The document discusses challenges with data-driven cloud modernization and how the Denodo platform can help address them. It outlines Denodo's capabilities like universal connectivity, data services APIs, security and governance features. Example use cases are presented around real-time analytics, centralized access control and transitioning to the cloud. Key benefits of the Denodo data virtualization approach are that it provides a logical view of data across sources and enables self-service analytics while reducing costs and IT dependencies.
Introduction to Snowflake Datawarehouse and Architecture for Big data company. Centralized data management. Snowpipe and Copy into a command for data loading. Stream loading and Batch Processing.
Wonder what this data mesh stuff is all about? What are the principles of data mesh? Can you or should you consider data mesh as the approach for your analytics platform? And most important - how can Snowflake help?
Given in Montreal on 14-Dec-2021
Data Catalog as the Platform for Data IntelligenceAlation
Data catalogs are in wide use today across hundreds of enterprises as a means to help data scientists and business analysts find and collaboratively analyze data. Over the past several years, customers have increasingly used data catalogs in applications beyond their search & discovery roots, addressing new use cases such as data governance, cloud data migration, and digital transformation. In this session, the founder and CEO of Alation will discuss the evolution of the data catalog, the many ways in which data catalogs are being used today, the importance of machine learning in data catalogs, and discuss the future of the data catalog as a platform for a broad range of data intelligence solutions.
On-premise to Microsoft Azure Cloud Migration.Emtec Inc.
This presentation sheds light on migrating on-premise apps to Microsoft Azure cloud. It also highlights the technical capabilities of Microsoft Azure cloud services.
Describes what Enterprise Data Architecture in a Software Development Organization should cover and does that by listing over 200 data architecture related deliverables an Enterprise Data Architect should remember to evangelize.
NEW LAUNCH! Amazon Neptune Overview and Customer Use Cases - DAT319 - re:Inve...Amazon Web Services
In this session, we will provide an overview of Amazon Neptune, AWS’s newest database service. Amazon Neptune is a fast, reliable graph database that makes it easy to build applications over highly connected data. We will then explore how Siemens is building a knowledge using Amazon Neptune.
Introduction to Snowflake Datawarehouse and Architecture for Big data company. Centralized data management. Snowpipe and Copy into a command for data loading. Stream loading and Batch Processing.
Wonder what this data mesh stuff is all about? What are the principles of data mesh? Can you or should you consider data mesh as the approach for your analytics platform? And most important - how can Snowflake help?
Given in Montreal on 14-Dec-2021
Data Catalog as the Platform for Data IntelligenceAlation
Data catalogs are in wide use today across hundreds of enterprises as a means to help data scientists and business analysts find and collaboratively analyze data. Over the past several years, customers have increasingly used data catalogs in applications beyond their search & discovery roots, addressing new use cases such as data governance, cloud data migration, and digital transformation. In this session, the founder and CEO of Alation will discuss the evolution of the data catalog, the many ways in which data catalogs are being used today, the importance of machine learning in data catalogs, and discuss the future of the data catalog as a platform for a broad range of data intelligence solutions.
On-premise to Microsoft Azure Cloud Migration.Emtec Inc.
This presentation sheds light on migrating on-premise apps to Microsoft Azure cloud. It also highlights the technical capabilities of Microsoft Azure cloud services.
Describes what Enterprise Data Architecture in a Software Development Organization should cover and does that by listing over 200 data architecture related deliverables an Enterprise Data Architect should remember to evangelize.
NEW LAUNCH! Amazon Neptune Overview and Customer Use Cases - DAT319 - re:Inve...Amazon Web Services
In this session, we will provide an overview of Amazon Neptune, AWS’s newest database service. Amazon Neptune is a fast, reliable graph database that makes it easy to build applications over highly connected data. We will then explore how Siemens is building a knowledge using Amazon Neptune.
GSS America\'s Workplace Services aim at equipping customer’s business with round-the-clock support, through its Global Operations Command Center (GOCC). Its comprehensive range of workplace services gives customers the ability to reduce their costs and improve their service levels. GSS intends to help global enterprises cut down on their infrastructure maintenance costs and provide access to expert skills.
Come costruire servizi di Forecasting sfruttando algoritmi di ML e deep learn...Amazon Web Services
Il Forecasting è un processo importante per tantissime aziende e viene utilizzato in vari ambiti per cercare di prevedere in modo accurato la crescita e distribuzione di un prodotto, l’utilizzo delle risorse necessarie nelle linee produttive, presentazioni finanziarie e tanto altro. Amazon utilizza delle tecniche avanzate di forecasting, in parte questi servizi sono stati messi a disposizione di tutti i clienti AWS.
In questa sessione illustreremo come pre-processare i dati che contengono una componente temporale e successivamente utilizzare un algoritmo che a partire dal tipo di dato analizzato produce un forecasting accurato.
This is Part 4 of the GoldenGate series on Data Mesh - a series of webinars helping customers understand how to move off of old-fashioned monolithic data integration architecture and get ready for more agile, cost-effective, event-driven solutions. The Data Mesh is a kind of Data Fabric that emphasizes business-led data products running on event-driven streaming architectures, serverless, and microservices based platforms. These emerging solutions are essential for enterprises that run data-driven services on multi-cloud, multi-vendor ecosystems.
Join this session to get a fresh look at Data Mesh; we'll start with core architecture principles (vendor agnostic) and transition into detailed examples of how Oracle's GoldenGate platform is providing capabilities today. We will discuss essential technical characteristics of a Data Mesh solution, and the benefits that business owners can expect by moving IT in this direction. For more background on Data Mesh, Part 1, 2, and 3 are on the GoldenGate YouTube channel: https://www.youtube.com/playlist?list=PLbqmhpwYrlZJ-583p3KQGDAd6038i1ywe
Webinar Speaker: Jeff Pollock, VP Product (https://www.linkedin.com/in/jtpollock/)
Mr. Pollock is an expert technology leader for data platforms, big data, data integration and governance. Jeff has been CTO at California startups and a senior exec at Fortune 100 tech vendors. He is currently Oracle VP of Products and Cloud Services for Data Replication, Streaming Data and Database Migrations. While at IBM, he was head of all Information Integration, Replication and Governance products, and previously Jeff was an independent architect for US Defense Department, VP of Technology at Cerebra and CTO of Modulant – he has been engineering artificial intelligence based data platforms since 2001. As a business consultant, Mr. Pollock was a Head Architect at Ernst & Young’s Center for Technology Enablement. Jeff is also the author of “Semantic Web for Dummies” and "Adaptive Information,” a frequent keynote at industry conferences, author for books and industry journals, formerly a contributing member of W3C and OASIS, and an engineering instructor with UC Berkeley’s Extension for object-oriented systems, software development process and enterprise architecture.
Modernizing to a Cloud Data ArchitectureDatabricks
Organizations with on-premises Hadoop infrastructure are bogged down by system complexity, unscalable infrastructure, and the increasing burden on DevOps to manage legacy architectures. Costs and resource utilization continue to go up while innovation has flatlined. In this session, you will learn why, now more than ever, enterprises are looking for cloud alternatives to Hadoop and are migrating off of the architecture in large numbers. You will also learn how elastic compute models’ benefits help one customer scale their analytics and AI workloads and best practices from their experience on a successful migration of their data and workloads to the cloud.
The Path to Data and Analytics ModernizationAnalytics8
Learn about the business demands driving modernization, the benefits of doing so, and how to get started.
Can your data and analytics solutions handle today’s challenges?
To stay competitive in today’s market, companies must be able to use their data to make better decisions. However, we are living in a world flooded by data, new technologies, and demands from the business for better and more advanced analytics. Most companies do not have the modern technologies and processes in place to keep up with these growing demands. They need to modernize how they collect, analyze, use, and share their data.
In this webinar, we discuss how you can build modern data and analytics solutions that are future ready, scalable, real-time, high speed, and agile and that can enable better use of data throughout your company.
We cover:
-The business demands and industry shifts that are impacting the need to modernize
-The benefits of data and analytics modernization
-How to approach data and analytics modernization- steps you need to take and how to get it right
-The pillars of modern data management
-Tips for migrating from legacy analytics tools to modern, next-gen platforms
-Lessons learned from companies that have gone through the modernization process
Accelerate your Cloud Migration Journey (Level 100)
Many enterprises have realized the benefits of migrating services to the cloud and are considering the next stage in their journey. In this webinar we will take you through the principles of cloud migration including the business benefits, cloud economics, methodologies and tools to accelerate your journey. We will also discuss the key enablers for cloud adoption based on real examples.
This is a Level 100 webinar
Speakers: Manav Prabhakar, Practice Manager, AWS Professional Services
Jon Austin, Principal Solutions Architect, Amazon Web Services
Parijat Mishra, Solutions Architect Manager, Amazon Web Services
Why Do Banks Need A Customer Data Platform?Lemnisk
Banks traditionally have been known to amass customer information across both online and offline data channels. However, a lot of this data resides in silos and marketers have been unable to leverage this data to run targeted marketing campaigns. Here are the top four reasons why a Customer Data Platform would be best suited for Banks.
Cloud First does not mean you should jump into cloud without a well-constructed plan. The most successful organizations build the foundational capabilities first and create a roadmap that aligns people, technology, platforms, security, governance and culture. Many CIO’s want the benefits associated with cloud technologies but don’t necessarily know where to start and what questions to ask. This session will provide real world examples of the transformation process, challenges and successes that organizations have experienced in their cloud journey. We will define a low risk strategy and approach to achieve success in the cloud quickly. We will describe the sequencing requirements, milestones, and foundational services that need to be in place on Day 1. And finally, we will reveal the most critical and often overlooked component of your transformation strategy. Sponsored by Smartronix.
Customers migrating workloads to AWS have a variety of tools to monitor their infrastructure, generating large volumes of alarms from services such as Amazon CloudWatch, AWS Config, and other third party tools. Without careful curation, events and tickets can exponentially multiply and overwhelm ITSM systems and the teams operating them, obscuring real problems and wasting time. Using advanced Machine Learning techniques, customers can reduce noise from these events and tickets and increase their service quality. In this presentation, we explore challengs of adopting AIOps, and provide examples of how AIOPs can be used to reduce Mean Time To Restore and improve customer outcomes
Open Digital Architecture (ODA) is a blueprint for modular, cloud-based, open digital platforms that can be orchestrated using AI.
Designed to support our industry into the cloud native era, ODA sets the framework required
for CSPs to invest in IT, transforming business agility and operations by creating simpler IT and network solutions that are easier and cheaper to deploy, integrate and upgrade. Enabling growth, profitability and a cutting-edge customer experience.
In this session, Sergio covered the Lakehouse concept and how companies implement it, from data ingestion to insight. He showed how you could use Azure Data Services to speed up your Analytics project from ingesting, modelling and delivering insights to end users.
This describes a conceptual model approach to designing an enterprise data fabric. This is the set of hardware and software infrastructure, tools and facilities to implement, administer, manage and operate data operations across the entire span of the data within the enterprise across all data activities including data acquisition, transformation, storage, distribution, integration, replication, availability, security, protection, disaster recovery, presentation, analytics, preservation, retention, backup, retrieval, archival, recall, deletion, monitoring, capacity planning across all data storage platforms enabling use by applications to meet the data needs of the enterprise.
The conceptual data fabric model represents a rich picture of the enterprise’s data context. It embodies an idealised and target data view.
Designing a data fabric enables the enterprise respond to and take advantage of key related data trends:
• Internal and External Digital Expectations
• Cloud Offerings and Services
• Data Regulations
• Analytics Capabilities
It enables the IT function demonstrate positive data leadership. It shows the IT function is able and willing to respond to business data needs. It allows the enterprise to meet data challenges
• More and more data of many different types
• Increasingly distributed platform landscape
• Compliance and regulation
• Newer data technologies
• Shadow IT where the IT function cannot deliver IT change and new data facilities quickly
It is concerned with the design an open and flexible data fabric that improves the responsiveness of the IT function and reduces shadow IT.
Slides for the talk at AI in Production meetup:
https://www.meetup.com/LearnDataScience/events/255723555/
Abstract: Demystifying Data Engineering
With recent progress in the fields of big data analytics and machine learning, Data Engineering is an emerging discipline which is not well-defined and often poorly understood.
In this talk, we aim to explain Data Engineering, its role in Data Science, the difference between a Data Scientist and a Data Engineer, the role of a Data Engineer and common concepts as well as commonly misunderstood ones found in Data Engineering. Toward the end of the talk, we will examine a typical Data Analytics system architecture.
Modern Data Management for Federal ModernizationDenodo
Watch full webinar here: https://bit.ly/2QaVfE7
Faster, more agile data management is at the heart of government modernization. However, Traditional data delivery systems are limited in realizing a modernized and future-proof data architecture.
This webinar will address how data virtualization can modernize existing systems and enable new data strategies. Join this session to learn how government agencies can use data virtualization to:
- Enable governed, inter-agency data sharing
- Simplify data acquisition, search and tagging
- Streamline data delivery for transition to cloud, data science initiatives, and more
Denodo Partner Connect: A Review of the Top 5 Differentiated Use Cases for th...Denodo
Watch full webinar here: https://buff.ly/46pRfV7
This Denodo session explores the power of data virtualization, shedding light on its architecture, customer value, and a diverse range of use cases. Attendees will discover how the Denodo Platform enables seamless connectivity to various data sources while effortlessly combining, cleansing, and delivering data through 5 differentiated use cases.
Architecture: Delve into the core architecture of the Denodo Platform and learn how it empowers organizations to create a unified virtual data layer. Understand how data is accessed, integrated, and delivered in a real-time, agile manner.
Value for the Customer: Explore the tangible benefits that Denodo offers to its customers. From cost savings to improved decision-making, discover how the Denodo Platform helps organizations derive maximum value from their data assets.
Five Different Use Cases: Uncover five real-world use cases where Denodo's data virtualization platform has made a significant impact. From data governance to analytics, Denodo proves its versatility across a variety of domains.
- Logical Data Fabric
- Self Service Analytics
- Data Governance
- 360 degree of Entities
- Hybrid/Multi-Cloud Integration
Watch this illuminating session to gain insights into the transformative capabilities of the Denodo Platform.
GSS America\'s Workplace Services aim at equipping customer’s business with round-the-clock support, through its Global Operations Command Center (GOCC). Its comprehensive range of workplace services gives customers the ability to reduce their costs and improve their service levels. GSS intends to help global enterprises cut down on their infrastructure maintenance costs and provide access to expert skills.
Come costruire servizi di Forecasting sfruttando algoritmi di ML e deep learn...Amazon Web Services
Il Forecasting è un processo importante per tantissime aziende e viene utilizzato in vari ambiti per cercare di prevedere in modo accurato la crescita e distribuzione di un prodotto, l’utilizzo delle risorse necessarie nelle linee produttive, presentazioni finanziarie e tanto altro. Amazon utilizza delle tecniche avanzate di forecasting, in parte questi servizi sono stati messi a disposizione di tutti i clienti AWS.
In questa sessione illustreremo come pre-processare i dati che contengono una componente temporale e successivamente utilizzare un algoritmo che a partire dal tipo di dato analizzato produce un forecasting accurato.
This is Part 4 of the GoldenGate series on Data Mesh - a series of webinars helping customers understand how to move off of old-fashioned monolithic data integration architecture and get ready for more agile, cost-effective, event-driven solutions. The Data Mesh is a kind of Data Fabric that emphasizes business-led data products running on event-driven streaming architectures, serverless, and microservices based platforms. These emerging solutions are essential for enterprises that run data-driven services on multi-cloud, multi-vendor ecosystems.
Join this session to get a fresh look at Data Mesh; we'll start with core architecture principles (vendor agnostic) and transition into detailed examples of how Oracle's GoldenGate platform is providing capabilities today. We will discuss essential technical characteristics of a Data Mesh solution, and the benefits that business owners can expect by moving IT in this direction. For more background on Data Mesh, Part 1, 2, and 3 are on the GoldenGate YouTube channel: https://www.youtube.com/playlist?list=PLbqmhpwYrlZJ-583p3KQGDAd6038i1ywe
Webinar Speaker: Jeff Pollock, VP Product (https://www.linkedin.com/in/jtpollock/)
Mr. Pollock is an expert technology leader for data platforms, big data, data integration and governance. Jeff has been CTO at California startups and a senior exec at Fortune 100 tech vendors. He is currently Oracle VP of Products and Cloud Services for Data Replication, Streaming Data and Database Migrations. While at IBM, he was head of all Information Integration, Replication and Governance products, and previously Jeff was an independent architect for US Defense Department, VP of Technology at Cerebra and CTO of Modulant – he has been engineering artificial intelligence based data platforms since 2001. As a business consultant, Mr. Pollock was a Head Architect at Ernst & Young’s Center for Technology Enablement. Jeff is also the author of “Semantic Web for Dummies” and "Adaptive Information,” a frequent keynote at industry conferences, author for books and industry journals, formerly a contributing member of W3C and OASIS, and an engineering instructor with UC Berkeley’s Extension for object-oriented systems, software development process and enterprise architecture.
Modernizing to a Cloud Data ArchitectureDatabricks
Organizations with on-premises Hadoop infrastructure are bogged down by system complexity, unscalable infrastructure, and the increasing burden on DevOps to manage legacy architectures. Costs and resource utilization continue to go up while innovation has flatlined. In this session, you will learn why, now more than ever, enterprises are looking for cloud alternatives to Hadoop and are migrating off of the architecture in large numbers. You will also learn how elastic compute models’ benefits help one customer scale their analytics and AI workloads and best practices from their experience on a successful migration of their data and workloads to the cloud.
The Path to Data and Analytics ModernizationAnalytics8
Learn about the business demands driving modernization, the benefits of doing so, and how to get started.
Can your data and analytics solutions handle today’s challenges?
To stay competitive in today’s market, companies must be able to use their data to make better decisions. However, we are living in a world flooded by data, new technologies, and demands from the business for better and more advanced analytics. Most companies do not have the modern technologies and processes in place to keep up with these growing demands. They need to modernize how they collect, analyze, use, and share their data.
In this webinar, we discuss how you can build modern data and analytics solutions that are future ready, scalable, real-time, high speed, and agile and that can enable better use of data throughout your company.
We cover:
-The business demands and industry shifts that are impacting the need to modernize
-The benefits of data and analytics modernization
-How to approach data and analytics modernization- steps you need to take and how to get it right
-The pillars of modern data management
-Tips for migrating from legacy analytics tools to modern, next-gen platforms
-Lessons learned from companies that have gone through the modernization process
Accelerate your Cloud Migration Journey (Level 100)
Many enterprises have realized the benefits of migrating services to the cloud and are considering the next stage in their journey. In this webinar we will take you through the principles of cloud migration including the business benefits, cloud economics, methodologies and tools to accelerate your journey. We will also discuss the key enablers for cloud adoption based on real examples.
This is a Level 100 webinar
Speakers: Manav Prabhakar, Practice Manager, AWS Professional Services
Jon Austin, Principal Solutions Architect, Amazon Web Services
Parijat Mishra, Solutions Architect Manager, Amazon Web Services
Why Do Banks Need A Customer Data Platform?Lemnisk
Banks traditionally have been known to amass customer information across both online and offline data channels. However, a lot of this data resides in silos and marketers have been unable to leverage this data to run targeted marketing campaigns. Here are the top four reasons why a Customer Data Platform would be best suited for Banks.
Cloud First does not mean you should jump into cloud without a well-constructed plan. The most successful organizations build the foundational capabilities first and create a roadmap that aligns people, technology, platforms, security, governance and culture. Many CIO’s want the benefits associated with cloud technologies but don’t necessarily know where to start and what questions to ask. This session will provide real world examples of the transformation process, challenges and successes that organizations have experienced in their cloud journey. We will define a low risk strategy and approach to achieve success in the cloud quickly. We will describe the sequencing requirements, milestones, and foundational services that need to be in place on Day 1. And finally, we will reveal the most critical and often overlooked component of your transformation strategy. Sponsored by Smartronix.
Customers migrating workloads to AWS have a variety of tools to monitor their infrastructure, generating large volumes of alarms from services such as Amazon CloudWatch, AWS Config, and other third party tools. Without careful curation, events and tickets can exponentially multiply and overwhelm ITSM systems and the teams operating them, obscuring real problems and wasting time. Using advanced Machine Learning techniques, customers can reduce noise from these events and tickets and increase their service quality. In this presentation, we explore challengs of adopting AIOps, and provide examples of how AIOPs can be used to reduce Mean Time To Restore and improve customer outcomes
Open Digital Architecture (ODA) is a blueprint for modular, cloud-based, open digital platforms that can be orchestrated using AI.
Designed to support our industry into the cloud native era, ODA sets the framework required
for CSPs to invest in IT, transforming business agility and operations by creating simpler IT and network solutions that are easier and cheaper to deploy, integrate and upgrade. Enabling growth, profitability and a cutting-edge customer experience.
In this session, Sergio covered the Lakehouse concept and how companies implement it, from data ingestion to insight. He showed how you could use Azure Data Services to speed up your Analytics project from ingesting, modelling and delivering insights to end users.
This describes a conceptual model approach to designing an enterprise data fabric. This is the set of hardware and software infrastructure, tools and facilities to implement, administer, manage and operate data operations across the entire span of the data within the enterprise across all data activities including data acquisition, transformation, storage, distribution, integration, replication, availability, security, protection, disaster recovery, presentation, analytics, preservation, retention, backup, retrieval, archival, recall, deletion, monitoring, capacity planning across all data storage platforms enabling use by applications to meet the data needs of the enterprise.
The conceptual data fabric model represents a rich picture of the enterprise’s data context. It embodies an idealised and target data view.
Designing a data fabric enables the enterprise respond to and take advantage of key related data trends:
• Internal and External Digital Expectations
• Cloud Offerings and Services
• Data Regulations
• Analytics Capabilities
It enables the IT function demonstrate positive data leadership. It shows the IT function is able and willing to respond to business data needs. It allows the enterprise to meet data challenges
• More and more data of many different types
• Increasingly distributed platform landscape
• Compliance and regulation
• Newer data technologies
• Shadow IT where the IT function cannot deliver IT change and new data facilities quickly
It is concerned with the design an open and flexible data fabric that improves the responsiveness of the IT function and reduces shadow IT.
Slides for the talk at AI in Production meetup:
https://www.meetup.com/LearnDataScience/events/255723555/
Abstract: Demystifying Data Engineering
With recent progress in the fields of big data analytics and machine learning, Data Engineering is an emerging discipline which is not well-defined and often poorly understood.
In this talk, we aim to explain Data Engineering, its role in Data Science, the difference between a Data Scientist and a Data Engineer, the role of a Data Engineer and common concepts as well as commonly misunderstood ones found in Data Engineering. Toward the end of the talk, we will examine a typical Data Analytics system architecture.
Modern Data Management for Federal ModernizationDenodo
Watch full webinar here: https://bit.ly/2QaVfE7
Faster, more agile data management is at the heart of government modernization. However, Traditional data delivery systems are limited in realizing a modernized and future-proof data architecture.
This webinar will address how data virtualization can modernize existing systems and enable new data strategies. Join this session to learn how government agencies can use data virtualization to:
- Enable governed, inter-agency data sharing
- Simplify data acquisition, search and tagging
- Streamline data delivery for transition to cloud, data science initiatives, and more
Denodo Partner Connect: A Review of the Top 5 Differentiated Use Cases for th...Denodo
Watch full webinar here: https://buff.ly/46pRfV7
This Denodo session explores the power of data virtualization, shedding light on its architecture, customer value, and a diverse range of use cases. Attendees will discover how the Denodo Platform enables seamless connectivity to various data sources while effortlessly combining, cleansing, and delivering data through 5 differentiated use cases.
Architecture: Delve into the core architecture of the Denodo Platform and learn how it empowers organizations to create a unified virtual data layer. Understand how data is accessed, integrated, and delivered in a real-time, agile manner.
Value for the Customer: Explore the tangible benefits that Denodo offers to its customers. From cost savings to improved decision-making, discover how the Denodo Platform helps organizations derive maximum value from their data assets.
Five Different Use Cases: Uncover five real-world use cases where Denodo's data virtualization platform has made a significant impact. From data governance to analytics, Denodo proves its versatility across a variety of domains.
- Logical Data Fabric
- Self Service Analytics
- Data Governance
- 360 degree of Entities
- Hybrid/Multi-Cloud Integration
Watch this illuminating session to gain insights into the transformative capabilities of the Denodo Platform.
Simplifying Your Cloud Architecture with a Logical Data Fabric (APAC)Denodo
Watch full webinar here: https://bit.ly/3dudL6u
It's not if you move to the cloud, but when. Most organisations are well underway with migrating applications and data to the cloud. In fact, most organisations - whether they realise it or not - have a multi-cloud strategy. Single, hybrid, or multi-cloud…the potential benefits are huge - flexibility, agility, cost savings, scaling on-demand, etc. However, the challenges can be just as large and daunting. A poorly managed migration to the cloud can leave users frustrated at their inability to get to the data that they need and IT scrambling to cobble together a solution.
In this session, we will look at the challenges facing data management teams as they migrate to cloud and multi-cloud architectures. We will show how the Denodo Platform can:
- Reduce the risk and minimise the disruption of migrating to the cloud.
- Make it easier and quicker for users to find the data that they need - wherever it is located.
- Provide a uniform security layer that spans hybrid and multi-cloud environments.
Enabling Next Gen Analytics with Azure Data Lake and StreamSetsStreamsets Inc.
Big data and the cloud are perfect partners for companies who want to unlock maximum value from all of their unstructured, semi-structured, and structured data. The challenge has been how to create and manage a reliable end-to-end solution that spans data ingestion, storage and analysis in the face of the volume, velocity and variety of big data sources.
In this webinar, we will show you how to achieve big data bliss by combining StreamSets Data Collector, which specializes in creating and running complex any-to-any dataflows, with Microsoft's Azure Data Lake and Azure analytic solutions.
We will walk through an example of how a major bank is using StreamSets to transport their on-premise data to the Azure Cloud Computing Platform and Azure Data Lake to take advantage of analytics tools with unprecedented scale and performance.
Cloud Migration headache? Ease the pain with Data Virtualization! (EMEA)Denodo
Watch full webinar here: https://bit.ly/3CWIBzd
Moving data to the Cloud is a priority for many organizations. Benefits - in terms of flexibility, agility, and cost savings - are driving Cloud adoption. This journey to the Cloud is not easy: moving application(s) and data to the Cloud can be challenging and entails disruption of business, when not carefully managed.
When systems are being migrated, the resultant hybrid (or even multi-) Cloud architecture is, by definition, more complex AND making it harder/more costly to retrieve the data we need.
Data Virtualization can help organizations at all stages of a Cloud journey - during migration as well as in our “new hybrid multi-Cloud reality”
Watch on-demand this webinar to learn how Data Virtualization can:
- Help organizations manage risk and minimize the disruption caused as systems are moved to the Cloud
- Provide a single point of access for data that is both on-premise and in the Cloud, making it easier for users to find and access the data that they need
- Provide a secure layer to protect and manage data when it's distributed across hybrid or multi-Cloud architectures
… watch a live demo about how to ease the migration.
Data Virtualization: Introduction and Business Value (UK)Denodo
Watch full webinar here: https://bit.ly/30mHuYH
What started to evolve as the most agile and real-time enterprise data fabric, data virtualization is proving to go beyond its initial promise and is becoming one of the most important enterprise big data fabrics. Denodo’s vision is to provide a unified data delivery layer as a logical data fabric, to bridge the gap between the IT and the business, hiding the underlying complexity and creating a semantic layer to expose data in a business friendly manner.
Attend this webinar to learn:
- What data virtualization really is
- How it differs from other enterprise data integration technologies
- Why data virtualization is finding enterprise-wide deployment inside some of the largest organizations
- Business Value of data virtualization and customer use cases
- Highlights of the newly launched Denodo Platform 8.0
Data Services and the Modern Data Ecosystem (ASEAN)Denodo
Watch full webinar here: https://bit.ly/2YdstdU
Digital Transformation has changed IT the way information services are delivered. The pace of business engagement, the rise of Digital IT (formerly known as “Shadow IT), has also increased demands on IT, especially in the area of Data Management.
Data Services exploits widely adopted interoperability standards, providing a strong framework for information exchange but also has enabled growth of robust systems of engagement that can now exploit information that was normally locked away in some internal silo with Data Virtualization.
We will discuss how a business can easily support and manage a Data Service platform, providing a more flexible approach for information sharing supporting an ever-diverse community of consumers.
Watch this on-demand webinar as we cover:
- Why Data Services are a critical part of a modern data ecosystem
- How IT teams can manage Data Services and the increasing demand by businesses
- How Digital IT can benefit from Data Services and how this can support the need for rapid prototyping allowing businesses to experiment with data and fail fast where necessary
- How a good Data Virtualization platform can encourage a culture of Data amongst business consumers (internally and externally)
Best Practices in the Cloud for Data Management (US)Denodo
Watch here: https://bit.ly/2Npt82U
If you have data, you are engaged in data management—be sure to do it effectively.
As organizations are assessing how COVID-19 has impacted their operations, new possibilities and uncharted routes are becoming the norm for many businesses. While exploring and implementing different deployment and operational models, the question of data management naturally surfaces while considering how these changes impact your data. Is this the right time to focus on data management? The reality is that if you have data, you are engaged in data management and so the real question is, are you doing it well?
Join Brice Giesbrecht from Caserta and Mitesh Shah from Denodo to explore data management challenges and solutions facing data driven organizations.
Your Data is Waiting. What are the Top 5 Trends for Data in 2022? (ASEAN)Denodo
Watch full webinar here: https://bit.ly/3saONRK
COVID-19 has pushed every industry and organization to embrace digital transformation at scale, upending the way many businesses will operate for the foreseeable future. Organizations no longer tolerate monolithic and centralized data architecture; they are embracing flexibility, modularity, and distributed data architecture to help drive innovation and modernize processes.
The pandemic has compelled organizations to accelerate their digital transformation initiatives and look for smarter and more agile ways to manage and leverage their corporate data assets. Data governance has become challenging in the ever-increasing complexity and distributed nature of the data ecosystem. Interoperability, collaboration and trust in data are imperative for a business to succeed. Data needs to be easily accessible and fit for purpose.
In this session, Denodo experts will discuss 5 key trends that are expected to be top of mind for CIOs and CDOs;
- Distributed Data Environments
- Decision Intelligence
- Modern Data Architecture
- Composable Data & Analytics
- Hyper-personalized Experiences
Fast Data Strategy Houston Roadshow PresentationDenodo
Fast Data Strategy Houston Roadshow focused on the next industrial revolution on the horizon, driven by the application of big data, IoT and Cloud technologies.
• Denodo’s innovative customer, Anadarko, elaborated on how data virtualization serves as the key component in their prescriptive and predictive analytics initiatives, driven by multi-structured data ranging from customer data to equipment data.
• Denodo’s session, Unleashing the Power of Data, described the complexity of the modern data ecosystem and how to overcome challenges and successfully harness insights.
• Our Partner Noah Consulting, an expert analytics solutions provider in the energy industry, explained how your peers are innovating using new business models and reducing cost in areas such as Asset Management and Operations by leveraging Data Virtualization and Prescriptive and Predictive Analytics.
For more information on upcoming roadshows near you, follow this link: https://goo.gl/WBDHiE
Maximizing Oil and Gas (Data) Asset Utilization with a Logical Data Fabric (A...Denodo
Watch full webinar here: https://bit.ly/3g9PlQP
It is no news that Oil and Gas companies are constantly faced with immense pressure to stay competitive, especially in the current climate while striving towards becoming data-driven at the heart of the process to scale and gain greater operational efficiencies across the organization.
Hence, the need for a logical data layer to help Oil and Gas businesses move towards a unified secure and governed environment to optimize the potential of data assets across the enterprise efficiently and deliver real-time insights.
Tune in to this on-demand webinar where you will:
- Discover the role of data fabrics and Industry 4.0 in enabling smart fields
- Understand how to connect data assets and the associated value chain to high impact domain areas
- See examples of organizations accelerating time-to-value and reducing NPT
- Learn best practices for handling real-time/streaming/IoT data for analytical and operational use cases
Data Virtualization. An Introduction (ASEAN)Denodo
Watch full webinar here: https://bit.ly/3uiXVoC
What is Data Virtualization and why do I care? In this webinar we intend to help you understand not only what Data Virtualization is but why it's a critical component of any organization's data fabric and how it fits. How data virtualization liberates and empowers your business users via data discovery, data wrangling to generation of reusable reporting objects and data services. Digital transformation demands that we empower all consumers of data within the organization, it also demands agility too. Data Virtualization gives you meaningful access to information that can be shared by a myriad of consumers.
Watch on-demand this session to learn:
- What is Data Virtualization?
- Why do I need Data Virtualization in my organization?
- How do I implement Data Virtualization in my enterprise? Where does it fit..?
Multi-Cloud Integration with Data Virtualization (ASEAN)Denodo
Watch full webinar here: https://bit.ly/3corOL4
More and more organizations are adopting multi-cloud strategies to provide greater flexibility, cost savings, and performance optimization. Even when organizations commit to a single cloud provider, they often have data and applications spread across different cloud regions to support different business units or geographies. The result of this is a highly distributed infrastructure that makes finding and accessing the data needed for reporting and analytics even more challenging.
The Denodo Platform Multi-Location Architecture provides quick and easy managed access to data while still providing local control to the 'data owners' and complying with local privacy and data protection regulations (think GDPR and CCPA).
In this on-demand webinar, you will learn about:
- The challenges facing organizations as they adopt multi-cloud data strategies
- How the Denodo Platform provides a managed data access layer across the organization
- The different multi-location architectures that can maximize local control over data while still making it readily available
- How organizations have benefited from using the Denodo Platform as a multi-cloud data access layer
Virtualisation de données : Enjeux, Usages & BénéficesDenodo
Watch full webinar here: https://bit.ly/3oah4ng
Gartner a récemment qualifié la Data Virtualisation comme étant une pièce maitresse des architectures d’intégration de données.
Découvrez :
- Les bénéfices d’une plateforme de virtualisation de données
- La multiplication des usages : Lakehouse, Data Science, Big Data, Data Service & IoT
- La création d’une vue unifiée de votre patrimoine de données sans transiger sur la performance
- La construction d’une architecture d’intégration Agile des données : on-premise, dans le cloud ou hybride
DAMA & Denodo Webinar: Modernizing Data Architecture Using Data Virtualization Denodo
Watch here: https://bit.ly/2NGQD7R
In an era increasingly dominated by advancements in cloud computing, AI and advanced analytics it may come as a shock that many organizations still rely on data architectures built before the turn of the century. But that scenario is rapidly changing with the increasing adoption of real-time data virtualization - a paradigm shift in the approach that organizations take towards accessing, integrating, and provisioning data required to meet business goals.
As data analytics and data-driven intelligence takes centre stage in today’s digital economy, logical data integration across the widest variety of data sources, with proper security and governance structure in place has become mission-critical.
Attend this session to learn:
- Learn how you can meet cloud and data science challenges with data virtualization.
- Why data virtualization is increasingly finding enterprise-wide adoption
- Discover how customers are reducing costs and improving ROI with data virtualization
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(ENT211) Migrating the US Government to the Cloud | AWS re:Invent 2014Amazon Web Services
The US government has built hundreds of applications that must be refactored to task advantage of modern distributed systems. This session discusses EzBake, an open-source, secure big data platform deployed on top of Amazon EC2 and using Amazon S3 and Amazon RDS. This solution has helped speed the US government to the cloud and make big data easy. Furthermore this session discusses critical architecture design decisions through the creation of the platform in order to add additional security, leverage future AWS offerings, and cut total operations and maintenance costs.
Sponsored by CSC
Big Data, IoT, data lake, unstructured data, Hadoop, cloud, and massively parallel processing (MPP) are all just fancy words unless you can find uses cases for all this technology. Join me as I talk about the many use cases I have seen, from streaming data to advanced analytics, broken down by industry. I’ll show you how all this technology fits together by discussing various architectures and the most common approaches to solving data problems and hopefully set off light bulbs in your head on how big data can help your organization make better business decisions.
A Successful Journey to the Cloud with Data VirtualizationDenodo
Watch full webinar here: https://bit.ly/3mPLIlo
A shift to the cloud is a common element of any current data strategy. However, a successful transition to the cloud is not easy and can take years. It comes with security challenges, changes in downstream and upstream applications, and new ways to operate and deploy software. An abstraction layer that decouples data access from storage and processing can be a key element to enable a smooth journey to the cloud.
Attend this webinar to learn more about:
- How to use Data Virtualization to gradually change data systems without impacting business operations
- How Denodo integrates with the larger cloud ecosystems to enable security
- How simple it is to create and manage a Denodo cloud deployment
Similar to Data Driven Advanced Analytics using Denodo Platform on AWS (20)
Enterprise Monitoring and Auditing in DenodoDenodo
Watch full webinar here: https://buff.ly/3P3l4oK
Proper monitoring of an enterprise system is critical to understanding its capacity and growth, anticipating potential issues, and even understanding key ROI metrics. This also facilitates the implementation of policies and user access audits which are key to optimizing the resource utilization in an organization. Do you want to learn more about the new Denodo features for monitoring, auditing, and visualizing enterprise monitoring data?
Join us for the session with Vijayalakshmi Mani, Data Engineer at Denodo, to understand how the new features and components help in monitoring your Denodo Servers and the resource utilizations and how to extract the most out of the logs that the Denodo Platform generates including FinOps information.
Watch on-demand and Learn:
- What is a Denodo Monitor and what’s new in it?
- How to visualize the Denodo Monitor Information and use of Diagnostics & Monitoring Tool
- Introduction to the new Denodo Dashboard
- Demonstration on the Denodo Dashboard
Lunch and Learn ANZ: Mastering Cloud Data Cost Control: A FinOps ApproachDenodo
Watch full webinar here: https://buff.ly/4bYOOgb
With the rise of cloud-first initiatives and pay-per-use systems, forecasting IT costs has become a challenge. It's easy to start small, but it's equally easy to get skyrocketing bills with little warning. FinOps is a discipline that tries to tackle these issues, by providing the framework to understand and optimize cloud costs in a more controlled manner. The Denodo Platform, being a middleware layer in charge of global data delivery, sits in a privileged position not only to help us understand where costs are coming from, but also to take action, manage, and reduce them.
Attend this session to learn:
- The importance of FinOps in a cloud architecture.
- How the Denodo Platform can help you collect and visualize key FinOps metrics to understand where your costs are coming from?
- What actions and controls the Denodo Platform offers to keep costs at bay.
Achieving Self-Service Analytics with a Governed Data Services LayerDenodo
Watch full webinar here: https://buff.ly/3wBhxYb
In an increasingly distributed and complex data landscape, it is becoming increasingly difficult to govern and secure data effectively throughout the enterprise. Whether it be securing data across different repositories or monitoring access across different business units, the proliferation of data technologies and repositories across both on-premises and in the cloud is making the task unattainable. The challenge is only made greater by the ongoing pressure to offer self-service data access to business users.
Watch on-demand and learn:
- How to use a logical data fabric to build an enterprise-wide data access role model.
- Centralise security when data is spread across multiple systems residing both on-premises and in the cloud.
- Control and audit data access across different regions.
What you need to know about Generative AI and Data Management?Denodo
Watch full webinar here: https://buff.ly/3UXy0A2
It should be no surprise that Generative AI will have a profound impact to data management in years to come. Much like other areas of the technology sector, the opportunities presented by GenAI will accelerate our efforts around all aspects of data management, including self-service, automation, data governance and security. On the other hand, it is also becoming clearer that to unleash the true potential of AI assistants powered by GenAI, we need novel implementation strategies and a reimagined data architecture. This presents an exhilarating yet challenging future, demanding innovative thinking and methodologies in data management.
Join us on this webinar to learn about:
- The opportunities and challenges presented by GenAI today.
- Exploiting GenAI to democratize data management.
- How to augment GenAI applications with corporate data and knowledge.
- How to get started.
Mastering Data Compliance in a Dynamic Business LandscapeDenodo
Watch full webinar here: https://buff.ly/48rpLQ3
Join us for an enlightening webinar, "Mastering Data Compliance in a Dynamic Business Landscape," presented by Denodo Technologies and W5 Consulting. This session is tailored for business leaders and decision-makers who are navigating the complexities of data compliance in an ever-evolving business environment.
This webinar will focus on why data compliance is crucial for your business. Discover how to turn compliance into a competitive advantage, enhancing operational efficiency and market trust. We'll also address the risks of non-compliance, including financial penalties and the loss of customer trust, and provide strategies to proactively overcome these challenges.
Key Takeaways:
- How can your business leverage data management practices to stay agile and compliant in a rapidly changing regulatory landscape?
- Keys to balancing data accessibility with security and privacy in today's data-driven environment.
- What are the common pitfalls in achieving compliance with regulations like GDPR, CCPA, and HIPAA, and how can your business avoid them?
We will go beyond the technical aspects and delve into how you can strategically position your organization in the realm of data management and compliance. Learn how to craft a data compliance strategy that aligns with your business goals, enhances operational efficiency, and builds stakeholder trust.
Denodo Partner Connect: Business Value Demo with Denodo Demo LiteDenodo
Watch full webinar here: https://buff.ly/3OCQvGk
In this session, Denodo Sales Engineer, Yik Chuan Tan, will guide you through the art of delivering a compelling demo of the Denodo Platform with Denodo Demo Lite. Watch to uncover the significant functionalities that set Denodo apart and learn how to effectively win over potential customers.
In this session, we will cover:
Understanding the Denodo Platform & Tailoring Your Demo to Prospect Needs: By gaining a comprehensive understanding of the Denodo Platform, its architecture, and how it addresses data management challenges, you can customize your demo to align with the specific needs and pain points of your prospects, including:
- seamless data integration with real-time access
- data security and governance
- self-service data discovery
- advanced analytics and reporting
- performance optimization scalability and deployment
Watch this Denodo demo session and acquire the skills and knowledge necessary to captivate your prospects. Whether you're a seasoned technical professional or new to the field, this session will equip you with the skills to deliver compelling demos that lead to successful conversions.
Expert Panel: Overcoming Challenges with Distributed Data to Maximize Busines...Denodo
Watch full webinar here: https://buff.ly/3wdI1il
As organizations compete in new markets and new channels, business data requirements include new data platforms and applications. Migration to the cloud typically adds more distributed data when operations set up their own data platforms. This spreads important data across on-premises and cloud-based data platforms. As a result, data silos proliferate and become difficult to access, integrate, manage, and govern. Many organizations are using cloud data platforms to consolidate data, but distributed environments are unlikely to go away.
Organizations need holistic data strategies for unifying distributed data environments to improve data access and data governance, optimize costs and performance, and take advantage of modern technologies as they arrive. This TDWI Expert Panel will focus on overcoming challenges with distributed data to maximize business value.
Key topics this panel will address include:
- Developing the right strategy for your use cases and workloads in distributed data environments, such as data fabrics, data virtualization, and data mesh
- Deciding whether to consolidate data silos or bridge them with distributed data technologies
- Enabling easier self-service access and analytics across a distributed data environment
- Maximizing the value of data catalogs and other data intelligence technologies for distributed data environments
- Monitoring and data observability for spotting problems and ensuring business satisfaction
Watch full webinar here: https://buff.ly/3UE5K5l
The ability to recognize and flag sensitive information within corporate datasets is essential for compliance with emerging privacy laws, for completing a privacy impact assessment (PIA) or data subject access request (DSAR), and also for cyber-insurance compliance. During this session, we will discuss data privacy laws, the challenges they present, and how they can be applied with modern tools.
Join us for the session driven by Mark Rowan, CEO at Data Sentinel, and Bhavita Jaiswal, SE at Denodo, who will show how a data classification engine augments Data Catalog to support data governance and compliance objectives.
Watch on-demand & Learn:
- Changing landscape of data privacy laws and compliance requirements
- How to create a data classification framework
- How Data Sentinel classifies data and this can be integrated into Denodo
- Using the enhanced data classifications via consuming tools such as Data Catalog and Power BI
Знакомство с виртуализацией данных для профессионалов в области данныхDenodo
Watch full webinar here: https://buff.ly/3OETC08
По данным аналитической компании Gartner, "к 2022 году 60% предприятий включат виртуализацию данных в качестве основного метода доставки данных в свою интеграционную архитектуру". Компания Gartner назвала Denodo лидером в Магическом квадранте 2020 года по инструментам интеграции данных.
В ходе этого 1,5-часового занятия вы узнаете, как виртуализация данных революционизирует бизнес и ИТ-подход к доступу, доставке, потреблению, управлению и защите данных, независимо от возраста вашей технологии, формата данных или их местонахождения. Эта зрелая технология устраняет разрыв между ИТ и бизнес-пользователями и обеспечивает значительную экономию средств и времени.
**ФОРМАТ
Онлайн-семинар продолжительностью 1 час 30 минут.
Благодаря записи вы можете выполнять упражнения в своем собственном темпе.
**ДЛЯ КОГО ЭТОТ СЕМИНАР?
ИТ-менеджеры / архитекторы
Специалисты по анализу данных / аналитики
CDO
**СОДЕРЖАНИЕ
В программе: введение в суть виртуализации данных, примеры использования, реальные примеры из практики клиентов и демонстрация возможностей платформы Denodo Platform:
Интеграция и предоставление данных быстро и легко с помощью платформы Denodo Platform 8.0
Оптимизатор запросов Denodo предоставляет данные в режиме реального времени, по запросу, даже для очень больших наборов данных
Выставлять данные в качестве "сервисов данных" для потребления различными пользователями и инструментами
Каталог данных: Открывайте и документируйте данные с помощью нашего Каталога данных
пространства для самостоятельного доступа к данным.
Виртуализация данных играет ключевую роль в управлении и обеспечении безопасности данных в вашей организации
**ПОВЕСТКА
Введение в виртуализацию данных
Примеры использования и примеры из практики клиентов
Архитектура - Управление и безопасность
Производительность
Демо
Следующие шаги: как самостоятельно протестировать и внедрить платформу
Интерактивная сессия вопросов и ответов
Data Democratization: A Secret Sauce to Say Goodbye to Data FragmentationDenodo
Watch full webinar here: https://buff.ly/41Zf31D
Despite recent and evolving technological advances, the vast amounts of data that exist in a typical enterprise is not always available to all stakeholders when they need it. In modern enterprises, there are broad sets of users, with varying levels of skill sets, who strive to make data-driven decisions daily but struggle to gain access to the data needed in a timely manner.
Join our webinar to learn how to:
- Unlock the Power of Your Data: Discover how data democratization can transform your organization by giving every user access to the data they need, when they need it.
- Say 'Goodbye' to Data Fragmentation: Learn practical strategies to break down data silos and foster a more collaborative and efficient data environment.
- Realize the Full Potential of Your Data: Hear success stories about industry leaders who have embraced data democratization and witnessed tangible results.
Denodo Partner Connect - Technical Webinar - Ask Me AnythingDenodo
Watch full webinar here: https://buff.ly/48ZpEf1
In this session, we will cover a deeper dive into the Denodo Platform 8.0 Certified Architect Associate (DEN80EDUCAA) exam by answering any questions that have developed since the previous session.
Additionally, we invite partners to bring any general questions related to Denodo, the Denodo Platform, or data management.
Lunch and Learn ANZ: Key Takeaways for 2023!Denodo
Watch full webinar here: https://buff.ly/3SnH5QY
2023 is coming to an end where organisations dependency on trusted, accurate, secure and contextual data only grows more challenging. The perpetual aspect in seeking new architectures, processes, organisational team structures to "get the business their data" and reduce the operating costs continues unabated. While confidence from the business in what "value" is being derived or "to be" delivered from these investments in data, is being heavily scrutinised. 2023 saw significant new releases from vendors, focusing on the Data Fabric.
At this session we will look at these topics and key takeaways for 2023, including;
- Data management and data integration market highlights for 2023
- Key achievements for Denodo in their journey as a leader in this market
- A few case studies from Australian organisations in how they are delivering strategic business value through Denodo's Data Fabric platform and what they have been doing differently
It’s a Wrap! 2023 – A Groundbreaking Year for AI and The Way ForwardDenodo
Watch full webinar here: https://buff.ly/3S4Y49o
A little over a year ago, we would not have expected the disruptions caused by the rise of Generative AI. If 2023 was a groundbreaking year for AI, what will 2024 bring? More importantly, what can you do now to take advantage of these trends and ensure you are future-proof?
For example:
- Generative AI will become more powerful and user-friendly, enabling novel and realistic content creation and automation.
- Data Architectures will need to adapt to feed these powerful new models.
- Data ecosystems are moving to the cloud, but there is a growing need to maintain control of costs and optimize workloads better.
Join us for a discussion on the most significant trends in the Data & AI space, and how you can prepare to ride this wave!
Quels sont les facteurs-clés de succès pour appliquer au mieux le RGPD à votr...Denodo
Watch full webinar here: https://buff.ly/3O7rd2R
Afin d’être conformes au RGPD, les entreprises ont besoin d'avoir une vue d'ensemble sur toutes leurs données et d'établir des contrôles de sécurité sur toute l'infrastructure. La virtualisation des données de Denodo permet de rassembler les multiples sources de données, de les rendre accessibles à partir d'une seule couche, et offre des capacités de monitoring pour surveiller les changements.
Pour cela, Square IT Services a développé pour l’un de ses grands clients français prestigieux dans le secteur du luxe une interface utilisateur ergonomique qui lui permet de consulter les informations personnelles de ses clients, vérifier leur éligibilité à pratiquer leur droit à l'oubli, et de désactiver leurs différents canaux de notification. Elle dispose aussi d'une fonctionnalité d'audit qui permet de tracer l'historique des opérations effectuées, et lui permet donc de retrouver notamment la date à laquelle la personne a été anonymisée.
L'ensemble des informations remontées au niveau de l'application sont récupérées à partir des APIs REST exposées par Denodo.
Dans ce webinar, nous allons détailler l’ensemble des fonctionnalités de l’application DPO-Cockpit autour d’une démo, et expliquer à chaque étape le rôle central de Denodo pour réussir à simplifier la gestion du RGPD tout en étant compliant.
Les points clés abordés:
- Contexte client face aux enjeux du RGPD
- Défis et challenges rencontrés
- Options et choix retenu (Denodo)
- Démarche: architecture de la solution proposée
- Démo de l'outil: fonctionnalités principales
Lunch and Learn ANZ: Achieving Self-Service Analytics with a Governed Data Se...Denodo
Watch full webinar here: https://buff.ly/48zzN2h
In an increasingly distributed and complex data landscape, it is becoming increasingly difficult to govern and secure data effectively throughout the enterprise. Whether it be securing data across different repositories or monitoring access across different business units, the proliferation of data technologies and repositories across both on-premises and in the cloud is making the task unattainable. The challenge is only made greater by the ongoing pressure to offer self-service data access to business users.
Tune in and learn:
- How to use a logical data fabric to build an enterprise-wide data access role model.
- Centralise security when data is spread across multiple systems residing both on-premises and in the cloud.
- Control and audit data access across different regions.
How to Build Your Data Marketplace with Data Virtualization?Denodo
Watch full webinar here: https://buff.ly/4aAi0cS
Organizations continue to collect mounds of data and it is spread over different locations and in different formats. The challenge is navigating the vastness and complexity of the modern data ecosystem to find the right data to suit your specific business purpose. Data is an important corporate asset and it needs to be leveraged but also protected.
By adopting an alternate approach to data management and adapting a logical data architecture, data can be democratized while providing centralized control within a distributed data landscape. The web-based Data Catalog tool acts as a single access point for secure enterprise-wide data access and governance. This corporate data marketplace provides visibility into your data ecosystem and allows data to be shared without compromising data security policies.
Catch this live webinar to understand how this approach can transform how you leverage data across the business:
- Empower the knowledge worker with data and increase productivity
- Promote data accuracy and trust to encourage re-use of important data assets
- Apply consistent security and governance policies across the enterprise data landscape
Webinar #2 - Transforming Challenges into Opportunities for Credit UnionsDenodo
Watch full webinar here: https://buff.ly/3vhzqL5
Join our exclusive webinar series designed to empower credit unions with transformative insights into the untapped potential of data. Explore how data can be a strategic asset, enabling credit unions to overcome challenges and foster substantial growth.
This webinar will delve into how data can serve as a catalyst for addressing key challenges faced by credit unions, propelling them towards a future of enhanced efficiency and growth.
Enabling Data Catalog users with advanced usabilityDenodo
Watch full webinar here: https://buff.ly/48A4Yu1
Data catalogs are increasingly important in any modern data-driven organization. They are essential to manage and make the most of the huge amount of data that any organization uses. As this information is continuously growing in size and complexity, data catalogs are key to providing Data Discovery, Data Governance, and Data Lineage capabilities.
Join us for the session driven by David Fernandez, Senior Technical Account Manager at Denodo, to review the latest features aimed at improving the usability of the Denodo Data Catalog.
Watch on-demand & Learn:
- Enhanced search capabilities using multiple terms.
- How to create workflows to manage internal requests.
- How to leverage the AI capabilities of Data Catalog to generate SQL queries from natural language.
Watch full webinar here: https://buff.ly/3vjrn0s
The purpose of the Denodo Platform 8.0 Certified Architect Associate (DEN80EDUCAA) exam is to provide organizations that use Denodo Platform 8.0 with a means of identifying suitably qualified data architects who understand the role and position of the Denodo Platform within their broader information architecture.
This exam covers the following technical topics and subject areas:
- Denodo Platform functionality, including
- Governance and metadata management
- Security
- Performance optimization
- Caching
- Defining Denodo Platform use scenarios
Along with some sample questions, a Denodo Sales Engineer will help you prepare for exam topics and ace the exam.
Join us now to start your journey toward becoming a Certified Denodo Architect Associate!
GenAI y el futuro de la gestión de datos: mitos y realidadesDenodo
Watch full webinar here: https://buff.ly/3NLMSNM
El Generative AI y los Large Language Models (LLMs), encabezados por GPT de OpenAI, han supuesto la mayor revolución en el mundo de la computación de los últimos años. Pero ¿Cómo afectan realmente a la gestión de datos? ¿Reemplazarán los LLMs al profesional de la gestion de datos? ¿Cuánto hay de mito y cuánto de realidad?
En esta sesión revisaremos:
- Que es la Generative AI y por qué es importante para la gestión de datos
- Presente y futuro de aplicación de genAI en el mundo de los datos
- Cómo preparar tu organización para la adopción de genAI
Levelwise PageRank with Loop-Based Dead End Handling Strategy : SHORT REPORT ...Subhajit Sahu
Abstract — Levelwise PageRank is an alternative method of PageRank computation which decomposes the input graph into a directed acyclic block-graph of strongly connected components, and processes them in topological order, one level at a time. This enables calculation for ranks in a distributed fashion without per-iteration communication, unlike the standard method where all vertices are processed in each iteration. It however comes with a precondition of the absence of dead ends in the input graph. Here, the native non-distributed performance of Levelwise PageRank was compared against Monolithic PageRank on a CPU as well as a GPU. To ensure a fair comparison, Monolithic PageRank was also performed on a graph where vertices were split by components. Results indicate that Levelwise PageRank is about as fast as Monolithic PageRank on the CPU, but quite a bit slower on the GPU. Slowdown on the GPU is likely caused by a large submission of small workloads, and expected to be non-issue when the computation is performed on massive graphs.
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Empowering the Data Analytics Ecosystem: A Laser Focus on Value
The data analytics ecosystem thrives when every component functions at its peak, unlocking the true potential of data. Here's a laser focus on key areas for an empowered ecosystem:
1. Democratize Access, Not Data:
Granular Access Controls: Provide users with self-service tools tailored to their specific needs, preventing data overload and misuse.
Data Catalogs: Implement robust data catalogs for easy discovery and understanding of available data sources.
2. Foster Collaboration with Clear Roles:
Data Mesh Architecture: Break down data silos by creating a distributed data ownership model with clear ownership and responsibilities.
Collaborative Workspaces: Utilize interactive platforms where data scientists, analysts, and domain experts can work seamlessly together.
3. Leverage Advanced Analytics Strategically:
AI-powered Automation: Automate repetitive tasks like data cleaning and feature engineering, freeing up data talent for higher-level analysis.
Right-Tool Selection: Strategically choose the most effective advanced analytics techniques (e.g., AI, ML) based on specific business problems.
4. Prioritize Data Quality with Automation:
Automated Data Validation: Implement automated data quality checks to identify and rectify errors at the source, minimizing downstream issues.
Data Lineage Tracking: Track the flow of data throughout the ecosystem, ensuring transparency and facilitating root cause analysis for errors.
5. Cultivate a Data-Driven Mindset:
Metrics-Driven Performance Management: Align KPIs and performance metrics with data-driven insights to ensure actionable decision making.
Data Storytelling Workshops: Equip stakeholders with the skills to translate complex data findings into compelling narratives that drive action.
Benefits of a Precise Ecosystem:
Sharpened Focus: Precise access and clear roles ensure everyone works with the most relevant data, maximizing efficiency.
Actionable Insights: Strategic analytics and automated quality checks lead to more reliable and actionable data insights.
Continuous Improvement: Data-driven performance management fosters a culture of learning and continuous improvement.
Sustainable Growth: Empowered by data, organizations can make informed decisions to drive sustainable growth and innovation.
By focusing on these precise actions, organizations can create an empowered data analytics ecosystem that delivers real value by driving data-driven decisions and maximizing the return on their data investment.
Adjusting primitives for graph : SHORT REPORT / NOTESSubhajit Sahu
Graph algorithms, like PageRank Compressed Sparse Row (CSR) is an adjacency-list based graph representation that is
Multiply with different modes (map)
1. Performance of sequential execution based vs OpenMP based vector multiply.
2. Comparing various launch configs for CUDA based vector multiply.
Sum with different storage types (reduce)
1. Performance of vector element sum using float vs bfloat16 as the storage type.
Sum with different modes (reduce)
1. Performance of sequential execution based vs OpenMP based vector element sum.
2. Performance of memcpy vs in-place based CUDA based vector element sum.
3. Comparing various launch configs for CUDA based vector element sum (memcpy).
4. Comparing various launch configs for CUDA based vector element sum (in-place).
Sum with in-place strategies of CUDA mode (reduce)
1. Comparing various launch configs for CUDA based vector element sum (in-place).
Data Driven Advanced Analytics using Denodo Platform on AWS
1.
2. Agenda
1. Introduction to Data Driven Everything on AWS
2. Challenges with Data Driven Cloud Modernization
3. Addressing Challenges with Denodo Platform for AWS
4. Denodo Platform Use Cases and Data Architectures.
5. Key Takeaways | Q&A
3. 3
Modernizing leads to maximum innovation velocity and optimal
total cost of ownership
On-premises Lift
and shift
Move to managed
databases
Modernize with
purpose-built
databases
Innovation
velocity
Total
cost of
ownership
(TCO)
Break-free from
legacy databases
6. 6
What are customers building?
Backup &
restore
Non-disruptive
Easy place to start
Integrated with all
major vendors
Archive &
compliance
Media workflows
Tape replacement
Public Sector,
FinServ,
Healthcare/Life
Sciences
Home
directories
Simple to move
Not sensitive to
latency
Significant cost
savings
Data lakes
Variety of analytics
tools
Built for
streaming data
Data visualization
Business-
critical
applications
Integrated with
major vendors
Fully managed
infrastructure
Lift-and-shift
migrations
7. 7
AWS Customer- Analytics Challenges in a Distributed Data Landscape
Point-to-point data integration approaches are
challenging:
§ Extracting and moving data increases latency
and cost, and decreases quality, thus lacking
unified data access
§ Every project solves data access and
integration in a different way, increasing IT
dependency
§ Solutions are tightly coupled to data sources,
impacting flexibility, agility and overall
governance
DATA
SOURCE
DATA
CONSUMER
Data
Governance
Tools
DB, DW &
Data Lakes
Files
BI Dashboard
Report and Tools
Data Science &
Machine Learning
Apps
Mobile &
Enterprise Apps
Microservices
Apps
Cloud DB
& SaaS
Streaming
Data & IoT
Cube
8. 8
• The business wants more useful data
• Timely, curated, usable
• IT can’t keep up
• 67% of companies use less than half
of their data*
• IT stuck in old school thinking about data
management
• ‘Business as usual’
The ‘Useful Data’ Gap
* Source: Denodo Global Cloud Survey 2022
10. 10
10
Businesses need a new approach to
connect data silos in real-time to
support various applications, insights,
and analytics.
11. 11
Modern Data Architectural Patterns & Data Driven Analytics
Data Mesh
Data Lakehouse
Data Lake
Data Fabric
Cloud Data Warehouse
12. 12
Real World Data Lake Example – AWS
Trusted Data Zone
Raw Data Zone Refined Data Zone
Transformation Transformation Data Consumers
Networking, Infrastructure & Security
Data Ingestion
Data
Sources
Data Catalog and Search – Asset Registry Workflow Orchestration, DevOps and CI/CD
13. 13
Denodo + AWS – Simple and Complementary Recipe!
• Embrace distributed data landscape
• Embrace the fact that data resides in multiple
locations or systems – on-prem, hybrid, multi-
cloud. All data needs to be managed with
consistency
• Use a Logical approach to manage it
• Consumers access data through a centralized
semantic model, decoupled from data location
and physical schemas, that can enforce security
and governance requirements
14. 14
Denodo Platform: ONE Logical Platform for All Your Data
Ease of Use Fast Query
Response
Integrated,
Active Data Catalog
Universal
Connectivity
Modern Data
Services API Layer
Dynamic Data
Masking
Automated Cloud
Management
Key Differentiators
83% reduction
in time-to-revenue
67% reduction
in data preparation effort
65% decrease
in delivery times over ETL
Source: Forrester Total Economic ImpactTM of Data
Virtualization, 2021
Hybrid/
Multi-Cloud
Security &
Governance
Al/ML
Recommendations
Advanced
Semantics
Data Catalog
Discover / Explore /
Document
BI Tools
SQL / MDX
Data Science
Tools
Data as a Service
RESTful / Odata
GraphQL/ GeoJSON
Files
Cubes
Cloud
Stores
Traditional
DB & DW
INTEGRATE
MANAGE
DELIVER
Disparate data in
any location, format
or latency
Related data with a universal
semantic model and AI / ML
functionality enabling vital
data governance
And democratize data using
BI & data science tools,
data catalogs, and APIs
Data Lake &
NoSQL
Query
Optimization &
Acceleration
17. 17
Reduce the Business Impact
1 - Transition to the AWS Cloud (Minimize Business Disruption)
Business Need
§ Transition to cloud – migrate
EDW
§ Real-time analytics from Business
Users and Data Scientists
§ Security and governance across
multiple analytical tools need to be
centralized
§ Acts as a single semantic layer
§ Homogeneous data access regardless of
back-end technology
§ No need to deal with new languages and
APIs: access to SFDC, Excel, Amazon
Redshift, Oracle, Hadoop, other SaaS
APIs, etc.
§ Consistent business data model across all
consumers and reporting tools
§ Reusability of analytical objects across
multiple tools and consuming applications
§ Abstracts access to disparate data sources
§ Change in the data sources buffered
minimizing the impact on consumer
business applications
§ New technology adoption with minimal
impact on the business
§ Minimizes impact on consumers
§ Minimizes cross-environment connectivity
§ reducing risks of unauthorized access to
data
§ Amazon Athena
§ Amazon S3 Buckets
§ Amazon Redshift
§ Amazon Aurora
§ AWS PaaS - RDBMs
Denodo AWS
18. 18
Transition to Cloud | Cloud Migration Acceleration
Denodo becomes the common access layer for all on-
premise and cloud systems:
Access to all data from a single system
The data can be accessed directly from the
original system, without the need for replication
The data can still be easily replicated and hidden
if necessary
Simplify data aggregation, regardless of the location or
format of the data
Allows semantic models definition, independent of
the original formats and structures
Advanced security for all data
Documentation and usage statistics included in the
Data Catalog
20. 20
AWS Cloud Modernization - LeasePlan Data Hub Architecture
`
DATA
ACQUISITION
DATA
SOURCES
DATA
STORE (RAW)
ANALYTICS
WAREHOUSE
DATA
SCIENCE
DATA
FABRIC
DATA
CONSUMER
Next Gen Data Management (Meta-data, data quality, governance)
Meta data management, data quality, data governance as central components guarding the overall
data-asset of the corporation to allow trusted access to data for utilisation across the enterprise
Structured
Unstructured
ETL/ELT
ORCHESTRATION
STREAMING
Native Extraction
No ETL Tool(s)
AWS
Kinesis
Airflow
SAP BW/4HANA +
HANA Native
Raw
Quality
Integration
Consumption
Glacier
Archive
BW/4HANA +
HANA Native
NG Finance 1
NG Insurance
NG Procurement
NG Marketing
NG Sales
NG Service
NG Commerce
NG Fleet Ops
NG Supplier
Engagement
NG Policy Mgt.
NG Portals
NG Contact Center
Legacy – NOLS/
DB2/AS400 etc.
Other External Data:
Telematics, IoT, GA,
Social feeds,
streams
Analytics for
Cloud
Analysis for Office
AWS
SageMaker
Power BI
Role Based Access
Control
Caching
21. 21
Take the right decision on accurate data
2 - Real-Time Analytics for Business Users
Business Need
§ Transition to cloud – migrate EDW
§ Real-time analysis from
Business Users and Data
Scientists
§ Security and governance across
multiple analytical tools need to be
centralized
§ Enables Self-Service BI
§ IT delivers a governed layer of “business
views” to business users
§ Business users can generate any report
over those IT-governed business views
§ Business views can be adapted for every
type of user making use of the same
terminology and naming conventions for
every Line of Business
§ Incorporate geospatial, IoT, and
other streaming data, to enable
real-time data services
§ Accelerate cloud analytics with Amazon’s
elastic infrastructure (EC2, auto-scaling)
§ Data is immediately available for use
without delays
§ Integrate and Manage data across
Amazon Redshift, Amazon RDS,
Amazon S3 in real-time to drive
advanced analytics
§ Source data to Amazon Lambda
serverless processes and expose them
as data source for BI-Analytics
§ Visualize data and reports in real time
with QuickSights
Denodo AWS
22. 22
How Does Denodo Platform Work?
Development
Lifecycle Mgmt
Monitoring & Audit
Governance
Security
Development Tools
and SDK
Scheduled Tasks
Data Caching
Query Optimizer
JDBC/ODBC/ADO.Net SOAP / REST WS
U
Customer 360
View
Virtual Data
Mart View
J
Application
Layer
Business
Layer
Unified View Unified View
Unified View
Unified View
A
J
J
Derived View Derived View
J
J
S
Transformation
& Cleansing
Data
Source
Layer
Base
View
Base
View
Base
View
Base
View
Base
View
Base
View
Base
View
Abstraction
23. 23
FAA – Federal Aviation Administration – Streamline Operations/Analytics
ü Reduced the IT Operations Cost by 99.8%,
while accelerating data access by 96%.
ü To reduce costs and streamline IT operations,
the U.S. Federal Aviation Administration (FAA)
wanted to consolidate multiple IT
organizations – each supporting different
mission areas – into a single office reporting
to a single CIO.
FAA leveraged the Denodo platform on AWS to:
24. 24
Across multiple analytical tools
3 - Centralized Security and Governance
Business Need
§ Transition to cloud – migrate EDW
§ Real-time analytics from Business
Users and Data Scientists
§ Security and governance across
multiple analytical tools need to
be centralized
§ Unified Security Layer
§ Global Tag-based Policy Engine
§ Role-based authorization to all tables in
the virtual layer (RBAC)
§ Attribute-based access control (ABAC)
§ Security is moved outside the reporting
layer to avoid security bypasses
§ Centralized access point simplifies
operations and auditing
§ Data Masking / Obfuscation
§ Centralized Governance Layer
§ Centralized metadata catalog accessible
for both technical and business users
§ Data Source refresh, change impact
analysis, full data lineage, etc.
§ Protects data sources from uncontrolled
access through query throttling, limiting
#concurrent queries over them, limiting
resulting datasets sizes, enabling the cache
for minimizing the access to data sources for
some views, etc.
Denodo AWS Services
§ Datawarehouse Built for the cloud
§ Athena
§ Redshift
§ Secured, Managed Access
§ With Amazon Resource Manager
§ Identity Management & SSO Amazon
IAM
25. 25
Data Fabric Overview
Core Principles:
ü Data Integration
ü Data Governance
ü Data Democratization
ü Data Intelligence
ü Data Interoperability
26. 26
Data Mesh Powered by Denodo Data Virtualization
SQL
Operational EDW
Data Lakes Files
SaaS APIs
REST GraphQL OData
Event
Product
Customer Location Employee
Common Domain Event Management Human Resources
MDX
2.Domains connect
their data sources
❷
1.Each domain is given a
separate virtual schema.
A common domain may be
useful to centralized data
products common across
domains
❶
3.Metadata is mapped
to relational views.
No data is replicated
❸
4.Domains SMEs can
model their Data
Products.
Products can be used to
define other products
❹
5.For execution, Products can
be served directly from
their sources, or replicated
to a central location, like a
lake
❺
6.A central team can
set guidelines and
governance to
ensure
interoperability
❻
7.Products can be access via
SQL, MDX or exposed as an
API. No coding is required
❼ 8.Infrastructure can
easily scale out in a
cluster
❽
New architectural paradigm for data management | distributed organizational paradigm | Domains in charge of Data Products
29. Benefits of a Logical Data Architecture
“Now, we can do weekly releases.
We’re able to add new data sources
within 2 to 3 hours. We’re about 60%
faster than we were in the old world.”
VP of data and analytics, real estate
“To me, it all boils down to speed to
insights. Not having to wait to get the
question that you have top-of-mind
answered with data is huge.”
VP of data and analytics, real estate
29
30. 30
Try Denodo Platform on AWS – Get Started Today!
• 30 days Free Trial of Denodo Professional via AWS Marketplace
• AWS Marketplace Transactable Pay-Go/Private Offers
• Denodo – AWS Test Drives (free hands-on learning in 2 hours) :
Denodo-AWS BI
Denodo-AWS Data Science
Visit Denodo Platform and AWS
https://www.denodo.com/en/denodo-platform/denodo-platform-for-aws