The role of Dremio in a data mesh architecture
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How to use Dremio a standard interface to implement Output Ports in a Data Mesh architecture
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Modernizing Global Shared Data Analytics Platform and our Alluxio JourneyAlluxio, Inc. Data Orchestration Summit 2020 organized by Alluxio
https://www.alluxio.io/data-orchestration-summit-2020/
Modernizing Global Shared Data Analytics Platform and our Alluxio Journey
Sandipan Chakraborty, Director of Engineering (Rakuten)
About Alluxio: alluxio.io
Engage with the open source community on slack: alluxio.io/slack
Introduction to Data Engineering
Introduction to Data EngineeringDurga Gadiraju As part of this session, I will be giving an introduction to Data Engineering and Big Data. It covers up to date trends.
* Introduction to Data Engineering
* Role of Big Data in Data Engineering
* Key Skills related to Data Engineering
* Role of Big Data in Data Engineering
* Overview of Data Engineering Certifications
* Free Content and ITVersity Paid Resources
Don't worry if you miss the video - you can click on the below link to go through the video after the schedule.
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* Upcoming Live Session - Overview of Big Data Certifications (Spark Based) - https://www.meetup.com/itversityin/events/271739702/
Relevant Playlists:
* Apache Spark using Python for Certifications - https://www.youtube.com/playlist?list=PLf0swTFhTI8rMmW7GZv1-z4iu_-TAv3bi
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Weathering the Data Storm – How SnapLogic and AWS Deliver Analytics in the Cl...
Weathering the Data Storm – How SnapLogic and AWS Deliver Analytics in the Cl...SnapLogic In this webinar, learn how SnapLogic and Amazon Web Services helped Earth Networks create a responsive, self-service cloud for data integration, preparation and analytics.
We also discuss how Earth Networks gained faster data insights using SnapLogic’s Amazon Redshift data integration and other connectors to quickly integrate, transfer and analyze data from multiple applications.
To learn more, visit: www.snaplogic.com/redshift
Simplifying Your Cloud Architecture with a Logical Data Fabric (APAC)
Simplifying Your Cloud Architecture with a Logical Data Fabric (APAC)Denodo Watch full webinar here: https://bit.ly/3dudL6u
It's not if you move to the cloud, but when. Most organisations are well underway with migrating applications and data to the cloud. In fact, most organisations - whether they realise it or not - have a multi-cloud strategy. Single, hybrid, or multi-cloud…the potential benefits are huge - flexibility, agility, cost savings, scaling on-demand, etc. However, the challenges can be just as large and daunting. A poorly managed migration to the cloud can leave users frustrated at their inability to get to the data that they need and IT scrambling to cobble together a solution.
In this session, we will look at the challenges facing data management teams as they migrate to cloud and multi-cloud architectures. We will show how the Denodo Platform can:
- Reduce the risk and minimise the disruption of migrating to the cloud.
- Make it easier and quicker for users to find the data that they need - wherever it is located.
- Provide a uniform security layer that spans hybrid and multi-cloud environments.
oracle.pptx
oracle.pptxMinakshee Patil Oracle 11g and 12c are database management systems. Oracle 11g allows for grid computing across clustered servers and has a browser-based interface. It supports creating and manipulating database objects. Oracle 12c has new features like cloud support and a pluggable database architecture. It is designed for the cloud and supports in-memory processing and native JSON. Grid computing links computing resources over a network to complete tasks more quickly. Cloud computing delivers computing resources over the internet in a pay-as-you-go model.
Building Blocks for Hybrid IT
Building Blocks for Hybrid ITRightScale By leveraging a hybrid model that encompasses both on-premise resource utilization and cloud computing, organizations can deploy applications to the most appropriate resource pools, making themselves more agile and saving money. In this presentation at AWS Summit San Francisco, RightScale Senior Services Architect Brian Adler describes the factors that organizations must consider when they create a hybrid model that uses AWS services. He shares a detailed reference architecture for hybrid clouds, covers the preferred use cases for the allocation and utilization of on-premise and cloud computing resources, and reviews technologies available to seamlessly manage hybrid IT infrastructure.
Data virtualization
Data virtualizationHamed Hatami Data virtualization allows applications to access and manipulate data without knowledge of physical data structures or locations. Teiid is a data virtualization system comprised of tools, components and services for creating and executing bidirectional data services across distributed, heterogeneous data sources in real-time without moving data. Teiid includes a query engine, embedded driver, server, connectors and tools for creating virtual databases (VDBs) containing models that define data structures and views. Models represent data sources or abstractions and must be validated and configured with translators and resource adapters to access physical data when a VDB is deployed.
BPM and SOA are going mobile - An architectural perspective
BPM and SOA are going mobile - An architectural perspectiveOPITZ CONSULTING Deutschland http://www.opitz-consulting.com/go/3-5-898
Smartphones and tablets conquered our world. Which new opportunities are there for our businesses? Which influence has the omnipresent HTML5? How can I integrate mobile solutions in an optimal architectural way in my SOA landscapes and which kind of advantages do I gain for business process automation? This session delivers answers and puts current buzzwords like Big Data, Cloud, internet of things, HTML5 and mobile in the context of BPM and integration. Thereby we derive a reference architecture for Oracle SOA Suite, OSB, BPM Suite, Enterprise Gateway, Webcenter, ADF Mobile, etc., which makes all the buzzwords easily manageable in our daily IT work and prevents you from making mistakes others already did.
Torsten Winterberg und Guido Schmutz, both well-respected SOA Experts, presented this session at German Oracle User Communities’s Conference (DOAG Konferenz) at nov 20th 2013 in Nuremberg, Germany.
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- - -
About us:
OPITZ CONSULTING is a leading project specialist for custom-build applications and individual business intelligence solutions in the German market. The company's ambition is to help organizations to be better than their competitors. To achieve this OPITZ CONSULTING analyses the individual competitive edge the customer has, optimizes business processes for process automation and IT-support, chooses and designs appropriate system architectures, develops and implements solutions and guarantees a 24/7 support and application maintenance. To ensure the necessary skill and qualification OPITZ CONSULTING has established a training center for customers and the internal staff.
Since 1990 over 600 customers have a long lasting and successful business relationship with OPITZ CONSULTING. Over 2/3 of the German stock index (DAX) companies rely on services from the 400+ OPITZ CONSULTING consultants. OPITZ CONSULTING maintains offices in Bad Homburg, Berlin, Essen, Gummersbach, Hamburg, Munich, Nuremberg and Kraków and Warsawa (Poland).
About us: http://www.opitz-consulting.com/en/about_us
Services: http://www.opitz-consulting.com/en/leistungsangebot
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BPM und SOA machen mobil - Ein Architekturüberblick
BPM und SOA machen mobil - Ein ArchitekturüberblickOPITZ CONSULTING Deutschland http://www.opitz-consulting.com/go/3-5-898
Smartphones haben unsere Welt im Schnellgang erobert. Die Tablets folgen nicht minder schnell nach. Was fasziniert uns so daran? Welche neuen Möglichkeiten bieten sich für das Business? Welchen Einfluss wird das allgegenwärtige HTML5 haben? Wie bekomme ich mobile Lösungen architektonisch optimal in meine SOA-Landschaft integriert, und welche Vorteile gewinne ich bei der Prozessautomatisierung? Diese Session liefert sowohl einen Überblick als auch Antworten für eine neue Klasse von Architekturfragen.
Die SOA-Experten Torsten Winterberg und Guido Schmutz hielten diesen Fachvortrag bei der DOAG Konferenz und Ausstellung am 20.11.2013 in Nürnberg.
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Über uns:
Als führender Projektspezialist für ganzheitliche IT-Lösungen tragen wir zur Wertsteigerung der Organisationen unserer Kunden bei und bringen IT und Business in Einklang. Mit OPITZ CONSULTING als zuverlässigem Partner können sich unsere Kunden auf ihr Kerngeschäft konzentrieren und ihre Wettbewerbsvorteile nachhaltig absichern und ausbauen.
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Karriere bei OPITZ CONSULTING: http://www.opitz-consulting.com/go/3-8-5
Break Free from Oracle
Break Free from OracleEDB This webinar will review the challenges teams face when migrating from Oracle databases to PostgreSQL. We will share insights gained from running large scale Oracle compatibility assessments over the last two years, including the over 2,200,000 Oracle DDL constructs that were assessed through EDB’s Migration Portal in 2020.
During this session we will address:
Storage definitions
Packages
Stored procedures
PL/SQL code
Proprietary database APIs
Large scale data migrations
We will end the session demonstrating migration tools that significantly simplify and aid in reducing the risk of migrating Oracle databases to PostgreSQL.
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kafka simplicity and complexity
kafka simplicity and complexityPaolo Platter Agile Lab is an Italian company that specializes in leveraging innovative technologies like machine learning, big data, and artificial intelligence to satisfy customers' objectives. They have over 50 specialists with deep experience in production environments. The company believes in investing in its team through conferences, R&D projects, and welfare benefits. They also release open source frameworks on GitHub and share knowledge through meetups in Milan and Turin.
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Wasp2 - IoT and Streaming PlatformPaolo Platter WASP is a framework to develop big data pipelines, working with streaming analytics, multi model storages and machine learning models. Everything is in real time.
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Meetup tensorframesPaolo Platter TensorFlow & TensorFrames w/ Apache Spark presents Marco Saviano. It discusses numerical computing with Apache Spark and Google TensorFlow. TensorFrames allows manipulating Spark DataFrames with TensorFlow programs. It provides most operations in row-based and block-based versions. Row-based processes rows individually while block-based processes blocks of rows together for better efficiency. Reduction operations coalesce rows until one row remains. Future work may improve communication between Spark and TensorFlow through direct memory copying and using columnar storage formats.
Bringing Deep Learning into production 
Bringing Deep Learning into production Paolo Platter - The document discusses deep learning frameworks and how to choose one for a given environment. It summarizes the strengths, weaknesses, opportunities and threats of popular frameworks like TensorFlow, Theano, Torch, Caffe, DeepLearning4J and H2O.
- It recommends H2O as a good choice for enterprise environments due to its ease of use, scalability on big data, integration with Spark, Java/Scala support and commercial support. DeepLearning4J is also recommended for more advanced deep neural networks and multi-dimensional arrays.
- The document proposes using Spark as a middleware to leverage multiple frameworks and avoid vendor lock-in, and describes Agile Lab's recommended stack for enterprises which combines H
Agile Lab_BigData_Meetup_AKKA
Agile Lab_BigData_Meetup_AKKAPaolo Platter This document discusses reactive and parallel programming using Akka. It introduces Akka, an open-source toolkit for building distributed, concurrent applications on the JVM. Akka supports actors, futures, software transactional memory, and message passing to handle concurrency. Akka cluster allows building fault-tolerant distributed systems. Examples demonstrate using Akka for microservices, streaming engines, authentication platforms, and IoT applications. The document concludes with an example of how Agile Lab uses Akka in their applications.
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Massive Streaming Analytics with Spark Streaming
Massive Streaming Analytics with Spark StreamingPaolo Platter Streaming data allows for faster reactions and more profits by enabling real-time processing compared to typical batch analysis workflows. Prediction is more valuable than rule-based categorization and clustering because it allows for pattern discovery, adaptation to changing data, and "smart thinking". Spark Streaming is presented as a tool for building streaming architectures with ingestion, processing, and serving layers. A demo of card transaction analysis with real-time classification, fraud detection, and alert generation is shown.
Scala Intro
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- Scala runs on the Java Virtual Machine (JVM) and allows for type inference, immutable values, functional programming patterns like pattern matching, and object-oriented features like traits for inheritance.
- Scala favors immutable values over mutable variables for scalability. Features like actors allow for concurrency without shared mutable state.
- Scala code can be compiled to JavaScript using Scala.js, allowing full-stack development in a single language.
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The role of Dremio in a data mesh architecture
- 1. The role of Dremio in a Data Mesh architecture Presented by: Paolo Platter – CTO & Co-founder @ Agile Lab
- 2. Who we are : • We value transparency, collaboration and results • Totally decentralized and self-managed • International culture and mindset • Customer laser focused What we do: • Data Engineering is our mission since 2013 • Crafting end-to-end data platforms • Data Strategy • Managed Data Service www.agilelab.it
- 3. Data Mesh Principles Domain Driven Data Ownership Architecture Data as a product Self-Serve Infrastructure as a Platform Federated Computational Governance
- 4. Data Product Data + Metadata (syntax+semantic, expected behaviour, access control ) Infrastructure Data Pipeline Data Access API Observability API Internal processes (GDPR, DQ, etc ) Stream Processing Information API Control Ports code data Input Ports • Operational systems • Other Data Products • External services Output Ports • Events • SQLView • Raw/Files • Graph/RDF infrastructure
- 5. Technology Independence • Addressability • Interoperability • Self-Serve provisioning • Independently deployable • Data Mesh is a practice • Each Data Product team can select the technology that best fits the use case. • The technology must be compliant with Data Product features and requirements • Multi-cloud needs
- 6. Output Ports Output Port API Data Consumer • Descriptive schema • Audit • Access Control • Decoupling(uri and protocol) • SLO Read data through native protocol Events SQL Files Output Port API Data Consumer • GraphQL or HTTP • Data is flowing throught API • Zero coupling, low performances • Not suitable for all use cases of data consumption Events SQL Files • Data is flowing throught native protocol • Low coupling, good performances • Fully Polyglot Pre-flight
- 8. Connecting a BI tool to an Output Port BI Tool SQL Files Output Port API GraphQL or other HTTP based protocols are not widely supported by BI Tools. Also thinking to have a custom pre-flight and dynamically discover the protocol of the source is something not easy In order to query directly a file/object storage you need a SQL Engine, tipically not available inside BI Tools JDBC/ODBC connection is a good and standard option for BI Tools, but this is hiding problems
- 9. Client-side coupling is not good Consumer JDBC driver Athena JDBC driver Redshift JDBC driver Aurora • One driver doesn’t fit all • Coupling is becoming a problem for change management • DP is not indipendently deployable Resons why you need multiple technologies in a data mesh: - Not all the use cases fit with a single tech - Data Mesh is an evolutionary architecture, technologies will evolve and change over time and DPs will adopt them indipendently - Your data mesh is expanding on a multi- cloud landscape
- 10. How to integrate legacy systems Data Mesh Data Lake Migration will require time... Consumer j d b c jdbc What if we need to join data coming from different JDBC channels ? Huge impact on performances Join must be resolved at this level
- 12. Dremio Uniqueness SQL Execution Engine OLAP Accelleration Virtualization Extensible Semantic Layer Scalable Cache Cloud & Tech Agnostic Flexible & Self Serve deployment
- 13. Fitting into the big picture Native integration with data lakes Bridge also other enteprise assets Data Consumer • Single interface to access all the silos and no coupling between data consumers and multiple specific technologies • Single catalog of data You can use it as SQL Query Engine inside Data Products Interfacing other DBMS Cloud agnostic • Efficient join between DPs leveraging different underlying technologies • Query federation between data mesh and other data assets across the organization • Native integration with DataLakes to facilitate the transition to the DataMesh
- 14. Self-Serve provisioning API Catalog Execution Engine ACL CI/CD Data Product specification Provision: • Execution resources • SQL View • ACL Provision: • Storage • DB • Policies • IAM • etc Deploy
- 15. Data-Product Caching Main Entity Pre-aggregated and denormalized views Query Acceleration & Caching Leverage external reflections to speed-up queries automatically without adding complexity to the data consumer Query Dremio can create such pre-aggregation automatically without the need to implement custom jobs for such purpose Data Consumer Data Consumer interacts with a single logical entity, but queries will speed-up due to the cache and reflections.
- 16. Thank You! – Q&A Time Contact me at: [email protected] https://www.agilelab.it/data-mesh-in-action/