Diyotta is the leading modern data integration company, helping companies turn Hadoop into a powerful information hub. We accelerate time to value for new investments in big data platforms and for ongoing data warehouse modernization.
A Journey to the Cloud with Data VirtualizationDenodo
Watch this Fast Data Strategy Virtual Summit with speakers Cijo Thomas Isaac, Big Data Architect, Asurion & Nick Sarkisian, Associate Vice President - North America Analytics Head, HCL here: https://buff.ly/2KwLvj3
While Asurion expanded its operations globally, their global client base expected highest quality customer service, something Asurion prides itself with. At the same time Asurions brand new digital home premium support required strong predictive analytics, IoT and big data architecture support to provide their customers with the best user experience.
Attend this session to learn:
• How Asurion built its hybrid cloud environment using data virtualization
• Why centralizing security and data governance is key to their data architecture
• Why data virtualization is important for their advanced analytics and data science
Enable Scalable, Intelligent
File Access and Management. Like most organizations today, yours is required to search millions of electronic records for audit and legal discovery. However, sprawling infrastructure and decentralized control with separate management tools make it difficult to search across the enterprise. Now, more than ever, powerful search engines are a must for your increasing unstructured data and content repositories.
Watch full webinar here: https://bit.ly/3eEax0F
iOCO enables companies to overcome challenges, so they can engage in successful digital transformations, gain all of their expected benefits, and remain competitive in the face of digital disruption. Listen to this session to learn how iOCO facilitates digital transformations that accelerate time-to-market while improving agility.
Partner Keynote: How Logical Data Fabric Knits Together Data Visualization wi...Denodo
Watch full webinar here: https://bit.ly/3aALFEC
Data Visualization and Data Virtualization are complementary technologies. But how do they come together under a common data fabric? This presentation will discuss how organizations are advancing their data fabric capabilities leveraging innovations in these two technologies in areas of self-service, data catalog, cloud, and AI/ML.
Watch full webinar here: https://bit.ly/2Y0vudM
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.
Register to attend 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?
Logical Data Fabric: Architectural ComponentsDenodo
Watch full webinar here: https://bit.ly/39MWm7L
Is the Logical Data Fabric one monolithic technology or does it comprise of various components? If so, what are they? In this presentation, Denodo CTO Alberto Pan will elucidate what components make up the logical data fabric.
Analyst Keynote: TDWI: Data Virtualization as a Data Management Strategy for ...Denodo
Watch full webinar here: https://bit.ly/3rnxYzr
In this presentation, TDWI analyst will describe data virtualization as an appropriate data management strategy when advanced analytics applications demand very fresh data or when advanced analytics data is distributed across multiple data platforms in a hybrid data architecture.
Supporting Data Services Marketplace using Data VirtualizationDenodo
Data is treated truly as an asset at Guardian Life. We have created a Data Services Marketplace which contains valuable data from the underlying sources and is used by business users for day-to-day operations. In this presentation, you will see how Data Virtualization can be used to support the marketplace with real-time data services, provision non real-time data into Hadoop, and swap underlying sources without effecting business users.
This presentation is part of the Fast Data Strategy Conference, and you can watch the video here goo.gl/PZ2uFj.
A Journey to the Cloud with Data VirtualizationDenodo
Watch this Fast Data Strategy Virtual Summit with speakers Cijo Thomas Isaac, Big Data Architect, Asurion & Nick Sarkisian, Associate Vice President - North America Analytics Head, HCL here: https://buff.ly/2KwLvj3
While Asurion expanded its operations globally, their global client base expected highest quality customer service, something Asurion prides itself with. At the same time Asurions brand new digital home premium support required strong predictive analytics, IoT and big data architecture support to provide their customers with the best user experience.
Attend this session to learn:
• How Asurion built its hybrid cloud environment using data virtualization
• Why centralizing security and data governance is key to their data architecture
• Why data virtualization is important for their advanced analytics and data science
Enable Scalable, Intelligent
File Access and Management. Like most organizations today, yours is required to search millions of electronic records for audit and legal discovery. However, sprawling infrastructure and decentralized control with separate management tools make it difficult to search across the enterprise. Now, more than ever, powerful search engines are a must for your increasing unstructured data and content repositories.
Watch full webinar here: https://bit.ly/3eEax0F
iOCO enables companies to overcome challenges, so they can engage in successful digital transformations, gain all of their expected benefits, and remain competitive in the face of digital disruption. Listen to this session to learn how iOCO facilitates digital transformations that accelerate time-to-market while improving agility.
Partner Keynote: How Logical Data Fabric Knits Together Data Visualization wi...Denodo
Watch full webinar here: https://bit.ly/3aALFEC
Data Visualization and Data Virtualization are complementary technologies. But how do they come together under a common data fabric? This presentation will discuss how organizations are advancing their data fabric capabilities leveraging innovations in these two technologies in areas of self-service, data catalog, cloud, and AI/ML.
Watch full webinar here: https://bit.ly/2Y0vudM
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.
Register to attend 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?
Logical Data Fabric: Architectural ComponentsDenodo
Watch full webinar here: https://bit.ly/39MWm7L
Is the Logical Data Fabric one monolithic technology or does it comprise of various components? If so, what are they? In this presentation, Denodo CTO Alberto Pan will elucidate what components make up the logical data fabric.
Analyst Keynote: TDWI: Data Virtualization as a Data Management Strategy for ...Denodo
Watch full webinar here: https://bit.ly/3rnxYzr
In this presentation, TDWI analyst will describe data virtualization as an appropriate data management strategy when advanced analytics applications demand very fresh data or when advanced analytics data is distributed across multiple data platforms in a hybrid data architecture.
Supporting Data Services Marketplace using Data VirtualizationDenodo
Data is treated truly as an asset at Guardian Life. We have created a Data Services Marketplace which contains valuable data from the underlying sources and is used by business users for day-to-day operations. In this presentation, you will see how Data Virtualization can be used to support the marketplace with real-time data services, provision non real-time data into Hadoop, and swap underlying sources without effecting business users.
This presentation is part of the Fast Data Strategy Conference, and you can watch the video here goo.gl/PZ2uFj.
Quicker Insights and Sustainable Business Agility Powered By Data Virtualizat...Denodo
Watch full webinar here: https://bit.ly/3xj6fnm
Presented at Chief Data Officer Live 2021 A/NZ
The world is changing faster than ever. And for companies to compete and succeed they need to be agile in order to respond quickly to market changes and emerging opportunities. Data plays an integral role in achieving this business agility. However, given the complex nature of the enterprise data architecture finding and analysing data is an increasingly challenging task. Data virtualization is a modern data integration technique that integrates data in real-time, without having to physically replicate it.
Watch on-demand this session to understand what data virtualization is and how it:
- Delivers data in real-time, and without replication
- Creates a logical architecture to provide a single view of truth
- Centralises the data governance and security framework
- Democratises data for faster decision making and business agility
Big Data Fabric: A Recipe for Big Data InitiativesDenodo
Big data fabric combines essential big data capabilities in a single platform to automate the many facets of data discovery, preparation, curation, orchestration, and integration across a multitude of data sources. Attend this session to learn how Big Data Fabric enabled by data virtualization constitutes a recipe for:
• Enabling new actionable insights with minimal effort
• Securing big data end-to-end
• Addressing big data skillset scarcity
• Providing easy access to data without having to decipher various data formats
Agenda:
• Big Data with Data Virtualization
• Product Demonstration
• Summary & Next Steps
• Q&A
Watch webinar on demand here: https://goo.gl/EpmIBx
This webinar is part of the Data Virtualization Packed Lunch Webinar Series: https://goo.gl/W1BeCb
As the deadline for GDPR approaches, it is time to get practical about protecting personal data.
We break down the steps for turning a data lake into a data hub with appropriate data management and governance activities: from capturing and reconciling personal data to providing for consent management, data anonymyzation, and the rights of the data subject.
A smart approach to GDPR compliance lays a foundation for personalized and profitable customer and employee relations.
Join us, as experts from MAPR and Talend show you how to:
Diagnose the maturity of your GDPR compliance
Set up milestones and priorities to reach compliance
Create a foundation to manage personal data through a data lake
Master compliance operations - from data inventory to data transfers to individual rights management
Data Virtualization for Compliance – Creating a Controlled Data EnvironmentDenodo
CIT modernized its data architecture in response to intense regulatory scrutiny. In this presentation, they present how data virtualization is being used to drive standardization, enable cross-company data integration, and serve as a common provisioning point from which to access all authoritative sources of data.
This presentation is part of the Fast Data Strategy Conference, and you can watch the video here goo.gl/CCqUeT.
Why Data Virtualization Matters in Your PortfolioDenodo
Watch full webinar here: [https://buff.ly/2W925vO]
Enterprise data virtualization has become critical to every organization in overcoming growing data challenges. In this webinar, Forrester analyst Noel Yuhanna, author of The Enterprise Data Virtualization Wave, will address:
Data virtualization market growth trends and momentum
Key solutions and use cases
How leaders like Denodo are differentiating from other vendors in the market
Analyst Keynote: Forrester: Data Fabric Strategy is Vital for Business Innova...Denodo
Watch full webinar here: https://bit.ly/36GEuJO
Traditional data integration is falling short to meet new business requirements - real-time connected data, self-service, automation, speed, and intelligence. Forrester analyst will explain how data fabric is emerging as a hot new market for an intelligent and unified platform.
The Role of the Logical Data Fabric in a Unified Platform for Modern AnalyticsDenodo
Watch full webinar here: https://bit.ly/3FHKalT
Given the growing demand for analytics and the need for organizations to advance beyond dashboards to self-service analytics and more sophisticated algorithms like machine learning (ML), enterprises are moving towards a unified environment for data and analytics. What is the best approach to accomplish this unification?
In TDWI’s recent Best Practice Report, Unified Platforms for Modern Analytics, written by Fern Halper, TDWI VP Research, Senior Research Director for Advanced Analytics, adoption, use, challenges, architectures, and best practices for unified platforms for modern analytics is explored. One of the approaches for unification outlined in the report is a data fabric approach.
Join us for a webinar with our Director of Product Marketing, Robin Tandon, where he will discuss the role of the logical data fabric in a unified platform for modern analytics, focusing on several of the key findings outlined in this report. He will share insights and use case examples that demonstrate how a properly implemented logical data fabric is the most suitable approach for Unified Data Platforms across enterprises and organizations.
Watch on-demand & Learn:
- The benefits of a unified platform and its ability to capture diverse & emerging data types and how to support high performance and scalable solutions.
- The role of an enhanced AI driven data catalog and its implications towards the findings in the best practice report.
- Implications of a logical data fabric as it relates to several of the recommendations outlined in the report.
Big Data Fabric: A Necessity For Any Successful Big Data InitiativeDenodo
Watch this webinar in full here: https://buff.ly/2IxM8Iy
Watch all webinars from the Denodo Packed Lunch webinar series here: https://buff.ly/2IR3q6w
While big data initiatives have become necessary for any business to generate actionable insights, big data fabric has become a necessity for any successful big data initiative. The best of breed big data fabrics should deliver actionable insights to the business users with minimal effort, provide end-to-end security to the entire enterprise data platform and provide real-time data integration, while delivering self-service data platform to business users.
Attend this session to learn how big data fabric enabled by data virtualization:
• Provides lightning fast self-service data access to business users
• Centralizes data security, governance and data privacy
• Fulfills the promise of data lakes to provide actionable insights
Delivering Self-Service Analytics using Big Data and Data Virtualization on t...Denodo
Watch full webinar here: [https://buff.ly/2FHWnMD]
Headquartered in New York City, Guardian Life is one of the largest mutual life insurance companies in the United States. Guardian offerings range from life insurance, disability income insurance, annuities, and investments to dental and vision insurance and employee benefits. The Enterprise Data Program was initiated to modernize Guardian’s technology capabilities and transform how Guardian leverages data – the Enterprise Data Lake was implemented to democratize data and drive self-service analytics throughout the organization. Data virtualization has played a key role for delivering data services through Guardian’s Enterprise Data Marketplace, a centralized portal for analytics and reporting.
Attend this session to learn:
Who is Guardian and what were the key drivers for building a data lake?
What are the data architectural patterns on the cloud?
How data virtualization is powering analytics and reporting?
In my 35 years in IT, I have never seen so much simultaneous change in technology. Every part of the IT stack is in transition - end user devices, networks, application design, virtual server software, physical server design, storage systems, and even storage media. Some of these transitions are well underway and will accelerate in 2015 while others are just starting to emerge. Either way, buckle up! IT is going to be a wild ride in 2015.
Implementar una estrategia eficiente de gobierno y seguridad del dato con la ...Denodo
Watch full webinar here: https://bit.ly/3lSwLyU
En la era de la explosión de la información repartida en distintas fuentes, el gobierno de datos es un componente clave para garantizar la disponibilidad, usabilidad, integridad y seguridad de la información. Asimismo, el conjunto de procesos, roles y políticas que define permite que las organizaciones alcancen sus objetivos asegurando el uso eficiente de sus datos.
La virtualización de datos forma parte de las herramientas estratégica para implementar y optimizar el gobierno de datos. Esta tecnología permite a las empresas crear una visión 360º de sus datos y establecer controles de seguridad y políticas de acceso sobre toda la infraestructura, independientemente del formato o de su ubicación. De ese modo, reúne múltiples fuentes de datos, las hace accesibles desde una sola capa y proporciona capacidades de trazabilidad para supervisar los cambios en los datos.
Le invitamos a participar en este webinar para aprender:
- Cómo acelerar la integración de datos provenientes de fuentes de datos fragmentados en los sistemas internos y externos y obtener una vista integral de la información.
- Cómo activar en toda la empresa una sola capa de acceso a los datos con medidas de protección.
- Cómo la virtualización de datos proporciona los pilares para cumplir con las normativas actuales de protección de datos mediante auditoría, catálogo y seguridad de datos.
Logical Data Warehouse and Data Lakes can play a role in many different type of projects and, in this presentation, we will look at some of the most common patterns and use cases. Learn about analytical and big data patterns as well as performance considerations. Example implementations will be discussed for each pattern.
- Architectural patterns for logical data warehouse and data lakes.
- Performance considerations.
- Customer use cases and demo.
This presentation is part of the Denodo Educational Seminar, and you can watch the video here goo.gl/vycYmZ.
Advanced Analytics and Machine Learning with Data Virtualization (India)Denodo
Watch full webinar here: https://bit.ly/3dMN503
Advanced data science techniques, like machine learning, have proven an extremely useful tool to derive valuable insights from existing data. Platforms like Spark, and complex libraries for R, Python, and Scala put advanced techniques at the fingertips of the data scientists. However, these data scientists spend most of their time looking for the right data and massaging it into a usable format. Data virtualization offers a new alternative to address these issues in a more efficient and agile way.
Watch this session to learn how companies can use data virtualization to:
- Create a logical architecture to make all enterprise data available for advanced analytics exercise
- Accelerate data acquisition and massaging, providing the data scientist with a powerful tool to complement their practice
- Integrate popular tools from the data science ecosystem: Spark, Python, Zeppelin, Jupyter, etc
Product Keynote: Denodo 8.0 - A Logical Data Fabric for the Intelligent Enter...Denodo
Watch full webinar here: https://bit.ly/2O9gcBT
Denodo 8 expands data integration and management to data fabric with advanced data virtualization capabilities. What are they? Denodo CTO Alberto Pan will touch upon the key Denodo 8 capabilities.
Introduction to Big Data Hadoop Training Online by www.itjobzone.bizITJobZone.biz
Want to learn Hadoop online? This PPT give you Introduction to Big Data Hadoop Training Online by expert trainers at ITJobZone.biz - Start your Hadoop Online training with this Presentation.
Unifying Big Data Integration | Diyotta Indiadiyotta
Data integration processes can be complex in big data architectures and deployments. When using Hadoop as a mainstream platform there is still a requirement to work with co-existing data platforms such as Massively Parallel Processing systems or traditional data repositories. Moving data from source systems to target needs to be efficient and leveraging the processing capabilities of those platforms to transform data is optimal.
Telecom Provider Case Study | Big Data Adoption | Diyottadiyotta
One of Diyotta’s and Hortonworks’ customer, a North American service provider had historically used traditional database systems to analyze these network transactions. However,the sheer volume of data, generated by this provider’s myriad of data sources needed a scalable solution for data storage, high-volume data ingestion at high frequency, data processing and data provisioning from Hadoop.
Quicker Insights and Sustainable Business Agility Powered By Data Virtualizat...Denodo
Watch full webinar here: https://bit.ly/3xj6fnm
Presented at Chief Data Officer Live 2021 A/NZ
The world is changing faster than ever. And for companies to compete and succeed they need to be agile in order to respond quickly to market changes and emerging opportunities. Data plays an integral role in achieving this business agility. However, given the complex nature of the enterprise data architecture finding and analysing data is an increasingly challenging task. Data virtualization is a modern data integration technique that integrates data in real-time, without having to physically replicate it.
Watch on-demand this session to understand what data virtualization is and how it:
- Delivers data in real-time, and without replication
- Creates a logical architecture to provide a single view of truth
- Centralises the data governance and security framework
- Democratises data for faster decision making and business agility
Big Data Fabric: A Recipe for Big Data InitiativesDenodo
Big data fabric combines essential big data capabilities in a single platform to automate the many facets of data discovery, preparation, curation, orchestration, and integration across a multitude of data sources. Attend this session to learn how Big Data Fabric enabled by data virtualization constitutes a recipe for:
• Enabling new actionable insights with minimal effort
• Securing big data end-to-end
• Addressing big data skillset scarcity
• Providing easy access to data without having to decipher various data formats
Agenda:
• Big Data with Data Virtualization
• Product Demonstration
• Summary & Next Steps
• Q&A
Watch webinar on demand here: https://goo.gl/EpmIBx
This webinar is part of the Data Virtualization Packed Lunch Webinar Series: https://goo.gl/W1BeCb
As the deadline for GDPR approaches, it is time to get practical about protecting personal data.
We break down the steps for turning a data lake into a data hub with appropriate data management and governance activities: from capturing and reconciling personal data to providing for consent management, data anonymyzation, and the rights of the data subject.
A smart approach to GDPR compliance lays a foundation for personalized and profitable customer and employee relations.
Join us, as experts from MAPR and Talend show you how to:
Diagnose the maturity of your GDPR compliance
Set up milestones and priorities to reach compliance
Create a foundation to manage personal data through a data lake
Master compliance operations - from data inventory to data transfers to individual rights management
Data Virtualization for Compliance – Creating a Controlled Data EnvironmentDenodo
CIT modernized its data architecture in response to intense regulatory scrutiny. In this presentation, they present how data virtualization is being used to drive standardization, enable cross-company data integration, and serve as a common provisioning point from which to access all authoritative sources of data.
This presentation is part of the Fast Data Strategy Conference, and you can watch the video here goo.gl/CCqUeT.
Why Data Virtualization Matters in Your PortfolioDenodo
Watch full webinar here: [https://buff.ly/2W925vO]
Enterprise data virtualization has become critical to every organization in overcoming growing data challenges. In this webinar, Forrester analyst Noel Yuhanna, author of The Enterprise Data Virtualization Wave, will address:
Data virtualization market growth trends and momentum
Key solutions and use cases
How leaders like Denodo are differentiating from other vendors in the market
Analyst Keynote: Forrester: Data Fabric Strategy is Vital for Business Innova...Denodo
Watch full webinar here: https://bit.ly/36GEuJO
Traditional data integration is falling short to meet new business requirements - real-time connected data, self-service, automation, speed, and intelligence. Forrester analyst will explain how data fabric is emerging as a hot new market for an intelligent and unified platform.
The Role of the Logical Data Fabric in a Unified Platform for Modern AnalyticsDenodo
Watch full webinar here: https://bit.ly/3FHKalT
Given the growing demand for analytics and the need for organizations to advance beyond dashboards to self-service analytics and more sophisticated algorithms like machine learning (ML), enterprises are moving towards a unified environment for data and analytics. What is the best approach to accomplish this unification?
In TDWI’s recent Best Practice Report, Unified Platforms for Modern Analytics, written by Fern Halper, TDWI VP Research, Senior Research Director for Advanced Analytics, adoption, use, challenges, architectures, and best practices for unified platforms for modern analytics is explored. One of the approaches for unification outlined in the report is a data fabric approach.
Join us for a webinar with our Director of Product Marketing, Robin Tandon, where he will discuss the role of the logical data fabric in a unified platform for modern analytics, focusing on several of the key findings outlined in this report. He will share insights and use case examples that demonstrate how a properly implemented logical data fabric is the most suitable approach for Unified Data Platforms across enterprises and organizations.
Watch on-demand & Learn:
- The benefits of a unified platform and its ability to capture diverse & emerging data types and how to support high performance and scalable solutions.
- The role of an enhanced AI driven data catalog and its implications towards the findings in the best practice report.
- Implications of a logical data fabric as it relates to several of the recommendations outlined in the report.
Big Data Fabric: A Necessity For Any Successful Big Data InitiativeDenodo
Watch this webinar in full here: https://buff.ly/2IxM8Iy
Watch all webinars from the Denodo Packed Lunch webinar series here: https://buff.ly/2IR3q6w
While big data initiatives have become necessary for any business to generate actionable insights, big data fabric has become a necessity for any successful big data initiative. The best of breed big data fabrics should deliver actionable insights to the business users with minimal effort, provide end-to-end security to the entire enterprise data platform and provide real-time data integration, while delivering self-service data platform to business users.
Attend this session to learn how big data fabric enabled by data virtualization:
• Provides lightning fast self-service data access to business users
• Centralizes data security, governance and data privacy
• Fulfills the promise of data lakes to provide actionable insights
Delivering Self-Service Analytics using Big Data and Data Virtualization on t...Denodo
Watch full webinar here: [https://buff.ly/2FHWnMD]
Headquartered in New York City, Guardian Life is one of the largest mutual life insurance companies in the United States. Guardian offerings range from life insurance, disability income insurance, annuities, and investments to dental and vision insurance and employee benefits. The Enterprise Data Program was initiated to modernize Guardian’s technology capabilities and transform how Guardian leverages data – the Enterprise Data Lake was implemented to democratize data and drive self-service analytics throughout the organization. Data virtualization has played a key role for delivering data services through Guardian’s Enterprise Data Marketplace, a centralized portal for analytics and reporting.
Attend this session to learn:
Who is Guardian and what were the key drivers for building a data lake?
What are the data architectural patterns on the cloud?
How data virtualization is powering analytics and reporting?
In my 35 years in IT, I have never seen so much simultaneous change in technology. Every part of the IT stack is in transition - end user devices, networks, application design, virtual server software, physical server design, storage systems, and even storage media. Some of these transitions are well underway and will accelerate in 2015 while others are just starting to emerge. Either way, buckle up! IT is going to be a wild ride in 2015.
Implementar una estrategia eficiente de gobierno y seguridad del dato con la ...Denodo
Watch full webinar here: https://bit.ly/3lSwLyU
En la era de la explosión de la información repartida en distintas fuentes, el gobierno de datos es un componente clave para garantizar la disponibilidad, usabilidad, integridad y seguridad de la información. Asimismo, el conjunto de procesos, roles y políticas que define permite que las organizaciones alcancen sus objetivos asegurando el uso eficiente de sus datos.
La virtualización de datos forma parte de las herramientas estratégica para implementar y optimizar el gobierno de datos. Esta tecnología permite a las empresas crear una visión 360º de sus datos y establecer controles de seguridad y políticas de acceso sobre toda la infraestructura, independientemente del formato o de su ubicación. De ese modo, reúne múltiples fuentes de datos, las hace accesibles desde una sola capa y proporciona capacidades de trazabilidad para supervisar los cambios en los datos.
Le invitamos a participar en este webinar para aprender:
- Cómo acelerar la integración de datos provenientes de fuentes de datos fragmentados en los sistemas internos y externos y obtener una vista integral de la información.
- Cómo activar en toda la empresa una sola capa de acceso a los datos con medidas de protección.
- Cómo la virtualización de datos proporciona los pilares para cumplir con las normativas actuales de protección de datos mediante auditoría, catálogo y seguridad de datos.
Logical Data Warehouse and Data Lakes can play a role in many different type of projects and, in this presentation, we will look at some of the most common patterns and use cases. Learn about analytical and big data patterns as well as performance considerations. Example implementations will be discussed for each pattern.
- Architectural patterns for logical data warehouse and data lakes.
- Performance considerations.
- Customer use cases and demo.
This presentation is part of the Denodo Educational Seminar, and you can watch the video here goo.gl/vycYmZ.
Advanced Analytics and Machine Learning with Data Virtualization (India)Denodo
Watch full webinar here: https://bit.ly/3dMN503
Advanced data science techniques, like machine learning, have proven an extremely useful tool to derive valuable insights from existing data. Platforms like Spark, and complex libraries for R, Python, and Scala put advanced techniques at the fingertips of the data scientists. However, these data scientists spend most of their time looking for the right data and massaging it into a usable format. Data virtualization offers a new alternative to address these issues in a more efficient and agile way.
Watch this session to learn how companies can use data virtualization to:
- Create a logical architecture to make all enterprise data available for advanced analytics exercise
- Accelerate data acquisition and massaging, providing the data scientist with a powerful tool to complement their practice
- Integrate popular tools from the data science ecosystem: Spark, Python, Zeppelin, Jupyter, etc
Product Keynote: Denodo 8.0 - A Logical Data Fabric for the Intelligent Enter...Denodo
Watch full webinar here: https://bit.ly/2O9gcBT
Denodo 8 expands data integration and management to data fabric with advanced data virtualization capabilities. What are they? Denodo CTO Alberto Pan will touch upon the key Denodo 8 capabilities.
Introduction to Big Data Hadoop Training Online by www.itjobzone.bizITJobZone.biz
Want to learn Hadoop online? This PPT give you Introduction to Big Data Hadoop Training Online by expert trainers at ITJobZone.biz - Start your Hadoop Online training with this Presentation.
Unifying Big Data Integration | Diyotta Indiadiyotta
Data integration processes can be complex in big data architectures and deployments. When using Hadoop as a mainstream platform there is still a requirement to work with co-existing data platforms such as Massively Parallel Processing systems or traditional data repositories. Moving data from source systems to target needs to be efficient and leveraging the processing capabilities of those platforms to transform data is optimal.
Telecom Provider Case Study | Big Data Adoption | Diyottadiyotta
One of Diyotta’s and Hortonworks’ customer, a North American service provider had historically used traditional database systems to analyze these network transactions. However,the sheer volume of data, generated by this provider’s myriad of data sources needed a scalable solution for data storage, high-volume data ingestion at high frequency, data processing and data provisioning from Hadoop.
Data integration in the big data world can be very complex. When using the MapR Distribution including Apache Hadoop as an integral component of your enterprise architecture, there is still the need to work with existing systems such as MPP data warehouses and traditional data repositories. Moving data from these sources to MapR needs to be efficient, and leveraging the processing capabilities of Hadoop to transform data is critical.
This new solution from Capgemini, implemented in
partnership with Informatica, Cloudera and Appfluent,
optimizes the ratio between the value of data and storage
costs, making it easy to take advantage of new big data
technologies.
Webinar: Improving Time to Value for Enterprise Big Data AnalyticsStorage Switzerland
In this webinar Storage Switzerland, Hitachi Data Systems and Brocade discuss why enterprises need to invest in big data analytics, how they can make that investment and what are some of the key requirements in designing a system.
The Cloudera Impala project is pioneering the next generation of Hadoop capabilities: the convergence of interactive SQL queries with the capacity, scalability, and flexibility of a Hadoop cluster. In this webinar, join Cloudera and MicroStrategy to learn how Impala works, how it is uniquely architected to provide an interactive SQL experience native to Hadoop, and how you can leverage the power of MicroStrategy 9.3.1 to easily tap into more data and make new discoveries.
Hadoop was born out of the need to process Big Data.Today data is being generated liked never before and it is becoming difficult to store and process this enormous volume and large variety of data, In order to cope this Big Data technology comes in.Today Hadoop software stack is go-to framework for large scale,data intensive storage and compute solution for Big Data Analytics Applications.The beauty of Hadoop is that it is designed to process large volume of data in clustered commodity computers work in parallel.Distributing the data that is too large across the nodes in clusters solves the problem of having too large data sets to be processed onto the single machine.
8.17.11 big data and hadoop with informatica slideshareJulianna DeLua
This presentation provides a briefing on Big Data and Hadoop and how Informatica's Big Data Integration plays a role to empower the data-centric enterprise.
Learn more about Hitachi Content Platform Anywhere by visiting http://www.hds.com/products/file-and-content/hitachi-content-platform-anywhere.html
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Watch full webinar here: https://bit.ly/2vN59VK
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.
Attend this session 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.
How to Swiftly Operationalize the Data Lake for Advanced Analytics Using a Lo...Denodo
Watch full webinar here: https://bit.ly/3mfFJqb
Presented at Chief Data Officer Live Series 2021, ASEAN (August Edition)
While big data initiatives have become necessary for any business to generate actionable insights, big data fabric has become a necessity for any successful big data initiative. The best-of-breed big data fabrics should deliver actionable insights to the business users with minimal effort, provide end-to-end security to the entire enterprise data platform, and provide real-time data integration while delivering a self-service data platform to business users.
Watch this on-demand session to learn how big data fabric enabled by Data Virtualization:
- Provides lightning fast self-service data access to business users
- Centralizes data security, governance, and data privacy
- Fulfills the promise of data lakes to provide actionable insights
Cloudera and Appfluent provide large enterprises with a proven solution that maximizes data savings and minimizes legacy data warehouse costs. Appfluent’s data usage analytics deliver in-depth visibility into data warehouse and business intelligence systems.
With this comprehensive information, organizations can create a plan for a successful move to Cloudera’s enterprise data hub, powered by Apache Hadoop.
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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.
Chatty Kathy - UNC Bootcamp Final Project Presentation - Final Version - 5.23...John Andrews
SlideShare Description for "Chatty Kathy - UNC Bootcamp Final Project Presentation"
Title: Chatty Kathy: Enhancing Physical Activity Among Older Adults
Description:
Discover how Chatty Kathy, an innovative project developed at the UNC Bootcamp, aims to tackle the challenge of low physical activity among older adults. Our AI-driven solution uses peer interaction to boost and sustain exercise levels, significantly improving health outcomes. This presentation covers our problem statement, the rationale behind Chatty Kathy, synthetic data and persona creation, model performance metrics, a visual demonstration of the project, and potential future developments. Join us for an insightful Q&A session to explore the potential of this groundbreaking project.
Project Team: Jay Requarth, Jana Avery, John Andrews, Dr. Dick Davis II, Nee Buntoum, Nam Yeongjin & Mat Nicholas
Data Centers - Striving Within A Narrow Range - Research Report - MCG - May 2...pchutichetpong
M Capital Group (“MCG”) expects to see demand and the changing evolution of supply, facilitated through institutional investment rotation out of offices and into work from home (“WFH”), while the ever-expanding need for data storage as global internet usage expands, with experts predicting 5.3 billion users by 2023. These market factors will be underpinned by technological changes, such as progressing cloud services and edge sites, allowing the industry to see strong expected annual growth of 13% over the next 4 years.
Whilst competitive headwinds remain, represented through the recent second bankruptcy filing of Sungard, which blames “COVID-19 and other macroeconomic trends including delayed customer spending decisions, insourcing and reductions in IT spending, energy inflation and reduction in demand for certain services”, the industry has seen key adjustments, where MCG believes that engineering cost management and technological innovation will be paramount to success.
MCG reports that the more favorable market conditions expected over the next few years, helped by the winding down of pandemic restrictions and a hybrid working environment will be driving market momentum forward. The continuous injection of capital by alternative investment firms, as well as the growing infrastructural investment from cloud service providers and social media companies, whose revenues are expected to grow over 3.6x larger by value in 2026, will likely help propel center provision and innovation. These factors paint a promising picture for the industry players that offset rising input costs and adapt to new technologies.
According to M Capital Group: “Specifically, the long-term cost-saving opportunities available from the rise of remote managing will likely aid value growth for the industry. Through margin optimization and further availability of capital for reinvestment, strong players will maintain their competitive foothold, while weaker players exit the market to balance supply and demand.”
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).