Rathin Vora

Regulation 1071 promises more transparency in small business lending for women and minorities in 2024. But it also brings challenges for lenders. Our blog explores the impact on loan availability, costs, and opportunities. Read more and stay informed: https://lnkd.in/gz687PdW #smallbusiness #lending #regulation1071

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Differences Between Ozone and HDFS: A Comparison of Distributed File Systems Ozone and HDFS are both distributed file systems, but they have some key differences: 1. Architecture: - HDFS (Hadoop Distributed File System) is the default distributed storage system in Hadoop. It follows a master-slave architecture with the NameNode as the master node managing metadata and DataNodes as the slave nodes storing the actual data. - Ozone, on the other hand, is a scalable, redundant, and distributed object store designed for Hadoop. It is part of the Apache Hadoop Ozone project and is built on the Hadoop 3.x architecture. 2. Storage Model: - HDFS is primarily a file-based storage system where data is stored in files and directories. - Ozone, however, is an object store that provides a REST API for storing and retrieving objects. It works with large volumes of unstructured data and is optimized for cloud-native applications. 3. Scalability: - HDFS has been known for its scalability in handling large-scale data processing jobs. - Ozone is designed to provide better scalability compared to HDFS, especially in terms of handling massive amounts of data and a large number of nodes. 4. Data Replication: - HDFS replicates data by default across multiple DataNodes to ensure fault tolerance. - Ozone uses software-defined storage that allows for custom data replication policies and data redundancy based on user requirements. 5. Use Cases: - HDFS is commonly used for batch processing, data warehousing, and other big data processing applications. - Ozone is suitable for scenarios requiring scalable object storage, such as modern data analytics, machine learning, and AI applications. These are some of the key differences between HDFS and Ozone in the context of distributed file storage systems within the Hadoop ecosystem. If both Apache Ozone and HDFS are utilizing the same Hive Metastore (HMS) for metadata management, it is possible for users to access and manage data stored in both systems using the shared Hive Metastore. This allows for seamless integration and access to metadata across both storage systems.

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Ready to take your lending strategy to the next level? Discover how Credit Builder Products can supercharge your efforts and empower your clients' financial journeys. Dive into our latest blog to learn more: https://lnkd.in/g65ZQbnp #CreditBuilder #LendingStrategy #FinancialEmpowerment #CreditBuilderProduct #CreditBuilderLoan #LoanOrigination #LoanServicing

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'Explore the intricacies of JCL SORT JOINKEYS for merging two files efficiently. Learn how to pair and unpair data using JCL JOINKEYS with DFSORT. Enhance your understanding of JCL and streamline your sorting processes. Stay ahead in the game with advanced JCL techniques. https://buff.ly/3YFkG5c #JCL #DFSORT'

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Proud to share our latest insights from FIIT Consulting! 🌟 Dive into our blog post where we compare the benefits of Single Stack ERPs and Dedicated Subledgers. Discover how to achieve real-time insights, operational excellence, and compliance by leveraging both solutions. Check out the full article to find the best fit for your financial strategy: https://lnkd.in/ggA2xWsV #FIITConsulting #FinancialExcellence #ERP #Subledger #AptitudeSoftware #RealTime

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Regulation 1071 promises more transparency in small business lending for women and minorities in 2024. But it also brings challenges for lenders. Our blog explores the impact on loan availability, costs, and opportunities. Read more and stay informed: https://lnkd.in/gvMxhY8S #smallbusiness #lending #regulation1071

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In today’s fast-paced software industry, maintaining a balance between stability and innovation is a challenge that every enterprise faces. As we strive for relentless improvement, a key principle in SAFe (Scaled Agile Framework), the choice of foundational technologies like Java versions becomes even more critical. Java’s Long-Term Support (LTS) versions are more than just stable releases—they’re a strategic choice that aligns perfectly with the goals of continuous improvement. While Java 8 remains a trusted workhorse in many organizations, the industry is steadily shifting towards Java 11 and Java 17, which offer enhanced performance, security, and a foundation for innovation. Java 21 Garbage Collector management is pure gold, indeed. In the spirit of relentless improvement, organizations adopting SAFe understand that to stay competitive, they must continuously refine and optimize their processes, tools, and technologies. Upgrading to newer LTS versions of Java isn’t just about adopting the latest features; it’s about ensuring that your systems are secure, reliable, and ready to support ongoing improvement efforts. LTS versions provide the stability needed to focus on scaling agile practices without the distraction of frequent major upgrades. They also ensure that teams can concentrate on delivering value, knowing that their foundational technology is robust and well-supported. For enterprises committed to relentless improvement, the move to a newer Java LTS version is not just a technical upgrade—it’s a strategic decision that supports the broader goal of continuous enhancement in both process and technology. As you plan your next steps, consider how this choice can enable your teams to build more resilient, future-proof solutions while maintaining the agility needed to adapt and thrive. #SAFe #Java #ContinuousImprovement #EnterpriseAgility #LongTermSupport #AgileTransformation #SoftwareDevelopment

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Just finished the course “Azure DevOps: Continuous Delivery with YAML Pipelines” by Mike Benkovich! Check it out: https://lnkd.in/geiMmRTv #azuredevopsservices #continuousintegrationandcontinuousdeliverycicd.

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🔧 Exciting News! I just completed the Liquibase and the CI/CD Process course!  🎓 This course is perfect for anyone eager to integrate Liquibase seamlessly into their CI/CD pipelines. I delved into core DevOps and CI/CD concepts, learned how Liquibase fits into the process and explored automation tools to streamline database changes. Plus, I mastered source control management best practices and database testing for the Liquibase build environment. If you're diving into CI/CD and #DevOps, don't miss out on how Liquibase can level up your database automation! 🚀 #Liquibase #DatabaseAutomation #TechSkills

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Join this session to learn the basics of REST APIs and practical applications across various tools and services, including: Postman, curl, Oracle Database, Data Integration, Oracle Analytics Cloud, and #OCI AI Generative Services. https://lnkd.in/dvCDguFF

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Very recently, I had the opportunity to cook for over 70 people, a challenging experience showcasing the complexity of scaling up simple tasks. What appeared effortless on a small scale became intricate with larger volumes, mirroring challenges in platform architecture and automation. At low volumes, imperfections may slip by unnoticed, but scaling up demands perfection. The key is to emulate a production line - meticulous organization, understanding, and preparation are paramount for seamless operations at scale. Lessons learned? Firstly, experimentation at scale is a no-go; perfect first, then scale. Secondly, dont under estimating scaling complexity. Lastly, respect those who excel in the field; it's truly an impressive feat. #PlatformArchitecture #Automation #ScalingUp r

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🎯What is Event Sourcing? How is it different from normal CRUD design? The diagram below shows a comparison of normal CRUD system design and event sourcing system design. We use an order service as an example. The event sourcing paradigm is used to design a system with determinism. This changes the philosophy of normal system designs. How does this work? Instead of recording the order states in the database, the event sourcing design persists the events that lead to the state changes in the event store. The event store is an append-only log. The events must be sequenced with incremental numbers to guarantee their ordering. The order states can be rebuilt from the events and maintained in OrderView. If the OrderView is down, we can always rely on the event store which is the source of truth to recover the order states. Let's look at the detailed steps. 🔹Non-Event Sourcing Steps 1 and 2: Bob wants to buy a product. The order is created and inserted into the database. Steps 3 and 4: Bob wants to change the quantity from 5 to 6. The order is modified with a new state. 🔹Event Sourcing Steps 1 and 2: Bob wants to buy a product. A NewOrderEvent is created, sequenced, and stored in the event store with eventID=321. Steps 3 and 4: Bob wants to change the quantity from 5 to 6. A ModifyOrderEvent is created, sequenced, and persisted in the event store with eventID=322. Stay Connected to Sidharth Sharma, CPA, CISA, CISM, CFE, CDPSE for content related to Cyber Security. #CyberSecurity #JPMC #Technology #InfoSec #DataProtection #DataPrivacy #ThreatIntelligence #CyberThreats #NetworkSecurity #CyberDefense #SecurityAwareness #ITSecurity #SecuritySolutions #CyberResilience #DigitalSecurity #SecurityBestPractices #CyberRisk #SecurityOperations 

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never stop learning

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When you realize you have learned many technologies and only few are in utilization...after a time you feel like sand in your fist. Therefore, keep updating yourself with new learnings. Completed AWS AMS training successfully 😊

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Another game changer in API economy. Postbot provides cost-effectiveness by automating integration tests, optimizing resource utilization, and minimizing API error rates with consistent and accurate results. No doubt it will streamline the testing process and henceforth enhancing productivity, accelerating development cycles for faster time-to-market. Milan's article on generating Tests using AI capabilities of Postbot within the .NET space is indeed valuable for developers & testers seeking to enhance their skills and efficiency in this domain.

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