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Oracle GoldenGate is the leading real-time data integration software provider in the industry - customers include 3 of the top 5 commercial banks, 3 of the top 3 busiest ATM networks, and 4 of the top 5 telecommunications providers. Oracle GoldenGate moves transactional data in real-time across heterogeneous database, hardware and operating systems with minimal impact. The software platform captures, routes, and delivers data in real time, enabling organizations to maintain continuous uptime for critical applications during planned and unplanned outages. Additionally, it moves data from transaction processing environments to read-only reporting databases and analytical applications for accurate, timely reporting and improved business intelligence for the enterprise.

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We produce quite a lot of data! Much of the data are business transactions stored in a relational database. More frequently, the data are non-structured, high volume and rapidly changing datasets known in the industry as Big Data. The challenge for data integration professionals is to combine and transform the data into useful information. Not just that, but it must also be done in near real-time and using a target system such as Hadoop. The topic of this session, real-time data streaming, provides a great solution for this challenging task. By integrating GoldenGate, Oracle’s premier data replication technology, and Apache Kafka, the latest open-source streaming and messaging system, we can implement a fast, durable, and scalable solution. Presented at Oracle OpenWorld 2016

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Big Data integration is an excellent feature in the Oracle Data Integration product suite (Oracle Data Integrator, GoldenGate, & Enterprise Data Quality). But not all analytics require big data technologies, such as labor cost, revenue, or expense reporting. Ralph Kimball, an original architect of the dimensional model in data warehousing, spent much of his career working to build an enterprise data warehouse methodology that can meet these reporting needs. His book, "The Data Warehouse ETL Toolkit", is a guide for many ETL developers. This session will walk you through his ETL Subsystem categories; Extracting, Cleaning & Conforming, Delivering, and Managing, describing how the Oracle Data Integration products are perfectly suited for the Kimball approach. Presented at KScope16.

A Walk Through the Kimball ETL Subsystems with Oracle Data Integration

As Oracle Warehouse builder nears the end of extended support; customers need to consider their migration options. In this webex we'll be discussing this topic and aim to answer questions like Which tool should I use for new projects? What should be done with existing implementations? And why should I migrate to ODI? In this session You will learn about – • Oracle Data Integrator 12c, concepts and features • The OWB2ODI migration utility • How to successfully migrate OWB projects to ODI • You will hear about customer success stories • New features of ODI 12c that are getting ETL developers excited including Big Data and Hybrid Cloud support.

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As a data integration professional, it’s almost a guarantee that you’ve heard of real-time stream processing of Big Data. The usual players in the open source world are Apache Kafka, used to move data in real-time, and Spark Streaming, built for in-flight transformations. But what about relational data? Quite often we forget that products incubated in the Apache Foundation can also serve a purpose for “standard” relational databases as well. But how? Well, let’s introduce Oracle GoldenGate and Oracle Data Integrator for Big Data. GoldenGate can extract relational data in real time and produce Kafka messages, ensuring relational data is a part of the enterprise data bus. These messages can then be ingested via ODI through a Spark Streaming process, integrating with additional data sources, such as other relational tables, flat files, etc, as needed. Finally, the output can be sent to multiple locations: on through to a data warehouse for analytical reporting, back to Kafka for additional targets to consume, or any number of targets. Attendees will walk away with a framework on which they can build their data streaming projects, combining relational data with big data and using a common, structured approach via the Oracle Data Integration product stack. Presented at BIWA Summit 2017.

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Watch full webinar here: https://bit.ly/33yYuQm Data virtualization has become an essential part of enterprise data architectures, bridging the gap between IT and business users and delivering significant cost and time savings. This technology revolutionizes the way data is accessed, delivered, consumed and governed regardless of its format and location. This 1.5 hour discovery session will show help you identify the benefits of this modern and agile data integration and management technology for your organisation.

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With an increase in the adoption of cloud applications, most organizations today are in some form of hybrid state (i.e. using a combination of on-premise and cloud applications to run their business). Regardless of where the data resides, you need a complete view of the company spanning across different parts of the business, combining insightful data across both onsite and public cloud instances. In this webinar, we looked at multiple approaches that organizations have successfully used to consolidate data from multiple cloud and on-premise applications and to perform seamless analytics across these varied data sources.

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This presentation provides a brief overview of some of the activities around Oracle JET at AMIS. This presentation was prepared for the Oracle OpenWorld 2017 conference - for the JET Panel Session- SUN4389 Oracle JavaScript Extension Toolkit is a modern architecture for front-end JavaScript development. Where ever an Oracle organization uses JavaScript for web or mobile development, they use Oracle JavaScript Extension Toolkit to solve common enterprise problems. However, what are organizations outside Oracle doing with Oracle JavaScript Extension Toolkit? In this session meet representatives from organizations where Oracle JavaScript Extension Toolkit is used, and let them show you the places where they're using Oracle JavaScript Extension Toolkit; what their mix of technology, architectures, and clouds is; and discuss with them the applicability of Oracle JavaScript Extension Toolkit in your context. Prepare to come to this session with questions!

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A data warehouse (DW) migration is no small undertaking, especially when moving from on-premises to the cloud. A typical data warehouse has numerous data sources connecting and loading data into the DW, ETL tools and data integration scripts performing transformations, and reporting, advanced analytics, or ad-hoc query tools accessing the data for insights and analysis. That’s a lot to coordinate and the data warehouse cannot be migrated all at once. Using a data replication technology such as Oracle GoldenGate, the data warehouse migration can be performed incrementally by keeping the data in-sync between the original DW and the new, cloud DW. This session will dive into the steps necessary for this incremental migration approach and walk through a customer use case scenario, leaving attendees with an understanding of how to perform a data warehouse migration to the cloud. Presented at RMOUG Training Days 2019

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There is a fundamental shift underway in IT to include open, software defined, distributed systems like Hadoop. As a result, every Oracle professional should strive to learn these new technologies or risk being left behind. This session is designed specifically for Oracle database professionals so they can better understand SQL on Hadoop and the benefits it brings to the enterprise. Attendees will see how SQL on Hadoop compares to Oracle in areas such as data storage, data ingestion, and SQL processing. Various live demos will provide attendees with a first-hand look at these new world technologies. Presented at Collaborate 18.

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Going "serverless" is the latest technology trend for enterprises moving their processing to the cloud, including data integration and ETL tools. But what does that mean and when should I use serverless ETL? In this session, we'll dive into the world of Amazon's fully managed data processing service called AWS Glue. With no server to provision or resources to allocate, and an easy to populate metadata catalog, AWS Glue allows the data engineer to focus on his or her craft; building data transformations and pipelines. Gaining an understanding of the similarities and differences between traditional ETL tools, such as Oracle Data Integrator, and Glue will prepare attendees for the new world of data integration. Presented at Collaborate 18.

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How much time and effort (and budget) do organizations spend moving data around the enterprise? Unfortunately, quite a lot. These days, ETL developers are tasked with performing the Extract (E) and Load (L), and spending less time on their craft, building Transformations (T). This changes in the new world of data integration. By offloading data from the RDBMS to Hadoop, with the ability to present it back to the relational database, data can be seamlessly integrated between different source and target systems. Transformations occur on data offloaded to Hadoop, using the latest ETL technologies, or in the target database, with a standard ETL-on-RDBMS tool. In this session, we’ll discuss how the new world of data integration will provide focus on transforming data into insightful information by simplifying the data movement process. Presented at Enkitec E4 2017.

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We produce quite a lot of data. Some of this data comes in the form of business transactions and is stored in a relational database. This relational data is often combined with other non-structured, high volume and rapidly changing datasets known in the industry as Big Data. The challenge for us as data integration professionals is to then combine this data and transform it into something useful. Not just that, but we must also do it in near real-time and using a big data target system such as Hadoop. The topic of this session, real-time data streaming, provides us a great solution for that challenging task. By combining GoldenGate, Oracle’s premier data replication technology, and Apache Kafka, the latest open-source streaming and messaging system for big data, we can implement a fast, durable, and scalable solution. This session will walk through the implementation of GoldenGate and Kafka. Presented at Collaborate16 in Las Vegas.

Oracle GoldenGate and Apache Kafka A Deep Dive Into Real-Time Data Streaming

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It's time to move to the Oracle Data Integrator version of Oracle Business Intelligence Applications! This has been the theme since it was recently announced that Oracle BI Applications 11g will move forward without updating functionality in the Informatica version of the product. Implementing Oracle BI Applications can be quite a challenge, specifically with Oracle Data Integrator being the “new” ETL tool. This session will provide attendees with practical tips, based on real-world experience, to help them get started with their implementation. How and why to use Oracle GoldenGate, high availability considerations, disaster recovery setup, and other functional and design factors will be covered, enhancing the attendee's ability to make the best design decisions for their BI Applications project. Presented at KScope15 & NWOUG 2015.

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Oracle Data Integrator and Oracle GoldenGate excel as standalone products, but paired together they are the perfect match for real-time data warehousing. Over the last few years, many real-time data integration solutions have been developed using the 11g version of the products. Now that 12c is available, it’s time to upgrade. This discussion will provide best practices on how to prepare, perform, and validate your data warehouse upgrade to GoldenGate and ODI 12c. Help kickstart your move to 12c with tips, tricks, and lessons learned from successful migrations. Presented at KScope15.

GoldenGate and Oracle Data Integrator - A Perfect Match- Upgrade to 12c

Oracle GoldenGate 12c is well known for its highly performant data replication between relational databases. With the GoldenGate Adaptors, the tool can now apply the source transactions to a Big Data target, such as HDFS. In this session, we'll explore the different options for utilizing Oracle GoldenGate 12c to perform real-time data replication from a relational source database into HDFS. The GoldenGate Adaptors will be used to load movie data from the source to HDFS for use by Hive. Next, we'll take the demo a step further and publish the source transactions to a Flume agent, allowing Flume to handle the final load into the targets. Presented at the Oracle Technology Network Virtual Technology Summit February/March 2015.

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In this session, Oracle Product Management covers how Oracle Data Integrator and Oracle GoldenGate are vital to big data initiatives across the enterprise, providing the movement, translation, and transformation of information and data not only heterogeneously but also in big data environments. Through a metadata-focused approach for cataloging, defining, and reusing big data technologies such as Hive, Hadoop Distributed File System (HDFS), HBase, Sqoop, Pig, Oracle Loader for Hadoop, Oracle SQL Connector for Hadoop Distributed File System, and additional big data projects, Oracle Data Integrator bridges the gap in the ability to unify data across these systems and helps deliver timely and trusted data to analytic and decision support platforms. Co-presented with Alex Kotopoulis at Oracle OpenWorld 2014.

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Providing a real-time BI solution for its global customers and operations department is a necessity for IFPI, the International Federation of the Phonographic Industry, whose primary objective is to safeguard the rights of record producers through various anti-piracy strategies. For the data warehousing team at IFPI, using Oracle Streams and Oracle Warehouse Builder (OWB) for real-time data replication and integration was becoming a challenge. The solution was difficult to maintain and overall throughput was degrading as data volumes increased. The need for greater stability and performance led IFPI to implement Oracle GoldenGate and Oracle Data Integrator. Co-presented with Nick Hurt at Rittman Mead BI Forum 2014 and KScope14.

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We all have business user requirements that drive our data warehouse and business intelligence system implementation. Delivered in various formats, these documents, emails, chats, or meeting minutes can be interpreted many different ways, depending on the reader. An effective approach to end the miscommunication...draw a picture. When properly constructed, an architecture diagram, data model, or process model will have only a single meaning. That is why a picture can replace a thousand words. Presented as a TED style talk at Rittman Mead BI Forum 2014.

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Oracle Data Integrator and Oracle GoldenGate excel as standalone products, but paired together they are the perfect match for real-time data warehousing. Following Oracle’s Next Generation Reference Data Warehouse Architecture, this discussion will provide best practices on how to configure, implement, and process data in real-time using ODI and GoldenGate. Attendees will see common real-time challenges solved, including parent-child relationships within micro-batch ETL. Presented at Rittman Mead BI Forum 2013 Masterclass.

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Providing real-time data to its global customers is a necessity for IFPI (International Federation of the Phonographic Industry), a not-for-profit organization with a mission to safeguard the rights of record producers and promote the value of recorded music. Using Oracle Streams and Oracle Warehouse Builder (OWB) for real-time data replication and integration, meeting this goal was becoming a challenge. The solution was difficult to maintain and overall throughput was degrading as data volume increased. The need for greater stability and performance led IFPI to implement Oracle GoldenGate and Oracle Data Integrator. This session will describe the innovative approach taken to complete the migration from a Streams and OWB implementation to a more robust, maintainable, and performant GoldenGate and ODI integrated solution.

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This presentation covers the following topics: What is logging? The purpose of logging: Debugging The purpose of logging: Security The purpose of logging: Stats & analytics Traditional logging Traditional logging: Advantages Traditional logging: Disadvantages The solution: Large-scale logging Large-scale logging: Core principles Large-scale logging: Solution types Large-scale logging: Cloud vs on-prem Large-scale logging: Operational complexity Large-scale logging: Security Large-scale logging: Costs Large-scale logging: On-prem comparison - Elasticsearch - Grafana Loki - VictoriaLogs On-prem comparison: Setup and operation On-prem comparison: Costs On-prem comparison: Full-text search support On-prem comparison: How to efficiently query 100TB of logs? On-prem comparison: Integration with CLI tools VictoriaLogs for large-scale logging VictoriaLogs demo instance - Ingestion rate: 3600 messages / minute - The number of log messages: 1.1 billion - Uncompressed log messages’ size: 1.5TB - Compressed log messages’ size: 23GB - Compression ratio: 47x - Memory usage: 150MB VictoriaLogs CLI integration demo - Which errors have occurred in all the apps during the last hour? - How many errors have occurred during the last hour? - Which apps generated the most of errors during the last hour? - The number of per-minute errors for the last 10 minutes - Status codes for the last hour - Non-200 status codes for the last week - Top client IPs for the last 4 weeks with 404 and 500 response status codes - Per-month stats for the given IP across all the logs Large-scale logging solution MUST provide excellent CLI integration VictoriaLogs: (temporary) drawbacks VictoriaLogs: Recap - Easy to setup and operate - The lowest RAM usage and disk space usage (up to 30x less than Elasticsearch and Grafana Loki) - Fast full-text search - Excellent integration with traditional command-line tools for log analysis - Accepts logs from popular log shippers (Filebeat, Fluentbit, Logstash, Vector, Promtail, Grafana Agent) - Open source and free to use!

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