covered:

Why should AI-driven analytics be used for business location optimization?
Brief overview of the AI Optimization Engine & map interface.
Key challenges faced and the process of integrating historical, demographic, and geospatial data.

Topics to be covered:

Key areas where we see impactful use cases
The current state of maturity and typical limits for productionalization
Key concerns, risks, and security

What will you learn?

How to migrate data from SAP BW?
Is it worth the effort and does it require specific licenses?
How to process data in (near) real time?
What is the cost of the DataSentics migration accelerator?

What will you learn?

How to improve customer engagemen
How to drive business results
What are the biggest blockers and gap skills within project/solution teams

Co si z webináře odnesete?

Naučíme vás nezbytné základy pro vytváření obrázků
Poradíme, jak online generovat grafiku snadno a za co nejnižší náklad
Předvedeme také několik pokročilejších postupů a služeb

Previous webinars

Webinars in English

Key topics:

Drop-off prevention from web app/funnel
Customer service (call centres, inbound)
Enriching CRM (Proactive retention & customer satisfaction management)
Cookieless targeting & 360 Attribution modelling
Customer 360 profil

Key topics:

How do you ensure your stock never runs out?
Is your shelf management data-driven?
How does Nestlé manage on-shelf availability with Shelf Inspector?

Key topics:

What services or products are your customers looking for?
What is their decision-making process?
Are the leads passed on to the right department?
What happens when a customer complains about the product via e-mail or chat?

Key topics:

Are you using AI/ML to detect fraud?
Do you offer a personalised experience?
What are the goals of an on-premises migration to the cloud?

Key topics:

Combine traditional credit risk, machine learning, and graph neural networks
Establish the probability of default for customers based on their behaviour
Improve credit risk scoring of new-to-bank clients and apply scoring even to non-clients

Key topics:

What does the end of 3rd party cookies mean for publishers?
What are the new opportunities?
How can publishers leverage machine learning?
What are the options for publishers now?

Key topics:

Drive innovation by reducing infrastructure spend
Achieve higher productivity by eliminating manual tasks
Accelerate your business by making use of the Databricks unified analytics platform’s AI capabilities

Webinars in Czech

Témata webináře:

Rozdíly mezi AWS, Azure a GCP
Proč poptávka po cloud specialistech roste
Co obnáší práce cloud engineera

Témata webináře:

Jaké to je pracovat v kalifornii jako ML engineer
Jaké rozdíly Dan vnímá mezi prací pro start-up a zaběhlou firmou
Jak to vypadá, když firma raketově vyroste
Jaké byly začátky, na co si dát pozor a Danova očekávání vs. realita

Témata webináře:

Co naše kolegy motivovalo jít zrovna do dat/ML
Co čekali a potvrdilo/nepotvrdilo se jim
Co nečekali a příjemně je to překvapilo
Co je na datech netěžší/největší výzva

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