026 Neo4j Data Loading (ETL_ELT) Best Practices - NODES2022 AMERICAS Advanced...Neo4j
What patterns are most appropriate for building ETLs using Neo4j? In this session, we share how we built the Google Cloud DataFlow flex template using the Neo4j Java API. You can then apply the same approach to building read and write operators in any framework, including AWS Lambda and Google Cloud Functions.
Organizations have been collecting, storing, and accessing data from the beginning of computerization. Insights gained from analyzing the data enable them to identify new opportunities, improve core processes, enable continuous learning and differentiation, remain competitive, and thrive in an increasingly challenging business environment.
The well-established data architecture, consisting of a data warehouse, fed from multiple operational data stores, and fronted by BI tools, has served most organizations well. However, over the last two decades, with the explosion of internet-scale data, and the advent of new approaches to data and computational processing, this tried-and-true data architecture has come under strain, and has created both challenges and opportunities for organizations.
In this green paper, we will discuss modern approaches to data architecture that have evolved to address these challenges and provide a framework for companies to build a data architecture and better adapt to increasing demands of the modern business environment. This discussion of data architecture will be tied to the Data Maturity Journey introduced in EQengineered’s June 2021 green paper on Data Modernization.
026 Neo4j Data Loading (ETL_ELT) Best Practices - NODES2022 AMERICAS Advanced...Neo4j
What patterns are most appropriate for building ETLs using Neo4j? In this session, we share how we built the Google Cloud DataFlow flex template using the Neo4j Java API. You can then apply the same approach to building read and write operators in any framework, including AWS Lambda and Google Cloud Functions.
Organizations have been collecting, storing, and accessing data from the beginning of computerization. Insights gained from analyzing the data enable them to identify new opportunities, improve core processes, enable continuous learning and differentiation, remain competitive, and thrive in an increasingly challenging business environment.
The well-established data architecture, consisting of a data warehouse, fed from multiple operational data stores, and fronted by BI tools, has served most organizations well. However, over the last two decades, with the explosion of internet-scale data, and the advent of new approaches to data and computational processing, this tried-and-true data architecture has come under strain, and has created both challenges and opportunities for organizations.
In this green paper, we will discuss modern approaches to data architecture that have evolved to address these challenges and provide a framework for companies to build a data architecture and better adapt to increasing demands of the modern business environment. This discussion of data architecture will be tied to the Data Maturity Journey introduced in EQengineered’s June 2021 green paper on Data Modernization.
Core Archive for SAP Solutions is a fully-featured archiving and document viewing solution that allows customers to archive content from the main SAP database yet still view and interact with the content directly from the Archive. Core Archive supports the archiving of all content and data from SAP and can leverage SAP ILM disciplines. Content is stored in a compliant manner ensuring that GDPR, CCPA and other standards can be met. Core Archive is entirely cloud-based, reducing the IT footprint and offering rapid time to value.
Talend Interview Questions and Answers | Talend Online Training | Talend Tuto...Edureka!
( Talend Training: https://www.edureka.co/talend-for-big-data)
This Edureka tutorial on Talend Interview Questions will help you to learn about the most frequently asked Talend questions and their answers which will set you apart in the interview process. This video helps you to learn the following topics:
1. Talend MCQ
2. General Talend Questions
3. Talend for Data Integration Questions
4. Talend for Big Data Questions
Here's the deck we used for our Series-A round. We raised $26M led by Benchmark, 2 months after our Seed round with Accel.
Even though we didn't necessarily show the appendix slides, we sent them along with the rest of the deck.
See https://airbyte.com
DataOps - The Foundation for Your Agile Data ArchitectureDATAVERSITY
Achieving agility in data and analytics is hard. It’s no secret that most data organizations struggle to deliver the on-demand data products that their business customers demand. Recently, there has been much hype around new design patterns that promise to deliver this much sought-after agility.
In this webinar, Chris Bergh, CEO and Head Chef of DataKitchen will cut through the noise and describe several elegant and effective data architecture design patterns that deliver low errors, rapid development, and high levels of collaboration. He’ll cover:
• DataOps, Data Mesh, Functional Design, and Hub & Spoke design patterns;
• Where Data Fabric fits into your architecture;
• How different patterns can work together to maximize agility; and
• How a DataOps platform serves as the foundational superstructure for your agile architecture.
Insurance companies are facing similar challenges like all other disrupted market segments like the change of customer expectations and hence the need of differentiating itself new as a brand in a challenging market environment. But at the same time, it underlies a very strict regulatory pressure. Generali Switzerland, as many market leaders in every industry, have understood the power of data to reimagine their markets, customers, products, and business model and managed this change by building their Connection Platform within one year.
Christian Nicoll, Director of Platform Engineering & Operations at Generali Switzerland guides us through their journey of setting up an event-driven architecture to support their digital transformation project.
Attend this online talk and learn more about:
-How Generali managed it to assemble various parts to one platform
-The architecture of the Generali Connection Platform, including Confluent, Kafka, and Attunity.
-Their challenges, best practices, and lessons learned
-Generali’s plans of expanding and scaling the Connection Platform
-Additional Use Cases in regulated markets like retail banking
Phar Data Platform: From the Lakehouse Paradigm to the RealityDatabricks
Despite the increased availability of ready-to-use generic tools, more and more enterprises are deciding to build in-house data platforms. This practice, common for some time in research labs and digital native companies, is now making its waves across large enterprises that traditionally used proprietary solutions and outsourced most of their IT. The availability of large volumes of data, coupled with more and more complex analytical use cases driven by innovations in data science have yielded these traditional and on premise architectures to become obsolete in favor of cloud architectures powered by open source technologies.
The idea of building an in-house platform at a larger enterprise comes with many challenges of its own: Build an Architecture that combines the best elements of data lakes and data warehouses to accommodate all kinds from BI to ML use cases. The need to interoperate with all the company’s data and technology, including legacy systems. Cultural transformation, including a commitment to adopt agile processes and data driven approaches.
This presentation describes a success story on building a Lakehouse in an enterprise such as LIDL, a successful chain of grocery stores operating in 32 countries worldwide. We will dive into the cloud-based architecture for batch and streaming workloads based on many different source systems of the enterprise and how we applied security on architecture and data. We will detail the creation of a curated Data Lake comprising several layers from a raw ingesting layer up to a layer that presents cleansed and enriched data to the business units as a kind of Data Marketplace.
A lot of focus and effort went into building a semantic Data Lake as a sustainable and easy to use basis for the Lakehouse as opposed to just dumping source data into it. The first use case being applied to the Lakehouse is the Lidl Plus Loyalty Program. It is already deployed to production in 26 countries with more than 30 millions of customers’ data being analyzed on a daily basis. In parallel to productionizing the Lakehouse, a cultural and organizational change process was undertaken to get all involved units to buy into the new data driven approach.
DI&A Slides: Data Lake vs. Data WarehouseDATAVERSITY
Modern data analysis is moving beyond the Data Warehouse to the Data Lake where analysts are able to take advantage of emerging technologies to manage complex analytics on large data volumes and diverse data types. Yet, for some business problems, a Data Warehouse may still be the right solution.
If you’re on the fence, join this webinar as we compare and contrast Data Lakes and Data Warehouses, identifying situations where one approach may be better than the other and highlighting how the two can work together.
Get tips, takeaways and best practices about:
- The benefits and problems of a Data Warehouse
- How a Data Lake can solve the problems of a Data Warehouse
- Data Lake Architecture
- How Data Warehouses and Data Lakes can work together
DataOps: An Agile Method for Data-Driven OrganizationsEllen Friedman
DataOps expands DevOps philosophy to include data-heavy roles (data engineering & data science). DataOps uses better cross-functional collaboration for flexibility, fast time to value and an agile workflow for data-intensive applications including machine learning pipelines. (Strata Data San Jose March 2018)
“Opening Pandora’s box” - Why bother data model for ERP systems?
This presentation covers :
a. Why should you bother with data modelling when you’ve got or are planning to get an ERP?
i. For requirements gathering.
ii. For Data migration / take on
iii. Master Data alignment
iv. Data lineage (particularly important with Data Lineage & SoX compliance issues)
v. For reporting (Particularly Business Intelligence & Data Warehousing)
vi. But most importantly, for integration of the ERP metadata into your overall Information Architecture.
b. But don’t you get a data model with the ERP anyway?
i. Errr not with all of them (e.g. SAP) – in fact non of them to our knowledge
ii. What can be leveraged from the vendor?
c. How can you incorporate SAP metadata into your overall model?
i. What are the requirements?
ii. How to get inside the black box
iii. Is there any technology available?
iv. What about DIY?
d. So, what are the overall benefits of doing this:
i. Ease of integration
ii. Fitness for purpose
iii. Reuse of data artefacts
iv. No nasty data surprises
v. Alignment with overall data strategy
Agile & Data Modeling – How Can They Work Together?DATAVERSITY
A tenet of the Agile Manifesto is ‘Working software over comprehensive documentation’, and many have interpreted that to mean that data models are not necessary in the agile development environment. Others have seen the value of data models for achieving the other core tenets of ‘Customer Collaboration’ and ‘Responding to Change’.
This webinar will discuss how data models are being effectively used in today’s Agile development environment and the benefits that are being achieved from this approach.
I gave this presentation at the Advanced Architecture Conference, Bill Inmon, 2011 in Evergreen, Colorado. This presentation covers a new breed of data warehousing called Operational Data Warehousing. These are the next steps in business intelligence towards self-service BI and enabling users to do more with their enterprise data warehouse solution. Specifically, it talks about how the Data Vault model fits in to this picture.
If you would like to use the slides, please e-mail me first, I'd be happy to discuss it with you.
Too often I hear the question “Can you help me with our data strategy?” Unfortunately, for most, this is the wrong request because it focuses on the least valuable component: the data strategy itself. A more useful request is: “Can you help me apply data strategically?” Yes, at early maturity phases the process of developing strategic thinking about data is more important than the actual product! Trying to write a good (must less perfect) data strategy on the first attempt is generally not productive –particularly given the widespread acceptance of Mike Tyson’s truism: “Everybody has a plan until they get punched in the face.” This program refocuses efforts on learning how to iteratively improve the way data is strategically applied. This will permit data-based strategy components to keep up with agile, evolving organizational strategies. It also contributes to three primary organizational data goals. Learn how to improve the following:
- Your organization’s data
- The way your people use data
- The way your people use data to achieve your organizational strategy
This will help in ways never imagined. Data are your sole non-depletable, non-degradable, durable strategic assets, and they are pervasively shared across every organizational area. Addressing existing challenges programmatically includes overcoming necessary but insufficient prerequisites and developing a disciplined, repeatable means of improving business objectives. This process (based on the theory of constraints) is where the strategic data work really occurs as organizations identify prioritized areas where better assets, literacy, and support (data strategy components) can help an organization better achieve specific strategic objectives. Then the process becomes lather, rinse, and repeat. Several complementary concepts are also covered, including:
- A cohesive argument for why data strategy is necessary for effective data governance
- An overview of prerequisites for effective strategic use of data strategy, as well as common pitfalls
- A repeatable process for identifying and removing data constraints
- The importance of balancing business operation and innovation
Core Archive for SAP Solutions is a fully-featured archiving and document viewing solution that allows customers to archive content from the main SAP database yet still view and interact with the content directly from the Archive. Core Archive supports the archiving of all content and data from SAP and can leverage SAP ILM disciplines. Content is stored in a compliant manner ensuring that GDPR, CCPA and other standards can be met. Core Archive is entirely cloud-based, reducing the IT footprint and offering rapid time to value.
Talend Interview Questions and Answers | Talend Online Training | Talend Tuto...Edureka!
( Talend Training: https://www.edureka.co/talend-for-big-data)
This Edureka tutorial on Talend Interview Questions will help you to learn about the most frequently asked Talend questions and their answers which will set you apart in the interview process. This video helps you to learn the following topics:
1. Talend MCQ
2. General Talend Questions
3. Talend for Data Integration Questions
4. Talend for Big Data Questions
Here's the deck we used for our Series-A round. We raised $26M led by Benchmark, 2 months after our Seed round with Accel.
Even though we didn't necessarily show the appendix slides, we sent them along with the rest of the deck.
See https://airbyte.com
DataOps - The Foundation for Your Agile Data ArchitectureDATAVERSITY
Achieving agility in data and analytics is hard. It’s no secret that most data organizations struggle to deliver the on-demand data products that their business customers demand. Recently, there has been much hype around new design patterns that promise to deliver this much sought-after agility.
In this webinar, Chris Bergh, CEO and Head Chef of DataKitchen will cut through the noise and describe several elegant and effective data architecture design patterns that deliver low errors, rapid development, and high levels of collaboration. He’ll cover:
• DataOps, Data Mesh, Functional Design, and Hub & Spoke design patterns;
• Where Data Fabric fits into your architecture;
• How different patterns can work together to maximize agility; and
• How a DataOps platform serves as the foundational superstructure for your agile architecture.
Insurance companies are facing similar challenges like all other disrupted market segments like the change of customer expectations and hence the need of differentiating itself new as a brand in a challenging market environment. But at the same time, it underlies a very strict regulatory pressure. Generali Switzerland, as many market leaders in every industry, have understood the power of data to reimagine their markets, customers, products, and business model and managed this change by building their Connection Platform within one year.
Christian Nicoll, Director of Platform Engineering & Operations at Generali Switzerland guides us through their journey of setting up an event-driven architecture to support their digital transformation project.
Attend this online talk and learn more about:
-How Generali managed it to assemble various parts to one platform
-The architecture of the Generali Connection Platform, including Confluent, Kafka, and Attunity.
-Their challenges, best practices, and lessons learned
-Generali’s plans of expanding and scaling the Connection Platform
-Additional Use Cases in regulated markets like retail banking
Phar Data Platform: From the Lakehouse Paradigm to the RealityDatabricks
Despite the increased availability of ready-to-use generic tools, more and more enterprises are deciding to build in-house data platforms. This practice, common for some time in research labs and digital native companies, is now making its waves across large enterprises that traditionally used proprietary solutions and outsourced most of their IT. The availability of large volumes of data, coupled with more and more complex analytical use cases driven by innovations in data science have yielded these traditional and on premise architectures to become obsolete in favor of cloud architectures powered by open source technologies.
The idea of building an in-house platform at a larger enterprise comes with many challenges of its own: Build an Architecture that combines the best elements of data lakes and data warehouses to accommodate all kinds from BI to ML use cases. The need to interoperate with all the company’s data and technology, including legacy systems. Cultural transformation, including a commitment to adopt agile processes and data driven approaches.
This presentation describes a success story on building a Lakehouse in an enterprise such as LIDL, a successful chain of grocery stores operating in 32 countries worldwide. We will dive into the cloud-based architecture for batch and streaming workloads based on many different source systems of the enterprise and how we applied security on architecture and data. We will detail the creation of a curated Data Lake comprising several layers from a raw ingesting layer up to a layer that presents cleansed and enriched data to the business units as a kind of Data Marketplace.
A lot of focus and effort went into building a semantic Data Lake as a sustainable and easy to use basis for the Lakehouse as opposed to just dumping source data into it. The first use case being applied to the Lakehouse is the Lidl Plus Loyalty Program. It is already deployed to production in 26 countries with more than 30 millions of customers’ data being analyzed on a daily basis. In parallel to productionizing the Lakehouse, a cultural and organizational change process was undertaken to get all involved units to buy into the new data driven approach.
DI&A Slides: Data Lake vs. Data WarehouseDATAVERSITY
Modern data analysis is moving beyond the Data Warehouse to the Data Lake where analysts are able to take advantage of emerging technologies to manage complex analytics on large data volumes and diverse data types. Yet, for some business problems, a Data Warehouse may still be the right solution.
If you’re on the fence, join this webinar as we compare and contrast Data Lakes and Data Warehouses, identifying situations where one approach may be better than the other and highlighting how the two can work together.
Get tips, takeaways and best practices about:
- The benefits and problems of a Data Warehouse
- How a Data Lake can solve the problems of a Data Warehouse
- Data Lake Architecture
- How Data Warehouses and Data Lakes can work together
DataOps: An Agile Method for Data-Driven OrganizationsEllen Friedman
DataOps expands DevOps philosophy to include data-heavy roles (data engineering & data science). DataOps uses better cross-functional collaboration for flexibility, fast time to value and an agile workflow for data-intensive applications including machine learning pipelines. (Strata Data San Jose March 2018)
“Opening Pandora’s box” - Why bother data model for ERP systems?
This presentation covers :
a. Why should you bother with data modelling when you’ve got or are planning to get an ERP?
i. For requirements gathering.
ii. For Data migration / take on
iii. Master Data alignment
iv. Data lineage (particularly important with Data Lineage & SoX compliance issues)
v. For reporting (Particularly Business Intelligence & Data Warehousing)
vi. But most importantly, for integration of the ERP metadata into your overall Information Architecture.
b. But don’t you get a data model with the ERP anyway?
i. Errr not with all of them (e.g. SAP) – in fact non of them to our knowledge
ii. What can be leveraged from the vendor?
c. How can you incorporate SAP metadata into your overall model?
i. What are the requirements?
ii. How to get inside the black box
iii. Is there any technology available?
iv. What about DIY?
d. So, what are the overall benefits of doing this:
i. Ease of integration
ii. Fitness for purpose
iii. Reuse of data artefacts
iv. No nasty data surprises
v. Alignment with overall data strategy
Agile & Data Modeling – How Can They Work Together?DATAVERSITY
A tenet of the Agile Manifesto is ‘Working software over comprehensive documentation’, and many have interpreted that to mean that data models are not necessary in the agile development environment. Others have seen the value of data models for achieving the other core tenets of ‘Customer Collaboration’ and ‘Responding to Change’.
This webinar will discuss how data models are being effectively used in today’s Agile development environment and the benefits that are being achieved from this approach.
I gave this presentation at the Advanced Architecture Conference, Bill Inmon, 2011 in Evergreen, Colorado. This presentation covers a new breed of data warehousing called Operational Data Warehousing. These are the next steps in business intelligence towards self-service BI and enabling users to do more with their enterprise data warehouse solution. Specifically, it talks about how the Data Vault model fits in to this picture.
If you would like to use the slides, please e-mail me first, I'd be happy to discuss it with you.
Too often I hear the question “Can you help me with our data strategy?” Unfortunately, for most, this is the wrong request because it focuses on the least valuable component: the data strategy itself. A more useful request is: “Can you help me apply data strategically?” Yes, at early maturity phases the process of developing strategic thinking about data is more important than the actual product! Trying to write a good (must less perfect) data strategy on the first attempt is generally not productive –particularly given the widespread acceptance of Mike Tyson’s truism: “Everybody has a plan until they get punched in the face.” This program refocuses efforts on learning how to iteratively improve the way data is strategically applied. This will permit data-based strategy components to keep up with agile, evolving organizational strategies. It also contributes to three primary organizational data goals. Learn how to improve the following:
- Your organization’s data
- The way your people use data
- The way your people use data to achieve your organizational strategy
This will help in ways never imagined. Data are your sole non-depletable, non-degradable, durable strategic assets, and they are pervasively shared across every organizational area. Addressing existing challenges programmatically includes overcoming necessary but insufficient prerequisites and developing a disciplined, repeatable means of improving business objectives. This process (based on the theory of constraints) is where the strategic data work really occurs as organizations identify prioritized areas where better assets, literacy, and support (data strategy components) can help an organization better achieve specific strategic objectives. Then the process becomes lather, rinse, and repeat. Several complementary concepts are also covered, including:
- A cohesive argument for why data strategy is necessary for effective data governance
- An overview of prerequisites for effective strategic use of data strategy, as well as common pitfalls
- A repeatable process for identifying and removing data constraints
- The importance of balancing business operation and innovation
Modernising Data Architecture for Data Driven Insights (Chinese)Denodo
Watch full webinar here: https://bit.ly/3phVEEv
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 organisations take towards accessing, integrating, and provisioning data required to meet business goals.
As data analytics and data-driven intelligence takes center 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.
Register this webinar to learn:
- How you can meet the challenges of delivering data insights with data virtualization
- Why Data Virtualization is increasingly find enterprise-wide adoption
- How customers are reducing costs and delivering faster insight
How Enterprises Leverage Data to Overcome Business Challenges During CoronavirusDenodo
Watch full webinar here: https://bit.ly/2Jgb1uc
Coronavirus is spreading all over the world and has big impact on all the industries. How to acquire latest virus information from different countries and regions in real time to help organizations strategically plan and take actions accordingly and timely becomes very important.
Attend this webinar to learn:
- How business department acquires trustworthy data, gain deeper insights and fasten decision making
- How IT easily supports dynamic business requirements in real time
Advanced Analytics and Machine Learning with Data Virtualization (Chinese)Denodo
Watch full webinar here: https://bit.ly/3mLNJ1J
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 spent 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.
Attend this webinar and learn:
- How data virtualization can accelerate data acquisition and massaging, providing the data scientist with a powerful tool to complement their practice
- How popular tools from the data science ecosystem: Spark, Python, Zeppelin, Jupyter, etc. integrate with Denodo
- How you can use the Denodo Platform with large data volumes in an efficient way
- How Prologis accelerated their use of Machine Learning with data virtualization
2012.05.24 於 「Big Data Taiwan 2012」的 Keynote 講稿。
主講者:Etu 副總經理/ 蔣居裕
《議題簡介》
無論是企業區域網路,還是開放的網際網路,在巨大的結構化與非結構化資料的背後,其實充滿著各種行為意圖,以及人、事、物、時、地的多維度關聯。商業的日益競爭,已經來到了一個除了講求行銷創意,還要擁有巨量資料處理與分析技術,才能出奇制勝的時代。有人形容 Big Data 的價值挖掘,就像是在攪拌混凝土,若在尚未完成前就中斷,將導致前功盡棄,全無可用的窘境。對 Big Data 的意圖與關聯探索,必須是 End-to-End 全程的照料,方得實現。本議程將舉例說明這個有序到永續的過程,讓聽者更能領略意圖與關聯充滿的世界。
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
6. 6
不同使用群组的需求
60% of employees
数据消费者 数据探索
30% of employees
8% of employees
数据分析
普通用户
高级用户
数据科学家
2% of employees
‘WHITE
GLOVE’
服务
自助服务
Top
Down
Bottom
Up
高手在民间