Ron Veen will present on data-oriented programming in Java. The presentation will cover: 1) the evolution of traditional object-oriented applications, 2) introducing the principles of data-oriented programming, 3) modern Java features that support data-oriented programming like records and pattern matching, and 4) examples of combining Java and data-oriented programming. Data-oriented programming treats data as immutable first-class citizens stored in generic structures separate from application logic.
Data and AI summit: data pipelines observability with open lineageJulien Le Dem
Presentation of Data lineage an Observability with OpenLineage at the "Data and AI summit" (formerly Spark summit). With a focus on the Apache Spark integration for OpenLineage
Observability for Data Pipelines With OpenLineageDatabricks
Data is increasingly becoming core to many products. Whether to provide recommendations for users, getting insights on how they use the product, or using machine learning to improve the experience. This creates a critical need for reliable data operations and understanding how data is flowing through our systems. Data pipelines must be auditable, reliable, and run on time. This proves particularly difficult in a constantly changing, fast-paced environment.
Collecting this lineage metadata as data pipelines are running provides an understanding of dependencies between many teams consuming and producing data and how constant changes impact them. It is the underlying foundation that enables the many use cases related to data operations. The OpenLineage project is an API standardizing this metadata across the ecosystem, reducing complexity and duplicate work in collecting lineage information. It enables many projects, consumers of lineage in the ecosystem whether they focus on operations, governance or security.
Marquez is an open source project part of the LF AI & Data foundation which instruments data pipelines to collect lineage and metadata and enable those use cases. It implements the OpenLineage API and provides context by making visible dependencies across organizations and technologies as they change over time.
Open Chemistry, JupyterLab and data: Reproducible quantum chemistryMarcus Hanwell
The Open Chemistry project is developing an ambitious platform to facilitate reproducible quantum chemistry workflows by integrating the best of breed open source projects currently available in a cohesive platform with extensions specific to the needs of quantum chemistry. The core of the project is a Python-based data server capable of storing metadata, executing quantum chemistry calculations, and processing the output. The platform exposes RESTful endpoints using programming language agnostic web endpoints, and uses Linux container technology to package quantum codes that are often difficult to build.
The Jupyter project has been leveraged as a web-based frontend offering reproducibility as a core principle. This has been coupled with the data server to initiate quantum chemistry calculations, cache results, make them searchable, and even visualize the results within a modern browser environment. The Avogadro libraries have been reused for visualization workflows, coupled with Open Babel for file translation, and examples of the use of NWChem and Psi4 will be demonstrated.
The core of the platform is developed upon JSON data standards, and encouraging the wider adoption of JSON/HDF5 as the principle storage mediums. A single page web application using React at its core will be shown for sharing simple views of data output, and linking to the Jupyter notebooks that documents how they were made. Command line tools and links to the Avogadro graphical interface will be shown demonstrating capabilities from web through to desktop.
Data and AI summit: data pipelines observability with open lineageJulien Le Dem
Presentation of Data lineage an Observability with OpenLineage at the "Data and AI summit" (formerly Spark summit). With a focus on the Apache Spark integration for OpenLineage
Observability for Data Pipelines With OpenLineageDatabricks
Data is increasingly becoming core to many products. Whether to provide recommendations for users, getting insights on how they use the product, or using machine learning to improve the experience. This creates a critical need for reliable data operations and understanding how data is flowing through our systems. Data pipelines must be auditable, reliable, and run on time. This proves particularly difficult in a constantly changing, fast-paced environment.
Collecting this lineage metadata as data pipelines are running provides an understanding of dependencies between many teams consuming and producing data and how constant changes impact them. It is the underlying foundation that enables the many use cases related to data operations. The OpenLineage project is an API standardizing this metadata across the ecosystem, reducing complexity and duplicate work in collecting lineage information. It enables many projects, consumers of lineage in the ecosystem whether they focus on operations, governance or security.
Marquez is an open source project part of the LF AI & Data foundation which instruments data pipelines to collect lineage and metadata and enable those use cases. It implements the OpenLineage API and provides context by making visible dependencies across organizations and technologies as they change over time.
Open Chemistry, JupyterLab and data: Reproducible quantum chemistryMarcus Hanwell
The Open Chemistry project is developing an ambitious platform to facilitate reproducible quantum chemistry workflows by integrating the best of breed open source projects currently available in a cohesive platform with extensions specific to the needs of quantum chemistry. The core of the project is a Python-based data server capable of storing metadata, executing quantum chemistry calculations, and processing the output. The platform exposes RESTful endpoints using programming language agnostic web endpoints, and uses Linux container technology to package quantum codes that are often difficult to build.
The Jupyter project has been leveraged as a web-based frontend offering reproducibility as a core principle. This has been coupled with the data server to initiate quantum chemistry calculations, cache results, make them searchable, and even visualize the results within a modern browser environment. The Avogadro libraries have been reused for visualization workflows, coupled with Open Babel for file translation, and examples of the use of NWChem and Psi4 will be demonstrated.
The core of the platform is developed upon JSON data standards, and encouraging the wider adoption of JSON/HDF5 as the principle storage mediums. A single page web application using React at its core will be shown for sharing simple views of data output, and linking to the Jupyter notebooks that documents how they were made. Command line tools and links to the Avogadro graphical interface will be shown demonstrating capabilities from web through to desktop.
Angular JS Institute: NBITS is the best Angular JS Online/Classroom Training Institute in Hyderabad.We provide training from best real time industry experts in Angular 2,Angular 4,Angular 5,Node js, mean stack courses through online and Classroom with Lab facility.
MongoDB for Spatio-Behavioral Data Analysis and VisualizationMongoDB
T-Sciences offers iSpatial - a web-based Spatial Data Infrastructure (SDI) to enable integration of third-party applications with geo-visualization tools. The iHarvest tool further enables the mining and analysis of data aggregated in the iSpatial platform for spatio-temporal behavior modelling. At the back-end of both products is MongoDB, providing fundamental framework capabilities for the spatial indexing and data analysis techniques. Come witness how Thermopylae Sciences and Technology leveraged the aggregation framework, and extended the spatial capabilities of MongoDB to tackle dynamic spatio-behavioral data at scale.
Spring Data Neo4j: Graph Power Your Enterprise AppsGraphAware
A few weeks ago Spring Data Neo4j version 5 was released as part of the Spring Data 2.0 release train. Time to present the Spring way to work with Neo4j and introduce the latest features SDN 5 and its supporting library Neo4j-OGM 3 provide. The talk will also give an overview of the overall architecture and shows examples how to build modern, compact back-ends and web-applications using Spring Data Neo4j. Of course we will give a glance of what the future will bring to Spring Data Neo4j.
Stitch Fix aspires to help you find the style that you will love. Data, the backbone of the business, is used to help with styling recommendations, demand modeling, user acquisition, and merchandise planning and also to influence business decisions throughout the organization. These decisions are backed by algorithms and data collected and interpreted based on client preferences. This talk offers an overview of the compute infrastructure used by the data science team at Stitch Fix, covering the architecture, tools within the larger ecosystem, and the challenges that the team overcame along the way.
Apache Spark plays an important role in Stitch Fix’s data platform, and the company’s data scientists use Spark for their ETL and Presto for their ad hoc queries. The goal for the team running the compute infrastructure is to understand and make the data scientists’ lives easier, particularly in terms of usability of Spark, by building tools that make it easier to get started with Spark and transition themselves to a daily workflow. The compute infrastructure is a part of the data platform that is responsible for all the needs of data scientists as Stitch Fix.
In this talk, we look at Stitch Fix’s journey, exploring its Spark setup, in-house tools and how they work in synergy with open source frameworks in a cloud environment. There are additional improvements to the infrastructure that help persist information for future use and optimization and we look at how the implementation of Amazon’s EMR FS has helped make it easier for us to read from the S3 source.
Architect’s Open-Source Guide for a Data Mesh ArchitectureDatabricks
Data Mesh is an innovative concept addressing many data challenges from an architectural, cultural, and organizational perspective. But is the world ready to implement Data Mesh?
In this session, we will review the importance of core Data Mesh principles, what they can offer, and when it is a good idea to try a Data Mesh architecture. We will discuss common challenges with implementation of Data Mesh systems and focus on the role of open-source projects for it. Projects like Apache Spark can play a key part in standardized infrastructure platform implementation of Data Mesh. We will examine the landscape of useful data engineering open-source projects to utilize in several areas of a Data Mesh system in practice, along with an architectural example. We will touch on what work (culture, tools, mindset) needs to be done to ensure Data Mesh is more accessible for engineers in the industry.
The audience will leave with a good understanding of the benefits of Data Mesh architecture, common challenges, and the role of Apache Spark and other open-source projects for its implementation in real systems.
This session is targeted for architects, decision-makers, data-engineers, and system designers.
Mobile Offline First for inclusive data that spans the data divideRob Worthington
This presentation - given at the 2016 GovTech conference in South Africa - provides an overview of a new mobile offline first architecture for government applications
District Data Labs Workshop
Current Workshop: August 23, 2014
Previous Workshops:
- April 5, 2014
Data products are usually software applications that derive their value from data by leveraging the data science pipeline and generate data through their operation. They aren’t apps with data, nor are they one time analyses that produce insights - they are operational and interactive. The rise of these types of applications has directly contributed to the rise of the data scientist and the idea that data scientists are professionals “who are better at statistics than any software engineer and better at software engineering than any statistician.”
These applications have been largely built with Python. Python is flexible enough to develop extremely quickly on many different types of servers and has a rich tradition in web applications. Python contributes to every stage of the data science pipeline including real time ingestion and the production of APIs, and it is powerful enough to perform machine learning computations. In this class we’ll produce a data product with Python, leveraging every stage of the data science pipeline to produce a book recommender.
LODFlow: Workflow Management System for Linked Data ProcessingIvan Ermilov
Sandro Rautenberg, Ivan Ermilov, Edgard Marx, Soeren Auer, Axel-Cyrille N. Ngomo. LODFlow: Workflow Management System for Linked Data Processing presentation for SEMANTiCS'2015 conference.
This session is about Django, which is a web framework build in python. It has several features like admin interface and ORM. The architecture of Django has Model, View, and template and it's ORM saves the pain of writing database queries.
Exploring Innovations in Data Repository Solutions - Insights from the U.S. G...Globus
The U.S. Geological Survey (USGS) has made substantial investments in meeting evolving scientific, technical, and policy driven demands on storing, managing, and delivering data. As these demands continue to grow in complexity and scale, the USGS must continue to explore innovative solutions to improve its management, curation, sharing, delivering, and preservation approaches for large-scale research data. Supporting these needs, the USGS has partnered with the University of Chicago-Globus to research and develop advanced repository components and workflows leveraging its current investment in Globus. The primary outcome of this partnership includes the development of a prototype enterprise repository, driven by USGS Data Release requirements, through exploration and implementation of the entire suite of the Globus platform offerings, including Globus Flow, Globus Auth, Globus Transfer, and Globus Search. This presentation will provide insights into this research partnership, introduce the unique requirements and challenges being addressed and provide relevant project progress.
Angular JS Institute: NBITS is the best Angular JS Online/Classroom Training Institute in Hyderabad.We provide training from best real time industry experts in Angular 2,Angular 4,Angular 5,Node js, mean stack courses through online and Classroom with Lab facility.
MongoDB for Spatio-Behavioral Data Analysis and VisualizationMongoDB
T-Sciences offers iSpatial - a web-based Spatial Data Infrastructure (SDI) to enable integration of third-party applications with geo-visualization tools. The iHarvest tool further enables the mining and analysis of data aggregated in the iSpatial platform for spatio-temporal behavior modelling. At the back-end of both products is MongoDB, providing fundamental framework capabilities for the spatial indexing and data analysis techniques. Come witness how Thermopylae Sciences and Technology leveraged the aggregation framework, and extended the spatial capabilities of MongoDB to tackle dynamic spatio-behavioral data at scale.
Spring Data Neo4j: Graph Power Your Enterprise AppsGraphAware
A few weeks ago Spring Data Neo4j version 5 was released as part of the Spring Data 2.0 release train. Time to present the Spring way to work with Neo4j and introduce the latest features SDN 5 and its supporting library Neo4j-OGM 3 provide. The talk will also give an overview of the overall architecture and shows examples how to build modern, compact back-ends and web-applications using Spring Data Neo4j. Of course we will give a glance of what the future will bring to Spring Data Neo4j.
Stitch Fix aspires to help you find the style that you will love. Data, the backbone of the business, is used to help with styling recommendations, demand modeling, user acquisition, and merchandise planning and also to influence business decisions throughout the organization. These decisions are backed by algorithms and data collected and interpreted based on client preferences. This talk offers an overview of the compute infrastructure used by the data science team at Stitch Fix, covering the architecture, tools within the larger ecosystem, and the challenges that the team overcame along the way.
Apache Spark plays an important role in Stitch Fix’s data platform, and the company’s data scientists use Spark for their ETL and Presto for their ad hoc queries. The goal for the team running the compute infrastructure is to understand and make the data scientists’ lives easier, particularly in terms of usability of Spark, by building tools that make it easier to get started with Spark and transition themselves to a daily workflow. The compute infrastructure is a part of the data platform that is responsible for all the needs of data scientists as Stitch Fix.
In this talk, we look at Stitch Fix’s journey, exploring its Spark setup, in-house tools and how they work in synergy with open source frameworks in a cloud environment. There are additional improvements to the infrastructure that help persist information for future use and optimization and we look at how the implementation of Amazon’s EMR FS has helped make it easier for us to read from the S3 source.
Architect’s Open-Source Guide for a Data Mesh ArchitectureDatabricks
Data Mesh is an innovative concept addressing many data challenges from an architectural, cultural, and organizational perspective. But is the world ready to implement Data Mesh?
In this session, we will review the importance of core Data Mesh principles, what they can offer, and when it is a good idea to try a Data Mesh architecture. We will discuss common challenges with implementation of Data Mesh systems and focus on the role of open-source projects for it. Projects like Apache Spark can play a key part in standardized infrastructure platform implementation of Data Mesh. We will examine the landscape of useful data engineering open-source projects to utilize in several areas of a Data Mesh system in practice, along with an architectural example. We will touch on what work (culture, tools, mindset) needs to be done to ensure Data Mesh is more accessible for engineers in the industry.
The audience will leave with a good understanding of the benefits of Data Mesh architecture, common challenges, and the role of Apache Spark and other open-source projects for its implementation in real systems.
This session is targeted for architects, decision-makers, data-engineers, and system designers.
Mobile Offline First for inclusive data that spans the data divideRob Worthington
This presentation - given at the 2016 GovTech conference in South Africa - provides an overview of a new mobile offline first architecture for government applications
District Data Labs Workshop
Current Workshop: August 23, 2014
Previous Workshops:
- April 5, 2014
Data products are usually software applications that derive their value from data by leveraging the data science pipeline and generate data through their operation. They aren’t apps with data, nor are they one time analyses that produce insights - they are operational and interactive. The rise of these types of applications has directly contributed to the rise of the data scientist and the idea that data scientists are professionals “who are better at statistics than any software engineer and better at software engineering than any statistician.”
These applications have been largely built with Python. Python is flexible enough to develop extremely quickly on many different types of servers and has a rich tradition in web applications. Python contributes to every stage of the data science pipeline including real time ingestion and the production of APIs, and it is powerful enough to perform machine learning computations. In this class we’ll produce a data product with Python, leveraging every stage of the data science pipeline to produce a book recommender.
LODFlow: Workflow Management System for Linked Data ProcessingIvan Ermilov
Sandro Rautenberg, Ivan Ermilov, Edgard Marx, Soeren Auer, Axel-Cyrille N. Ngomo. LODFlow: Workflow Management System for Linked Data Processing presentation for SEMANTiCS'2015 conference.
This session is about Django, which is a web framework build in python. It has several features like admin interface and ORM. The architecture of Django has Model, View, and template and it's ORM saves the pain of writing database queries.
Exploring Innovations in Data Repository Solutions - Insights from the U.S. G...Globus
The U.S. Geological Survey (USGS) has made substantial investments in meeting evolving scientific, technical, and policy driven demands on storing, managing, and delivering data. As these demands continue to grow in complexity and scale, the USGS must continue to explore innovative solutions to improve its management, curation, sharing, delivering, and preservation approaches for large-scale research data. Supporting these needs, the USGS has partnered with the University of Chicago-Globus to research and develop advanced repository components and workflows leveraging its current investment in Globus. The primary outcome of this partnership includes the development of a prototype enterprise repository, driven by USGS Data Release requirements, through exploration and implementation of the entire suite of the Globus platform offerings, including Globus Flow, Globus Auth, Globus Transfer, and Globus Search. This presentation will provide insights into this research partnership, introduce the unique requirements and challenges being addressed and provide relevant project progress.
Listen to the keynote address and hear about the latest developments from Rachana Ananthakrishnan and Ian Foster who review the updates to the Globus Platform and Service, and the relevance of Globus to the scientific community as an automation platform to accelerate scientific discovery.
First Steps with Globus Compute Multi-User EndpointsGlobus
In this presentation we will share our experiences around getting started with the Globus Compute multi-user endpoint. Working with the Pharmacology group at the University of Auckland, we have previously written an application using Globus Compute that can offload computationally expensive steps in the researcher's workflows, which they wish to manage from their familiar Windows environments, onto the NeSI (New Zealand eScience Infrastructure) cluster. Some of the challenges we have encountered were that each researcher had to set up and manage their own single-user globus compute endpoint and that the workloads had varying resource requirements (CPUs, memory and wall time) between different runs. We hope that the multi-user endpoint will help to address these challenges and share an update on our progress here.
Unleash Unlimited Potential with One-Time Purchase
BoxLang is more than just a language; it's a community. By choosing a Visionary License, you're not just investing in your success, you're actively contributing to the ongoing development and support of BoxLang.
In software engineering, the right architecture is essential for robust, scalable platforms. Wix has undergone a pivotal shift from event sourcing to a CRUD-based model for its microservices. This talk will chart the course of this pivotal journey.
Event sourcing, which records state changes as immutable events, provided robust auditing and "time travel" debugging for Wix Stores' microservices. Despite its benefits, the complexity it introduced in state management slowed development. Wix responded by adopting a simpler, unified CRUD model. This talk will explore the challenges of event sourcing and the advantages of Wix's new "CRUD on steroids" approach, which streamlines API integration and domain event management while preserving data integrity and system resilience.
Participants will gain valuable insights into Wix's strategies for ensuring atomicity in database updates and event production, as well as caching, materialization, and performance optimization techniques within a distributed system.
Join us to discover how Wix has mastered the art of balancing simplicity and extensibility, and learn how the re-adoption of the modest CRUD has turbocharged their development velocity, resilience, and scalability in a high-growth environment.
Providing Globus Services to Users of JASMIN for Environmental Data AnalysisGlobus
JASMIN is the UK’s high-performance data analysis platform for environmental science, operated by STFC on behalf of the UK Natural Environment Research Council (NERC). In addition to its role in hosting the CEDA Archive (NERC’s long-term repository for climate, atmospheric science & Earth observation data in the UK), JASMIN provides a collaborative platform to a community of around 2,000 scientists in the UK and beyond, providing nearly 400 environmental science projects with working space, compute resources and tools to facilitate their work. High-performance data transfer into and out of JASMIN has always been a key feature, with many scientists bringing model outputs from supercomputers elsewhere in the UK, to analyse against observational or other model data in the CEDA Archive. A growing number of JASMIN users are now realising the benefits of using the Globus service to provide reliable and efficient data movement and other tasks in this and other contexts. Further use cases involve long-distance (intercontinental) transfers to and from JASMIN, and collecting results from a mobile atmospheric radar system, pushing data to JASMIN via a lightweight Globus deployment. We provide details of how Globus fits into our current infrastructure, our experience of the recent migration to GCSv5.4, and of our interest in developing use of the wider ecosystem of Globus services for the benefit of our user community.
Into the Box Keynote Day 2: Unveiling amazing updates and announcements for modern CFML developers! Get ready for exciting releases and updates on Ortus tools and products. Stay tuned for cutting-edge innovations designed to boost your productivity.
Enterprise Resource Planning System includes various modules that reduce any business's workload. Additionally, it organizes the workflows, which drives towards enhancing productivity. Here are a detailed explanation of the ERP modules. Going through the points will help you understand how the software is changing the work dynamics.
To know more details here: https://blogs.nyggs.com/nyggs/enterprise-resource-planning-erp-system-modules/
OpenFOAM solver for Helmholtz equation, helmholtzFoam / helmholtzBubbleFoamtakuyayamamoto1800
In this slide, we show the simulation example and the way to compile this solver.
In this solver, the Helmholtz equation can be solved by helmholtzFoam. Also, the Helmholtz equation with uniformly dispersed bubbles can be simulated by helmholtzBubbleFoam.
Software Engineering, Software Consulting, Tech Lead.
Spring Boot, Spring Cloud, Spring Core, Spring JDBC, Spring Security,
Spring Transaction, Spring MVC,
Log4j, REST/SOAP WEB-SERVICES.
Globus Connect Server Deep Dive - GlobusWorld 2024Globus
We explore the Globus Connect Server (GCS) architecture and experiment with advanced configuration options and use cases. This content is targeted at system administrators who are familiar with GCS and currently operate—or are planning to operate—broader deployments at their institution.
May Marketo Masterclass, London MUG May 22 2024.pdfAdele Miller
Can't make Adobe Summit in Vegas? No sweat because the EMEA Marketo Engage Champions are coming to London to share their Summit sessions, insights and more!
This is a MUG with a twist you don't want to miss.
How Recreation Management Software Can Streamline Your Operations.pptxwottaspaceseo
Recreation management software streamlines operations by automating key tasks such as scheduling, registration, and payment processing, reducing manual workload and errors. It provides centralized management of facilities, classes, and events, ensuring efficient resource allocation and facility usage. The software offers user-friendly online portals for easy access to bookings and program information, enhancing customer experience. Real-time reporting and data analytics deliver insights into attendance and preferences, aiding in strategic decision-making. Additionally, effective communication tools keep participants and staff informed with timely updates. Overall, recreation management software enhances efficiency, improves service delivery, and boosts customer satisfaction.
Code reviews are vital for ensuring good code quality. They serve as one of our last lines of defense against bugs and subpar code reaching production.
Yet, they often turn into annoying tasks riddled with frustration, hostility, unclear feedback and lack of standards. How can we improve this crucial process?
In this session we will cover:
- The Art of Effective Code Reviews
- Streamlining the Review Process
- Elevating Reviews with Automated Tools
By the end of this presentation, you'll have the knowledge on how to organize and improve your code review proces
Enhancing Project Management Efficiency_ Leveraging AI Tools like ChatGPT.pdfJay Das
With the advent of artificial intelligence or AI tools, project management processes are undergoing a transformative shift. By using tools like ChatGPT, and Bard organizations can empower their leaders and managers to plan, execute, and monitor projects more effectively.
2. Who is Ron Veen
@ronveen
ronveen
@ronveen@foojay.social
● Java developer for 20+ years
● Special Agent @ Team Rockstars IT
● Speaker @ conferences
● Writing a book about Migrating to cloud-native Jakarta EE
3. Agenda
1. Evolution of traditional applications
2. Introducing data-oriented programming
3. Modern Java support for data-oriented programming
4. Examples of data-oriented programming with Java
22. Part 2 - Introducing Data-Oriented Programming
23. Principles of data-oriented programming
● Separate data from logic
● Data is stored in generic data structures
● Data is immutable
● Data schema is separated from representation
24. Separate logic from data
● Code can be re-used in different contexts
● Testing in isolation
● Less complex systems
25. Data is stored in generic data structures
● Flexibele data model
● Use of generic functions that are not scoped to our data classes
26. Data is immutable
● Reference to the data may change, but not the actual values
● Returning new objects with different values
● Gives predictable behaviour
● Enabled safe concurrency
27. Separate the data schema from representation
● How to express the shape of your data
● XSD
● JSON Schema
28. Part 3 - Modern Java support for data-oriented programming
29. Modern Java support for data-oriented programming
● Records
● Sealed classes
● Pattern matching
● Switch functions for pattern matching
33. Pattern Matching: Instanceof
● Predicate ==> instanceof Approver
● Object to test against ==> user
● Pattern variables ==> a
● Flow scope ==> between { }
36. Part 4 - Combining Java and data-oriented programming
37. Principles of data-oriented programming
● Separate data from logic
● Data is stored in generic data structures
● Data is immutable
● Data schema is separated from representation
38. Principles of data-oriented programming
● Separate data from logic
● Could be achieved by using static methods
● Not that different from how we use beans in Jakarta EE and Spring
42. Principles of data-oriented programming
● Separate data from logic
● Data is stored in generic data structures
● Data is immutable
● Data schema is separated from representation
46. Principles of data-oriented programming
● Model the data as data
● Data is immutable
● Validate at the boundary
● Make illegal states unrepresentable
54. Summary
● Data-oriented programming treats data as first-class citizens
● Data drives your application
● Java supports data-oriented programming via records, sealed classes and pattern matching
