This document discusses Klarna Tech Talk on managing data. It provides an overview of IBM's data integration, governance, and big data capabilities. IBM states it can help clients turn information into insights, deepen engagement, enable agile business, accelerate innovation, deliver enterprise mobility, optimize infrastructure, and manage risk through technology innovations like big data analytics, security intelligence, cloud computing, and mobile solutions. The document promotes IBM's data fabric and smart data solutions for integrating, governing, and providing access to data across an organization.
A modern approach to streaming data integration, event processing with a big data (kappa style) data architecture. Key patterns are discussed with pros/cons of newer approaches and open source technologies. Focus on Oracle and GoldenGate technology. OpenWorld 2018 presentation.
Strata 2015 presentation from Oracle for Big Data - we are announcing several new big data products including GoldenGate for Big Data, Big Data Discovery, Oracle Big Data SQL and Oracle NoSQL
GoldenGate and Stream Processing with Special Guest RakutenJeffrey T. Pollock
Oracle OpenWorld roadmap presentation for GoldenGate, stream processing, analytics and big data use cases with special guest presenters from Rakuten Travel.
CON6619 - OpenWorld Presentation. Oracle data integration, big data, data governance, and cloud integration. Replication, ETL, Data Quality, Streaming Big Data, and Data Preparation
A modern approach to streaming data integration, event processing with a big data (kappa style) data architecture. Key patterns are discussed with pros/cons of newer approaches and open source technologies. Focus on Oracle and GoldenGate technology. OpenWorld 2018 presentation.
Strata 2015 presentation from Oracle for Big Data - we are announcing several new big data products including GoldenGate for Big Data, Big Data Discovery, Oracle Big Data SQL and Oracle NoSQL
GoldenGate and Stream Processing with Special Guest RakutenJeffrey T. Pollock
Oracle OpenWorld roadmap presentation for GoldenGate, stream processing, analytics and big data use cases with special guest presenters from Rakuten Travel.
CON6619 - OpenWorld Presentation. Oracle data integration, big data, data governance, and cloud integration. Replication, ETL, Data Quality, Streaming Big Data, and Data Preparation
Oracle OpenWorld London - session for Stream Analysis, time series analytics, streaming ETL, streaming pipelines, big data, kafka, apache spark, complex event processing
This is Part 4 of the GoldenGate series on Data Mesh - a series of webinars helping customers understand how to move off of old-fashioned monolithic data integration architecture and get ready for more agile, cost-effective, event-driven solutions. The Data Mesh is a kind of Data Fabric that emphasizes business-led data products running on event-driven streaming architectures, serverless, and microservices based platforms. These emerging solutions are essential for enterprises that run data-driven services on multi-cloud, multi-vendor ecosystems.
Join this session to get a fresh look at Data Mesh; we'll start with core architecture principles (vendor agnostic) and transition into detailed examples of how Oracle's GoldenGate platform is providing capabilities today. We will discuss essential technical characteristics of a Data Mesh solution, and the benefits that business owners can expect by moving IT in this direction. For more background on Data Mesh, Part 1, 2, and 3 are on the GoldenGate YouTube channel: https://www.youtube.com/playlist?list=PLbqmhpwYrlZJ-583p3KQGDAd6038i1ywe
Webinar Speaker: Jeff Pollock, VP Product (https://www.linkedin.com/in/jtpollock/)
Mr. Pollock is an expert technology leader for data platforms, big data, data integration and governance. Jeff has been CTO at California startups and a senior exec at Fortune 100 tech vendors. He is currently Oracle VP of Products and Cloud Services for Data Replication, Streaming Data and Database Migrations. While at IBM, he was head of all Information Integration, Replication and Governance products, and previously Jeff was an independent architect for US Defense Department, VP of Technology at Cerebra and CTO of Modulant – he has been engineering artificial intelligence based data platforms since 2001. As a business consultant, Mr. Pollock was a Head Architect at Ernst & Young’s Center for Technology Enablement. Jeff is also the author of “Semantic Web for Dummies” and "Adaptive Information,” a frequent keynote at industry conferences, author for books and industry journals, formerly a contributing member of W3C and OASIS, and an engineering instructor with UC Berkeley’s Extension for object-oriented systems, software development process and enterprise architecture.
Oracle's BigData solutions consist of a number of new products and solutions to support customers looking to gain maximum business value from data sets such as weblogs, social media feeds, smart meters, sensors and other devices that generate massive volumes of data (commonly defined as ‘Big Data’) that isn’t readily accessible in enterprise data warehouses and business intelligence applications today.
Slides from a presentation I gave at the 5th SOA, Cloud + Service Technology Symposium (September 2012, Imperial College, London). The goal of this presentation was to explore with the audience use cases at the intersection of SOA, Big Data and Fast Data. If you are working with both SOA and Big Data I would would be very interested to hear about your projects.
This presentation was delivered at the BI SIG in Palo Alto. It provides an overview of the market shift away from on-premise solutions to on-demand in the business intelligence industry.
Data Science Operationalization: The Journey of Enterprise AIDenodo
Watch full webinar here: https://bit.ly/3kVmYJl
As we move into a world driven by AI initiatives, we find ourselves facing new and diverse challenges when it comes to operationalization. Creating a solution and putting it into practice, is certainly not the same. The challenges span various organizational and data facades. In many instances, the data scientists may be working in silos and connecting to the live data may not always be possible. But how does one guarantee their developed model in a silo is still relevant to live data? How can we manage the data flow and data access across the entire AI operationalization cycle?
Watch on-demand to explore:
- The journey and challenges of the Data Scientist
- How Denodo data virtualization with data movement streamlines operationalization
- The best practices and techniques when dealing with siloed data
- How customers have used data virtualization in their data science initiatives
Insurance companies of all sizes are challenged to keep up with emerging technologies that deliver a competitive advantage. Recording: https://www.brighttalk.com/webcast/9573/192877
Big data holds the key to greater customer insight and stronger customer relationships. But risk of sensitive data exposure — and compliance violations — keeps many insurers from pursuing big data initiatives and reaping the rewards of business-driven analytics. Join Dataguise and Hortonworks for this live webinar to learn how you can free your organization from traditional information security constraints and unlock the power of your most valuable business assets.
• What do you need to know about PII/PHI privacy before embarking on big data initiatives?
• Why do so many big data initiatives fail before they’ve even begun—and what can you do about it?
• How can IT security organizations help data scientists extract more business value from their data?
• How are leading insurance companies leveraging big data to gain competitive advantage?
Journey to Big Data: Main Issues, Solutions, BenefitsDataWorks Summit
One of the most fruit aspects of being chosen as a partner bank is that you can have a backend that can communicate directly with the client's system. With this partnership, Banco Santander has led to running a large series of third party applications on their banking system for many years.
Banking is the most regulated sector to make day-to-day operations more interesting. Adapting the system to regulation is not optional and is mandatory. For today's banks internal and external audits are an important routine. Furthermore, considering that SCIB is a global player, this pattern is repeated in each country where the group exists.
It can be said that it is a really interesting compound! Various kinds of third party systems are installed in many countries, coexisting with our centralized system, transmitting information mutually, being adjusted manually, data is aggregated / integrated at the back office. Spaghetti comes to mind when considering that all data comes and goes without delay. More and more, regulators and auditors are able to perfectly identify the origin of each data. This often means that you need to manually interfere in order to fully locate the data.
Javier Nieto, active in Banco Santander's corporate investment banking architecture and innovation department, talks about integration challenges that Santander experienced when building an on-demand Data Lake to move to global big data.
Active Governance Across the Delta Lake with AlationDatabricks
Alation provides a single interface to provide users and stewards to provide active and agile data governance across Databricks Delta Lake and Databricks SQL Analytics Service. Understand how Alation can expand adoption in the data lake while providing safe and responsible data consumption.
Hortonworks Oracle Big Data Integration Hortonworks
Slides from joint Hortonworks and Oracle webinar on November 11, 2014. Covers the Modern Data Architecture with Apache Hadoop and Oracle Data Integration products.
How to Capitalize on Big Data with Oracle Analytics CloudPerficient, Inc.
The average age of a company listed on the S&P 500 has fallen from almost 60 years old in the 1950s to less than 20 years old today. Innovative companies that are willing to embrace transformative technologies make the list today, while businesses that are hesitant to embrace change risk becoming obsolete.
Innovators use big data solutions as a competitive advantage to increase revenue, reduce cost, and improve cash flow. Turn big data into actionable insights with Oracle Analytics Cloud.
We identified the big data opportunities in front of you and how to take advantage of them:
-Big data and its architecture
-Why a big data strategy is imperative to remaining relevant
-How Oracle Analytics Cloud can help you connect people, places, data, and systems to fundamentally change how you analyze, understand, and act on information
Data Offload for the Chief Data Officer – how to move data onto Hadoop withou...DataWorks Summit
The CDO bears responsibility for the firm’s data and information strategy, governance, control, policy development, and exploitation of data assets to create business value” Source – Gartner
In this session we will show how the CDO can manage and exploit all of a company’s data assets on Hadoop, in a controlled manner where the quality of the data is verified and security access is controlled, and all data activities are logged and recorded automatically on Atlas. We will demonstrate how to use Bluemetrix Data Manager (BDM) and show how easy it is to ingest, transform and control data on Hadoop, while automatically deploying governance on Atlas.
Speaker
Liam English, CEO, Bluemetrix
Big Data LDN 2018: DATA MANAGEMENT AUTOMATION AND THE INFORMATION SUPPLY CHAI...Matt Stubbs
Date: 14th November 2018
Location: Governance and MDM Theatre
Time: 10:30 - 11:00
Speaker: Mike Ferguson
Organisation: IBS
About: For most organisations today, data complexity has increased rapidly. In the area of operations, we now have cloud and on-premises OLTP systems with customers, partners and suppliers accessing these applications via APIs and mobile apps. In the area of analytics, we now have data warehouse, data marts, big data Hadoop systems, NoSQL databases, streaming data platforms, cloud storage, cloud data warehouses, and IoT-generated data being created at the edge. Also, the number of data sources is exploding as companies ingest more and more external data such as weather and open government data. Silos have also appeared everywhere as business users are buying in self-service data preparation tools without consideration for how these tools integrate with what IT is using to integrate data. Yet new regulations are demanding that we do a better job of governing data, and business executives are demanding more agility to remain competitive in a digital economy. So how can companies remain agile, reduce cost and reduce the time-to-value when data complexity is on the up?
In this session, Mike will discuss how companies can create an information supply chain to manufacture business-ready data and analytics to reduce time to value and improve agility while also getting data under control.
Analyst Webinar: Best Practices In Enabling Data-Driven Decision MakingDenodo
Watch full webinar here: https://bit.ly/37YkgN4
This presentation looks at the trends that are emerging from companies on their journeys to becoming data-driven enterprises.
These trends are taken from a survey of 500 companies and highlight critical success factors, what companies are doing, their progress so far and their plans going forward. It also looks at the role that data virtualization has within the data driven enterprise.
During the session we'll address:
- What is a data-driven enterprise?
- What are the critical success factors?
- What are companies doing to create a data-driven enterprise and why?
- What progress are they making?
- What are the plans on people, process and technologies?
- Why is data virtualization central to provisioning and accessing data in a data-driven enterprise?
- How should you get started?
Oracle OpenWorld London - session for Stream Analysis, time series analytics, streaming ETL, streaming pipelines, big data, kafka, apache spark, complex event processing
This is Part 4 of the GoldenGate series on Data Mesh - a series of webinars helping customers understand how to move off of old-fashioned monolithic data integration architecture and get ready for more agile, cost-effective, event-driven solutions. The Data Mesh is a kind of Data Fabric that emphasizes business-led data products running on event-driven streaming architectures, serverless, and microservices based platforms. These emerging solutions are essential for enterprises that run data-driven services on multi-cloud, multi-vendor ecosystems.
Join this session to get a fresh look at Data Mesh; we'll start with core architecture principles (vendor agnostic) and transition into detailed examples of how Oracle's GoldenGate platform is providing capabilities today. We will discuss essential technical characteristics of a Data Mesh solution, and the benefits that business owners can expect by moving IT in this direction. For more background on Data Mesh, Part 1, 2, and 3 are on the GoldenGate YouTube channel: https://www.youtube.com/playlist?list=PLbqmhpwYrlZJ-583p3KQGDAd6038i1ywe
Webinar Speaker: Jeff Pollock, VP Product (https://www.linkedin.com/in/jtpollock/)
Mr. Pollock is an expert technology leader for data platforms, big data, data integration and governance. Jeff has been CTO at California startups and a senior exec at Fortune 100 tech vendors. He is currently Oracle VP of Products and Cloud Services for Data Replication, Streaming Data and Database Migrations. While at IBM, he was head of all Information Integration, Replication and Governance products, and previously Jeff was an independent architect for US Defense Department, VP of Technology at Cerebra and CTO of Modulant – he has been engineering artificial intelligence based data platforms since 2001. As a business consultant, Mr. Pollock was a Head Architect at Ernst & Young’s Center for Technology Enablement. Jeff is also the author of “Semantic Web for Dummies” and "Adaptive Information,” a frequent keynote at industry conferences, author for books and industry journals, formerly a contributing member of W3C and OASIS, and an engineering instructor with UC Berkeley’s Extension for object-oriented systems, software development process and enterprise architecture.
Oracle's BigData solutions consist of a number of new products and solutions to support customers looking to gain maximum business value from data sets such as weblogs, social media feeds, smart meters, sensors and other devices that generate massive volumes of data (commonly defined as ‘Big Data’) that isn’t readily accessible in enterprise data warehouses and business intelligence applications today.
Slides from a presentation I gave at the 5th SOA, Cloud + Service Technology Symposium (September 2012, Imperial College, London). The goal of this presentation was to explore with the audience use cases at the intersection of SOA, Big Data and Fast Data. If you are working with both SOA and Big Data I would would be very interested to hear about your projects.
This presentation was delivered at the BI SIG in Palo Alto. It provides an overview of the market shift away from on-premise solutions to on-demand in the business intelligence industry.
Data Science Operationalization: The Journey of Enterprise AIDenodo
Watch full webinar here: https://bit.ly/3kVmYJl
As we move into a world driven by AI initiatives, we find ourselves facing new and diverse challenges when it comes to operationalization. Creating a solution and putting it into practice, is certainly not the same. The challenges span various organizational and data facades. In many instances, the data scientists may be working in silos and connecting to the live data may not always be possible. But how does one guarantee their developed model in a silo is still relevant to live data? How can we manage the data flow and data access across the entire AI operationalization cycle?
Watch on-demand to explore:
- The journey and challenges of the Data Scientist
- How Denodo data virtualization with data movement streamlines operationalization
- The best practices and techniques when dealing with siloed data
- How customers have used data virtualization in their data science initiatives
Insurance companies of all sizes are challenged to keep up with emerging technologies that deliver a competitive advantage. Recording: https://www.brighttalk.com/webcast/9573/192877
Big data holds the key to greater customer insight and stronger customer relationships. But risk of sensitive data exposure — and compliance violations — keeps many insurers from pursuing big data initiatives and reaping the rewards of business-driven analytics. Join Dataguise and Hortonworks for this live webinar to learn how you can free your organization from traditional information security constraints and unlock the power of your most valuable business assets.
• What do you need to know about PII/PHI privacy before embarking on big data initiatives?
• Why do so many big data initiatives fail before they’ve even begun—and what can you do about it?
• How can IT security organizations help data scientists extract more business value from their data?
• How are leading insurance companies leveraging big data to gain competitive advantage?
Journey to Big Data: Main Issues, Solutions, BenefitsDataWorks Summit
One of the most fruit aspects of being chosen as a partner bank is that you can have a backend that can communicate directly with the client's system. With this partnership, Banco Santander has led to running a large series of third party applications on their banking system for many years.
Banking is the most regulated sector to make day-to-day operations more interesting. Adapting the system to regulation is not optional and is mandatory. For today's banks internal and external audits are an important routine. Furthermore, considering that SCIB is a global player, this pattern is repeated in each country where the group exists.
It can be said that it is a really interesting compound! Various kinds of third party systems are installed in many countries, coexisting with our centralized system, transmitting information mutually, being adjusted manually, data is aggregated / integrated at the back office. Spaghetti comes to mind when considering that all data comes and goes without delay. More and more, regulators and auditors are able to perfectly identify the origin of each data. This often means that you need to manually interfere in order to fully locate the data.
Javier Nieto, active in Banco Santander's corporate investment banking architecture and innovation department, talks about integration challenges that Santander experienced when building an on-demand Data Lake to move to global big data.
Active Governance Across the Delta Lake with AlationDatabricks
Alation provides a single interface to provide users and stewards to provide active and agile data governance across Databricks Delta Lake and Databricks SQL Analytics Service. Understand how Alation can expand adoption in the data lake while providing safe and responsible data consumption.
Hortonworks Oracle Big Data Integration Hortonworks
Slides from joint Hortonworks and Oracle webinar on November 11, 2014. Covers the Modern Data Architecture with Apache Hadoop and Oracle Data Integration products.
How to Capitalize on Big Data with Oracle Analytics CloudPerficient, Inc.
The average age of a company listed on the S&P 500 has fallen from almost 60 years old in the 1950s to less than 20 years old today. Innovative companies that are willing to embrace transformative technologies make the list today, while businesses that are hesitant to embrace change risk becoming obsolete.
Innovators use big data solutions as a competitive advantage to increase revenue, reduce cost, and improve cash flow. Turn big data into actionable insights with Oracle Analytics Cloud.
We identified the big data opportunities in front of you and how to take advantage of them:
-Big data and its architecture
-Why a big data strategy is imperative to remaining relevant
-How Oracle Analytics Cloud can help you connect people, places, data, and systems to fundamentally change how you analyze, understand, and act on information
Data Offload for the Chief Data Officer – how to move data onto Hadoop withou...DataWorks Summit
The CDO bears responsibility for the firm’s data and information strategy, governance, control, policy development, and exploitation of data assets to create business value” Source – Gartner
In this session we will show how the CDO can manage and exploit all of a company’s data assets on Hadoop, in a controlled manner where the quality of the data is verified and security access is controlled, and all data activities are logged and recorded automatically on Atlas. We will demonstrate how to use Bluemetrix Data Manager (BDM) and show how easy it is to ingest, transform and control data on Hadoop, while automatically deploying governance on Atlas.
Speaker
Liam English, CEO, Bluemetrix
Big Data LDN 2018: DATA MANAGEMENT AUTOMATION AND THE INFORMATION SUPPLY CHAI...Matt Stubbs
Date: 14th November 2018
Location: Governance and MDM Theatre
Time: 10:30 - 11:00
Speaker: Mike Ferguson
Organisation: IBS
About: For most organisations today, data complexity has increased rapidly. In the area of operations, we now have cloud and on-premises OLTP systems with customers, partners and suppliers accessing these applications via APIs and mobile apps. In the area of analytics, we now have data warehouse, data marts, big data Hadoop systems, NoSQL databases, streaming data platforms, cloud storage, cloud data warehouses, and IoT-generated data being created at the edge. Also, the number of data sources is exploding as companies ingest more and more external data such as weather and open government data. Silos have also appeared everywhere as business users are buying in self-service data preparation tools without consideration for how these tools integrate with what IT is using to integrate data. Yet new regulations are demanding that we do a better job of governing data, and business executives are demanding more agility to remain competitive in a digital economy. So how can companies remain agile, reduce cost and reduce the time-to-value when data complexity is on the up?
In this session, Mike will discuss how companies can create an information supply chain to manufacture business-ready data and analytics to reduce time to value and improve agility while also getting data under control.
Analyst Webinar: Best Practices In Enabling Data-Driven Decision MakingDenodo
Watch full webinar here: https://bit.ly/37YkgN4
This presentation looks at the trends that are emerging from companies on their journeys to becoming data-driven enterprises.
These trends are taken from a survey of 500 companies and highlight critical success factors, what companies are doing, their progress so far and their plans going forward. It also looks at the role that data virtualization has within the data driven enterprise.
During the session we'll address:
- What is a data-driven enterprise?
- What are the critical success factors?
- What are companies doing to create a data-driven enterprise and why?
- What progress are they making?
- What are the plans on people, process and technologies?
- Why is data virtualization central to provisioning and accessing data in a data-driven enterprise?
- How should you get started?
Die Big Data Fabric als Enabler für Machine Learning & AIDenodo
Ansehen: https://bit.ly/2Cet17K
Erstklassige Big Data Fabrics liefern verlässliche Insights, gewährleisten höchste End-to-End Sicherheitsstandards und ermöglichen eine konsistente Datenintegration in Echtzeit – während den Business-Anwendern agile Werkzeuge zum selbstgesteuerten Datenkonsum bereitgestellt werden.
Erfahren Sie in dem Vortrag, wie die Big Data Fabric als Enabler für ML & AI:
- den Business-Anwendern und Data Scientists einen schnellen und agilen Datenzugriff via Self-Services ermöglicht
- Data Governance und Security Richtlinien zentral und verlässlich managebar macht
- relevante Insights aus aktuellen und konsistenten Daten liefert
How a Logical Data Fabric Enhances the Customer 360 ViewDenodo
Watch full webinar here: https://bit.ly/3GI802M
Organisations have struggled for years in understanding their customers, this has mainly been due to not having the right data available at the right point in time. In this session we will discuss the role of Data Virtualization in providing customer 360 degree view and look at some of the success stories our customers have told us about.
Accelerate Digital Transformation with Data Virtualization in Banking, Financ...Denodo
Watch full webinar here: https://bit.ly/38uCCUB
Banking, Financial Services and Insurance (BFSI) organizations are globally accelerating their digital journey, making rapid strides with their digitization efforts, and adding key capabilities to adapt and innovate in the new normal.
Many companies find digital transformation challenging as they rely on established systems that are often not only poorly integrated, but also highly resistant to modernization without downtime. Hear how the BFSI industry is leveraging data virtualization that facilitates digital transformation via a modern data integration / data delivery approach to gain greater agility, flexibility, and efficiency.
In this joint live webinar session from Denodo and Wipro, you will learn:
- Industry key trends and challenges driving the digital transformation mandate and platform modernization initiatives
- Key concepts of Data Virtualization, and how it can enable BFSI customers to develop critical capabilities for real-time / near real-time data integration
- Success Stories on organizations who already use data virtualization to differentiate themselves from the competition
- Wipro’s role in helping enterprises define the business case, end-to-end services and operating model for the successful data virtualization implementations
Schedule a Discovery Session to learn more about Wipro and Denodo joint solutions for Banking, Financial Services, and Insurance.
Data Virtualization: Introduction and Business Value (UK)Denodo
Watch full webinar here: https://bit.ly/30mHuYH
What started to evolve as the most agile and real-time enterprise data fabric, data virtualization is proving to go beyond its initial promise and is becoming one of the most important enterprise big data fabrics. Denodo’s vision is to provide a unified data delivery layer as a logical data fabric, to bridge the gap between the IT and the business, hiding the underlying complexity and creating a semantic layer to expose data in a business friendly manner.
Attend this webinar to learn:
- What data virtualization really is
- How it differs from other enterprise data integration technologies
- Why data virtualization is finding enterprise-wide deployment inside some of the largest organizations
- Business Value of data virtualization and customer use cases
- Highlights of the newly launched Denodo Platform 8.0
Building the Artificially Intelligent EnterpriseDatabricks
This session looks at where we are today with data and analytics and what is needed to transition to the Artificially Intelligent Enterprise.
How do you mobilise developers to exploit what data scientists and business analysts have built? How do you align it all with business strategy to maximise business outcomes? How do you combine BI, predictive and prescriptive analytics, automation and reinforcement learning to get maximum value across the enterprise? What is the blueprint for building the artificially intelligent enterprise?
•Data and analytics – Where are we?
•Why is the journey only half-way done?
•2021 and beyond – The new era of AI usage and not just build
•The requirement – event-driven, on-demand and automated analytics
•Operationalising what you build – DataOps, MLOps and RPA
•Mobilising the masses to integrate AI into processes – what needs to be done?
•Business strategy alignment – the guiding light to AI utilisation for high reward
•Agility step change – the shift to no-code integration of AI by citizen developers
•Recording decisions, and analysing business impact
•Reinforcement-learning – transitioning to continuous reward
Is your big data journey stalling? Take the Leap with Capgemini and ClouderaCloudera, Inc.
Transitioning to a Big Data architecture is a big step; and the complexity of moving existing analytical services onto modern platforms like Cloudera, can seem overwhelming.
DataOps - Big Data and AI World London - March 2020 - Harvinder AtwalHarvinder Atwal
Title
DataOps, the secret weapon for delivering AI, data science, and business intelligence value at speed.
Synopsis
● According to recent research, just 7.3% of organisations say the state of their data and analytics is excellent, and only 22% of companies are currently seeing a significant return from data science expenditure.
● Poor returns on data & analytics investment are often the result of applying 20th-century thinking to 21st-century challenges and opportunities.
● Modern data science and analytics require secure, efficient processes to turn raw data from multiple sources and in numerous formats into useful inputs to a data product.
● Developing, orchestrating and iterating modern data pipelines is an extremely complex process requiring multiple technologies and skills.
● Other domains have to successfully overcome the challenge of delivering high-quality products at speed in complex environments. DataOps applies proven agile principles, lean thinking and DevOps practices to the development of data products.
● A DataOps approach aligns data producers, analytical data consumers, processes and technology with the rest of the organisation and its goals.
Fast Data Strategy Houston Roadshow PresentationDenodo
Fast Data Strategy Houston Roadshow focused on the next industrial revolution on the horizon, driven by the application of big data, IoT and Cloud technologies.
• Denodo’s innovative customer, Anadarko, elaborated on how data virtualization serves as the key component in their prescriptive and predictive analytics initiatives, driven by multi-structured data ranging from customer data to equipment data.
• Denodo’s session, Unleashing the Power of Data, described the complexity of the modern data ecosystem and how to overcome challenges and successfully harness insights.
• Our Partner Noah Consulting, an expert analytics solutions provider in the energy industry, explained how your peers are innovating using new business models and reducing cost in areas such as Asset Management and Operations by leveraging Data Virtualization and Prescriptive and Predictive Analytics.
For more information on upcoming roadshows near you, follow this link: https://goo.gl/WBDHiE
Denodo Partner Connect: A Review of the Top 5 Differentiated Use Cases for th...Denodo
Watch full webinar here: https://buff.ly/46pRfV7
This Denodo session explores the power of data virtualization, shedding light on its architecture, customer value, and a diverse range of use cases. Attendees will discover how the Denodo Platform enables seamless connectivity to various data sources while effortlessly combining, cleansing, and delivering data through 5 differentiated use cases.
Architecture: Delve into the core architecture of the Denodo Platform and learn how it empowers organizations to create a unified virtual data layer. Understand how data is accessed, integrated, and delivered in a real-time, agile manner.
Value for the Customer: Explore the tangible benefits that Denodo offers to its customers. From cost savings to improved decision-making, discover how the Denodo Platform helps organizations derive maximum value from their data assets.
Five Different Use Cases: Uncover five real-world use cases where Denodo's data virtualization platform has made a significant impact. From data governance to analytics, Denodo proves its versatility across a variety of domains.
- Logical Data Fabric
- Self Service Analytics
- Data Governance
- 360 degree of Entities
- Hybrid/Multi-Cloud Integration
Watch this illuminating session to gain insights into the transformative capabilities of the Denodo Platform.
Data Virtualization, a Strategic IT Investment to Build Modern Enterprise Dat...Denodo
This content was presented during the Smart Data Summit Dubai 2015 in the UAE on May 25, 2015, by Jesus Barrasa, Senior Solutions Architect at Denodo Technologies.
In the era of Big Data, IoT, Cloud and Social Media, Information Architects are forced to rethink how to tackle data management and integration in the enterprise. Traditional approaches based on data replication and rigid information models lack the flexibility to deal with this new hybrid reality. New data sources and an increasing variety of consuming applications, like mobile apps and SaaS, add more complexity to the problem of delivering the right data, in the right format, and at the right time to the business. Data Virtualization emerges in this new scenario as the key enabler of agile, maintainable and future-proof data architectures.
KASHTECH AND DENODO: ROI and Economic Value of Data VirtualizationDenodo
Watch full webinar here: https://bit.ly/3sumuL5
Join KashTech and Denodo to discover how Data Virtualization can help accelerate your time-to-value from data while reducing the costs at the same time.
Gartner has predicted that organizations using Data Virtualization will spend 40% less on data integration than those using traditional technologies. Denodo customers have experienced time-to-deliver improvements of up to 90% within their data provisioning processes and cost savings of 50% or more. As Rod Tidwell (Cuba Gooding Jr.) said in the movie 'Jerry Maguire', "Show me the money!"
Register to attend and learn how Data Virtualization can:
- Accelerate the delivery of data to users
- Drive digital transformation initiatives
- Reduce project costs and timelines
- Quickly deliver value to your organization
Rethink Your 2021 Data Management Strategy with Data Virtualization (ASEAN)Denodo
Watch full webinar here: https://bit.ly/2O2r3NP
In the last several decades, BI has evolved from large, monolithic implementations controlled by IT to orchestrated sets of smaller, more agile capabilities that include visual-based data discovery and governance. These new capabilities provide more democratic analytics accessibility that is increasingly being controlled by business users. However, given the rapid advancements in emerging technologies such as cloud and big data systems and the fast changing business requirements, creating a future-proof data management strategy is an incredibly complex task.
Catch this on demand session to understand:
- BI program modernization challenges
- What is data virtualization and why is its adoption growing so quickly?
- How data virtualization works and how it compares to alternative approaches to data integration
- How modern data virtualization can significantly increase agility while reducing costs
Modern data management using Kappa and streaming architectures, including discussion by EBay's Connie Yang about the Rheos platform and the use of Oracle GoldenGate, Kafka, Flink, etc.
this is part 3 of the series on Data Mesh ... looking at the intersection of microservices architecture concepts, data integration / replication technologies and log-based stream integration techniques. This webinar was mostly a demonstration, but several slides used to setup the demo are included here as a PDF for viewers.
Deep-dive into Microservices Patterns with Replication and Stream Analytics
Target Audience: Microservices and Data Architects
This is an informational presentation about microservices event patterns, GoldenGate event replication, and event stream processing with Oracle Stream Analytics. This session will discuss some of the challenges of working with data in a microservices architecture (MA), and how the emerging concept of a “Data Mesh” can go hand-in-hand to improve microservices-based data management patterns. You may have already heard about common microservices patterns like CQRS, Saga, Event Sourcing and Transaction Outbox; we’ll share how GoldenGate can simplify these patterns while also bringing stronger data consistency to your microservice integrations. We will also discuss how complex event processing (CEP) and stream processing can be used with event-driven MA for operational and analytical use cases.
Business pressures for modernization and digital transformation drive demand for rapid, flexible DevOps, which microservices address, but also for data-driven Analytics, Machine Learning and Data Lakes which is where data management tech really shines. Join us for this presentation where we take a deep look at the intersection of microservice design patterns and modern data integration tech.
Webinar future dataintegration-datamesh-and-goldengatekafkaJeffrey T. Pollock
The Future of Data Integration: Data Mesh, and a Special Deep Dive into Stream Processing with GoldenGate, Apache Kafka and Apache Spark. This video is a replay of a Live Webinar hosted on 03/19/2020.
Join us for a timely 45min webinar to see our take on the future of Data Integration. As the global industry shift towards the “Fourth Industrial Revolution” continues, outmoded styles of centralized batch processing and ETL tooling continue to be replaced by realtime, streaming, microservices and distributed data architecture patterns.
This webinar will start with a brief look at the macro-trends happening around distributed data management and how that affects Data Integration. Next, we’ll discuss the event-driven integrations provided by GoldenGate Big Data, and continue with a deep-dive into some essential patterns we see when replicating Database change events into Apache Kafka. In this deep-dive we will explain how to effectively deal with issues like Transaction Consistency, Table/Topic Mappings, managing the DB Change Stream, and various Deployment Topologies to consider. Finally, we’ll wrap up with a brief look into how Stream Processing will help to empower modern Data Integration by supplying realtime data transformations, time-series analytics, and embedded Machine Learning from within data pipelines.
GoldenGate: https://www.oracle.com/middleware/tec...
Webinar Speaker: Jeff Pollock, VP Product (https://www.linkedin.com/in/jtpollock/)
Brief training targeted to middle school aged students who are participating in First Lego League robotics and planning to use a version control tool such as EV3Hub
This is a brief technology introduction to Oracle Stream Analytics, and how to use the platform to develop streaming data pipelines that support a wide variety of industry use cases
Presentation to discuss major shift in enterprise data management. Describes movement away from older hub and spoke data architecture and towards newer, more modern Kappa data architecture
Oracle Data Integration overview, vision and roadmap. Covers GoldenGate, Data Integrator (ODI), Data Quality (EDQ), Metadata Management (MM) and Big Data Preparation (BDP)
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
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During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.