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Speaker: Tamika Tannis, Software Engineer - Data Products, Lyft
How Lyft Drives Data Discovery
How Lyft Drives Data Discovery
Neo4j
Amundsen is a metadata driven application for improving the productivity of data analysts, data scientists and engineers when interacting with data.
Strata sf - Amundsen presentation
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Tao Feng
Databricks used to use a static manually maintained wiki page for internal data exploration. We will discuss how we leverage Amundsen, an open source data discovery tool from Linux Foundation AI & Data, to improve productivity with trust by surfacing the most relevant dataset and SQL analytics dashboard with its important information programmatically at Databricks internally. We will also talk about how we integrate Amundsen with Databricks world class infrastructure to surface metadata including: Surface the most popular tables used within Databricks Support fuzzy search and facet search for dataset- Surface rich metadata on datasets: Lineage information (downstream table, upstream table, downstream jobs, downstream users) Dataset owner Dataset frequent users Delta extend metadata (e.g change history) ETL job that generates the dataset Column stats on numeric type columns Dashboards that use the given dataset Use Databricks data tab to show the sample data Surface metadata on dashboards including: create time, last update time, tables used, etc Last but not least, we will discuss how we incorporate internal user feedback and provide the same discovery productivity improvements for Databricks customers in the future.
Data Discovery at Databricks with Amundsen
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AI&BigData Conference 2017 Eugene Polonichko "Azure Data Lake: what is it? why is it? where is it?"
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Why we need Database Awareness? Document vs Relational Row-based vs Column-based In-memory Database vs In-memory Data grids Graph Time-series Solr vs ElasticSearch Event Store
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Build a simple data lake on AWS using a combination of services, including AWS Glue Data Catalog, AWS Glue Crawlers, AWS Glue Jobs, AWS Glue Studio, Amazon Athena, Amazon Relational Database Service (Amazon RDS), and Amazon S3. Link to the blog post and video: https://garystafford.medium.com/building-a-simple-data-lake-on-aws-df21ca092e32
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Speaker: Tamika Tannis, Software Engineer - Data Products, Lyft
How Lyft Drives Data Discovery
How Lyft Drives Data Discovery
Neo4j
Amundsen is a metadata driven application for improving the productivity of data analysts, data scientists and engineers when interacting with data.
Strata sf - Amundsen presentation
Strata sf - Amundsen presentation
Tao Feng
Databricks used to use a static manually maintained wiki page for internal data exploration. We will discuss how we leverage Amundsen, an open source data discovery tool from Linux Foundation AI & Data, to improve productivity with trust by surfacing the most relevant dataset and SQL analytics dashboard with its important information programmatically at Databricks internally. We will also talk about how we integrate Amundsen with Databricks world class infrastructure to surface metadata including: Surface the most popular tables used within Databricks Support fuzzy search and facet search for dataset- Surface rich metadata on datasets: Lineage information (downstream table, upstream table, downstream jobs, downstream users) Dataset owner Dataset frequent users Delta extend metadata (e.g change history) ETL job that generates the dataset Column stats on numeric type columns Dashboards that use the given dataset Use Databricks data tab to show the sample data Surface metadata on dashboards including: create time, last update time, tables used, etc Last but not least, we will discuss how we incorporate internal user feedback and provide the same discovery productivity improvements for Databricks customers in the future.
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AI&BigData Conference 2017 Eugene Polonichko "Azure Data Lake: what is it? why is it? where is it?"
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DataConf
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Database awareness
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Build a simple data lake on AWS using a combination of services, including AWS Glue Data Catalog, AWS Glue Crawlers, AWS Glue Jobs, AWS Glue Studio, Amazon Athena, Amazon Relational Database Service (Amazon RDS), and Amazon S3. Link to the blog post and video: https://garystafford.medium.com/building-a-simple-data-lake-on-aws-df21ca092e32
Building a Data Lake on AWS
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Data Engineering. Basics and getting started. References: The Data Engineering Cookbook by Andreas Kretz
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Presentation at SF Big Analytics meetup on Jan 12, 2021. https://www.meetup.com/SF-Big-Analytics/events/275217663/
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Big Data is the reality of modern business: from big companies to small ones, everybody is trying to find their own benefit. Big Data technologies are not meant to replace traditional ones, but to be complementary to them. In this presentation you will hear what is Big Data and Data Lake and what are the most popular technologies used in Big Data world. We will also speak about Hadoop and Spark, and how they integrate with traditional systems and their benefits.
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Institute of Contemporary Sciences
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Azure Synapse Analytics is Azure SQL Data Warehouse evolved: a limitless analytics service, that brings together enterprise data warehousing and Big Data analytics into a single service. It gives you the freedom to query data on your terms, using either serverless on-demand or provisioned resources, at scale. Azure Synapse brings these two worlds together with a unified experience to ingest, prepare, manage, and serve data for immediate business intelligence and machine learning needs. This is a huge deck with lots of screenshots so you can see exactly how it works.
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My updated Big Data with SQL Server presentation from my Razorfish case study. Presented Nov 17 @ Philly Code Camp.
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Dipping Your Toes: Azure Data Lake for DBAs
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RDX Insights Presentation - Microsoft Business Intelligence
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This is the first time I introduced the concept of Schema-on-Read vs Schema-on-Write to the public. It was at Berkeley EECS RAD Lab retreat Open Mic Session on May 28th, 2009 at Santa Cruz, California.
Schema-on-Read vs Schema-on-Write
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There are many options for providing SQL access over data in a Hadoop cluster, including proprietary vendor products such as Oracle Big Data SQL on the Oracle Big Data Appliance along with open-source technologies such as Apache Hive, Cloudera Impala and Apache Drill; customers are using those to provide reporting over their Hadoop and relational data platforms, and looking to add capabilities such as calculation engines, data integration and federation along with in-memory caching to create complete analytic platforms. In this session we'll look at the options that are available, compare database vendor solutions with their open-source alternative, and see how emerging vendors are going beyond simple SQL-on-Hadoop products to offer complete "data fabric" solutions that bring together old-world and new-world technologies and allow seamless offloading of archive data and compute work to lower-cost Hadoop platforms.
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Tired of seeing the loading spinner of doom while trying to analyze your big data on Tableau? Learn how Jethro accelerates your database so you can interactively analyze your big data on Tableau and gain the crucial insights that you need without losing your train of thought. Jethro enables you to be completely flexible with no need for partitions in order to speed up the data. This presentation will explain how indexing is a superior architecture for the BI use case when dealing with big data while compared to MPP architecture.
Jethro for tableau webinar (11 15)
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Talk by Joe Atkins-Turkish at Brex on why Brex chose Amundsen and their recent addition of Looker integration to Amundsen on November 5, 2020.
Amundsen at Brex and Looker integration
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When you model data you are making two decisions: * The location where data will be stored * How the data will be organized for ease of use
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This is the deck from my day-long presentation to some NorCal .NET developer UGs
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Big Data is the reality of modern business: from big companies to small ones, everybody is trying to find their own benefit. Big Data technologies are not meant to replace traditional ones, but to be complementary to them. In this presentation you will hear what is Big Data and Data Lake and what are the most popular technologies used in Big Data world. We will also speak about Hadoop and Spark, and how they integrate with traditional systems and their benefits.
How to use Big Data and Data Lake concept in business using Hadoop and Spark...
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Institute of Contemporary Sciences
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Hadoop Frameworks Panel__HadoopSummit2010
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Azure Synapse Analytics is Azure SQL Data Warehouse evolved: a limitless analytics service, that brings together enterprise data warehousing and Big Data analytics into a single service. It gives you the freedom to query data on your terms, using either serverless on-demand or provisioned resources, at scale. Azure Synapse brings these two worlds together with a unified experience to ingest, prepare, manage, and serve data for immediate business intelligence and machine learning needs. This is a huge deck with lots of screenshots so you can see exactly how it works.
Azure Synapse Analytics Overview (r1)
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My updated Big Data with SQL Server presentation from my Razorfish case study. Presented Nov 17 @ Philly Code Camp.
Big Data with SQL Server
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Mark Kromer
An introduction to Azure Data Lake for those already familiar with SQL Server. Presented at SQL Saturday Indianapolis on 17 August 2019
Dipping Your Toes: Azure Data Lake for DBAs
Dipping Your Toes: Azure Data Lake for DBAs
Bob Pusateri
May's RDX Insights Series Presentation focuses on Microsoft's BI products. We begin with an overview of Power BI, SSIS, SSAS and SSRS and how the products integrate with each other. The webinar continues with a detailed discussion on how to use Power BI to capture, model, transform, analyze and visualize key business metrics. We’ll finish with a Power BI demo highlighting some of its most beneficial and interesting features.
RDX Insights Presentation - Microsoft Business Intelligence
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Christopher Foot
This is the first time I introduced the concept of Schema-on-Read vs Schema-on-Write to the public. It was at Berkeley EECS RAD Lab retreat Open Mic Session on May 28th, 2009 at Santa Cruz, California.
Schema-on-Read vs Schema-on-Write
Schema-on-Read vs Schema-on-Write
Amr Awadallah
There are many options for providing SQL access over data in a Hadoop cluster, including proprietary vendor products such as Oracle Big Data SQL on the Oracle Big Data Appliance along with open-source technologies such as Apache Hive, Cloudera Impala and Apache Drill; customers are using those to provide reporting over their Hadoop and relational data platforms, and looking to add capabilities such as calculation engines, data integration and federation along with in-memory caching to create complete analytic platforms. In this session we'll look at the options that are available, compare database vendor solutions with their open-source alternative, and see how emerging vendors are going beyond simple SQL-on-Hadoop products to offer complete "data fabric" solutions that bring together old-world and new-world technologies and allow seamless offloading of archive data and compute work to lower-cost Hadoop platforms.
Enkitec E4 Barcelona : SQL and Data Integration Futures on Hadoop :
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Mark Rittman
These are the slides for my talk "An intro to Azure Data Lake" at Azure Lowlands 2019. The session was held on Friday January 25th from 14:20 - 15:05 in room Santander.
Azure Lowlands: An intro to Azure Data Lake
Azure Lowlands: An intro to Azure Data Lake
Rick van den Bosch
Presented at the UKOUG Business Analytics SIG Meeting in April 2016, addresses the question as to whether enterprise BI tools such as OBIEE12c are relevant in the world of Gartner BiModal Mode 1 + Mode 2 analytics, and Hybrid cloud/on-premise deployments
Oracle BI Hybrid BI : Mode 1 + Mode 2, Cloud + On-Premise Business Analytics
Oracle BI Hybrid BI : Mode 1 + Mode 2, Cloud + On-Premise Business Analytics
Mark Rittman
Graph databases are used to represent graph structures with nodes, edges and properties. Neo4j, an open-source graph database is reliable and fast for managing and querying highly connected data. Will explore how to install and configure, create nodes and relationships, query with the Cypher Query Language, importing data and using Neo4j in concert with SQL Server... Providing answers and insight with visual diagrams about connected data that you have in your SQL Server Databases!
Graph Databases for SQL Server Professionals
Graph Databases for SQL Server Professionals
Stéphane Fréchette
Did you know Microsoft provides a Hadoop Platform-as-a-Service (PaaS)? It’s called Azure HDInsight and it deploys and provisions managed Apache Hadoop clusters in the cloud, providing a software framework designed to process, analyze, and report on big data with high reliability and availability. HDInsight uses the Hortonworks Data Platform (HDP) Hadoop distribution that includes many Hadoop components such as HBase, Spark, Storm, Pig, Hive, and Mahout. Join me in this presentation as I talk about what Hadoop is, why deploy to the cloud, and Microsoft’s solution.
Introduction to Microsoft’s Hadoop solution (HDInsight)
Introduction to Microsoft’s Hadoop solution (HDInsight)
James Serra
Presentation from Data Science Conference 2.0 held in Belgrade, Serbia. The focus of the talk was to address the challenges of deploying a Data Lake infrastructure within the organization.
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Planing and optimizing data lake architecture
Milos Milovanovic
Azure Big Data
Prague data management meetup 2018-03-27
Prague data management meetup 2018-03-27
Martin Bém
Azure Data Lake Intro (SQLBits 2016 ADL/USQL Pre-Conference) Data Lake concept, Azure Data Lake, HDINSIGHT, Azure Data Lake Storage and Analytics
Azure Data Lake Intro (SQLBits 2016)
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Kishore Chaganti
Tired of seeing the loading spinner of doom while trying to analyze your big data on Tableau? Learn how Jethro accelerates your database so you can interactively analyze your big data on Tableau and gain the crucial insights that you need without losing your train of thought. Jethro enables you to be completely flexible with no need for partitions in order to speed up the data. This presentation will explain how indexing is a superior architecture for the BI use case when dealing with big data while compared to MPP architecture.
Jethro for tableau webinar (11 15)
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Remy Rosenbaum
Talk by Joe Atkins-Turkish at Brex on why Brex chose Amundsen and their recent addition of Looker integration to Amundsen on November 5, 2020.
Amundsen at Brex and Looker integration
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markgrover
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From discovering to trusting data
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Dipping Your Toes: Azure Data Lake for DBAs
RDX Insights Presentation - Microsoft Business Intelligence
RDX Insights Presentation - Microsoft Business Intelligence
Schema-on-Read vs Schema-on-Write
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Enkitec E4 Barcelona : SQL and Data Integration Futures on Hadoop :
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Azure Lowlands: An intro to Azure Data Lake
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Oracle BI Hybrid BI : Mode 1 + Mode 2, Cloud + On-Premise Business Analytics
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Prague data management meetup 2018-03-27
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Product overview for the All Access Suite of indexing and OneBox connectors for the Google Search Appliance by Adhere Solutions. www.adheresolutions.com Adhere Solutions is a Google Enterprise Partner providing products and services that help organizations accelerate their adoption of Google technologies and cloud computing. Adhere's team of consultants help customers leverage Google's Enterprise Search products, Google Maps, and Google Apps to improve access to information, productivity, and collaboration.
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User-Driven Taxonomies
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Presented by John Kreisa at Web Content Chicago, June 17-18, 2008. The combination of XML and XQuery provided by XML Content Servers are helping organizations become more agile with their content and enabling them to dynamically deliver a wide range of content in context to the web. In this session you'll learn about some of the key technical drivers behind XML Content Servers including a review of live customer deployments where agility was a key to success.
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ePADD is a software package developed by Stanford University's Special Collections & University Archives that supports archival processes around the appraisal, ingest, processing, discovery, and delivery of email archives.
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Extensible Python: Robustness through Addition - PyCon 2024
Patrick Viafore
Are you wondering why everyone is talking about the Flutterwave scandal? You’re not alone! It’s been in the news a lot. We’re going to tell you all about the Flutterwave Scandal in a way that’s easy to get. Keep reading, because we’re going to share the whole story with you. The company Flutterwave is headquartered in San Francisco, California, United States. In 2016, Iyinoluwa Aboyeji, Olugbenga Agboola, and Adeleke Adekoya established Flutterwave. It offers a payment infrastructure to international merchants and payment service providers throughout Africa. The company operates in various African countries including Nigeria, Kenya, Uganda, Ghana, South Africa, and others. They focus on digital payments, helping businesses accept and process payments on various channels like the web, mobile, ATM, and POS. Recently, they’ve been in the news due to allegations of misconduct within the company, which has affected their reputation and value. Flutterwave is an essential player in the African fintech landscape, aiming to drive growth for banks and businesses through digital payment solutions. The Flutterwave scandal involves allegations of misconduct and inappropriate behaviour towards female employees by the company’s co-founder and CEO, Olugbenga Agboola. Reports have surfaced from both current and former employees about bullying, intimidation, and sexual harassment at work. The allegations of inappropriate behaviour towards female employees at Flutterwave, specifically involving the CEO Olugbenga Agboola, were brought to public attention in April 2022.This was when Clara Wanjiku Odero, an ex-employee and current CEO of Credrails, published a Medium post and a series of tweets on April 4, 2022, accusing Flutterwave and Agboola of bullying. These allegations were part of a broader range of misconduct claims that surfaced around the same time The reasons behind the scandal are rooted in accusations of unethical behavior within the company. The allegations suggest a workplace culture that allowed for misconduct and failed to protect employees from harassment and intimidation. Specifically, the Flutterwave scandal refers to the series of events where the CEO was accused of engaging in improper conduct with female colleagues. This led to a broader investigation into the company’s practices and raised serious concerns about the fintech’s corporate governance. The scandal had significant repercussions, including a drop in the company’s stock price and a loss of trust among customers and partners. The trust that customers and investors had in Flutterwave was greatly damaged. People started to doubt the company’s integrity and whether their money and personal information were safe. Market Impact The scandal shook the entire fintech market. Flutterwave’s competitors saw this as an opportunity and started to attract customers who were leaving Flutterwave.
Breaking Down the Flutterwave Scandal What You Need to Know.pdf
Breaking Down the Flutterwave Scandal What You Need to Know.pdf
UK Journal
We start by setting up a common ground introducing why relational databases fall short, addressing common EDA characteristics such as the need for real-time response times and schemaless approaches to address recurring changes to adapt and on-board new use cases. Next, interact with a sample Rust-based application: a social network app demonstrating an integration of both ScyllaDB and Redpanda.
Event-Driven Architecture Masterclass: Integrating Distributed Data Stores Ac...
Event-Driven Architecture Masterclass: Integrating Distributed Data Stores Ac...
ScyllaDB
Delivered by Michael Down at Gartner Data & Analytics Summit London 2024 - Your enemies use GenAI too: Staying ahead of fraud with Neo4j. Fraudsters exploit the latest technologies like generative AI to stay undetected. Static applications can’t adapt quickly enough. Learn why you should build flexible fraud detection apps on Neo4j’s native graph database combined with advanced data science algorithms. Uncover complex fraud patterns in real-time and shut down schemes before they cause damage.
Your enemies use GenAI too - staying ahead of fraud with Neo4j
Your enemies use GenAI too - staying ahead of fraud with Neo4j
Neo4j
At Skynet Technologies, our team of accessibility experts performs automated, semi-automated, and manual audits of websites and web applications as per WCAG 2.2 level AA, ADA, and section 508. Based on evaluations of the accessibility compliance level of the website’s UI, design, source code, navigation, interactive elements, and overall usability, we will provide a digital accessibility evaluation report with in-depth details of potential accessibility barriers and remediation recommendations. Get a manual website WCAG audit (2.0, 2.1, 2.2 level AA) for a small website: 10 pages: $2,500 within 7 business days 30 pages: $7,500 within 14 business days 50 pages: $12,500 within 28 business days For medium websites: 100 pages: $25,000 within 6 weeks For larger websites or audits of all pages, please reach out hello@skynettechnologies.com.
Human Expert Website Manual WCAG 2.0 2.1 2.2 Audit - Digital Accessibility Au...
Human Expert Website Manual WCAG 2.0 2.1 2.2 Audit - Digital Accessibility Au...
Skynet Technologies
FIDO Seminar RSAC 2024
Introduction to FIDO Authentication and Passkeys.pptx
Introduction to FIDO Authentication and Passkeys.pptx
FIDO Alliance
Discuss the core tradeoffs and considerations involved in order-free and ordered stream processing. Brian Taylor walks through the pros and cons of three different approaches: no data dependency, deferred inter-event data dependency, and streaming inter-event data dependency.
Event-Driven Architecture Masterclass: Challenges in Stream Processing
Event-Driven Architecture Masterclass: Challenges in Stream Processing
ScyllaDB
Portal Kombat : extension du réseau de propagande russe
Portal Kombat : extension du réseau de propagande russe
Portal Kombat : extension du réseau de propagande russe
中 央社
FIDO Seminar RSAC 2024
Tales from a Passkey Provider Progress from Awareness to Implementation.pptx
Tales from a Passkey Provider Progress from Awareness to Implementation.pptx
FIDO Alliance
FIDO Taipei Workshop: Securing the Edge with FDO
Choosing the Right FDO Deployment Model for Your Application _ Geoffrey at In...
Choosing the Right FDO Deployment Model for Your Application _ Geoffrey at In...
FIDO Alliance
Artificial Intelligence is referred to as machine intelligence, and it is rooted in binary codes and mathematical algorithms. It is a testament to human creativity and is capable of massive data processing, pattern recognition, and even self-learning. However, the realm of AI realm is confined.
AI mind or machine power point presentation
AI mind or machine power point presentation
yogeshlabana357357
Question de pré-engagement à remplir !
Microsoft CSP Briefing Pre-Engagement - Questionnaire
Microsoft CSP Briefing Pre-Engagement - Questionnaire
Exakis Nelite
FIDO Taipei Workshop: Securing the Edge with FDO
Introduction to FDO and How It works Applications _ Richard at FIDO Alliance.pdf
Introduction to FDO and How It works Applications _ Richard at FIDO Alliance.pdf
FIDO Alliance
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FDO for Camera, Sensor and Networking Device – Commercial Solutions from VinC...
FDO for Camera, Sensor and Networking Device – Commercial Solutions from VinC...
FIDO Alliance
FIDO Seminar RSAC 2024
Harnessing Passkeys in the Battle Against AI-Powered Cyber Threats.pptx
Harnessing Passkeys in the Battle Against AI-Powered Cyber Threats.pptx
FIDO Alliance
FIDO Seminar RSAC 2024
ADP Passwordless Journey Case Study.pptx
ADP Passwordless Journey Case Study.pptx
FIDO Alliance
Learn about the basics of OAuth 2.0 and the different OAuth flows in this introductory video. Understand how OAuth works and the various authorization mechanisms involved.
Oauth 2.0 Introduction and Flows with MuleSoft
Oauth 2.0 Introduction and Flows with MuleSoft
shyamraj55
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ASRock Industrial FDO Solutions in Action for Industrial Edge AI _ Kenny at A...
ASRock Industrial FDO Solutions in Action for Industrial Edge AI _ Kenny at A...
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Intro to Passkeys and the State of Passwordless.pptx
Simplified FDO Manufacturing Flow with TPMs _ Liam at Infineon.pdf
Simplified FDO Manufacturing Flow with TPMs _ Liam at Infineon.pdf
Extensible Python: Robustness through Addition - PyCon 2024
Extensible Python: Robustness through Addition - PyCon 2024
Breaking Down the Flutterwave Scandal What You Need to Know.pdf
Breaking Down the Flutterwave Scandal What You Need to Know.pdf
Event-Driven Architecture Masterclass: Integrating Distributed Data Stores Ac...
Event-Driven Architecture Masterclass: Integrating Distributed Data Stores Ac...
Your enemies use GenAI too - staying ahead of fraud with Neo4j
Your enemies use GenAI too - staying ahead of fraud with Neo4j
Human Expert Website Manual WCAG 2.0 2.1 2.2 Audit - Digital Accessibility Au...
Human Expert Website Manual WCAG 2.0 2.1 2.2 Audit - Digital Accessibility Au...
Introduction to FIDO Authentication and Passkeys.pptx
Introduction to FIDO Authentication and Passkeys.pptx
Event-Driven Architecture Masterclass: Challenges in Stream Processing
Event-Driven Architecture Masterclass: Challenges in Stream Processing
Portal Kombat : extension du réseau de propagande russe
Portal Kombat : extension du réseau de propagande russe
Tales from a Passkey Provider Progress from Awareness to Implementation.pptx
Tales from a Passkey Provider Progress from Awareness to Implementation.pptx
Choosing the Right FDO Deployment Model for Your Application _ Geoffrey at In...
Choosing the Right FDO Deployment Model for Your Application _ Geoffrey at In...
AI mind or machine power point presentation
AI mind or machine power point presentation
Microsoft CSP Briefing Pre-Engagement - Questionnaire
Microsoft CSP Briefing Pre-Engagement - Questionnaire
Introduction to FDO and How It works Applications _ Richard at FIDO Alliance.pdf
Introduction to FDO and How It works Applications _ Richard at FIDO Alliance.pdf
FDO for Camera, Sensor and Networking Device – Commercial Solutions from VinC...
FDO for Camera, Sensor and Networking Device – Commercial Solutions from VinC...
Harnessing Passkeys in the Battle Against AI-Powered Cyber Threats.pptx
Harnessing Passkeys in the Battle Against AI-Powered Cyber Threats.pptx
ADP Passwordless Journey Case Study.pptx
ADP Passwordless Journey Case Study.pptx
Oauth 2.0 Introduction and Flows with MuleSoft
Oauth 2.0 Introduction and Flows with MuleSoft
KnowIT, semantic informatics knowledge base
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knowIT Mapping out
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Under the hood
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