Agile Lab

?? In his latest article "Succeding with Data Mesh" published by Business Reporter, Andrea Novara explains why data guardrails are the key to successfully implementing #datamesh. As organizations shift towards more decentralized decision-making, data mesh enables teams to access, share and consume #data in real-time, empowering faster-informed decisions. But success requires setting strict #governance rules from the start. Discover how data mesh can revolutionize business performance by breaking down silos and fostering agility. In the article, Andrea dives into the importance of data ownership, governance and creating a secure platform for data autonomy. ?? Read the full article to learn more about how data mesh can drive #innovation and transform your organization. The link is in the first comment.

We’re thrilled to bring you the latest edition of the Data Architecture Elevator Espresso series, featuring an exciting session on FinOps! ??? Learn how to take charge of cost management, encourage effortless team collaboration and keep your cloud budget under control. ????? Join the fantastic Ugo Ciracì and Antonio Murgia, and don’t forget to check out https://lnkd.in/dVuT_Gkj after the episode for even more insights on #FinOps and #DataProducts. ?? Tune in on your favourite podcast platform: Podbean: https://lnkd.in/diuj4MR2 Amazon Music: https://lnkd.in/dq5-z-AY Apple Podcasts: https://lnkd.in/dXRTNpY8 Spotify: https://lnkd.in/dzhF28yi ?? YouTube (Video): https://lnkd.in/dFRyHxVj Fuel up your knowledge and elevate your #data strategy with us! ???

?? Tomorrow, we’re thrilled to be part of the Databricks Data + AI World Tour 2024 in Milan! ?? When: 26 November 2024 ?? Where: Superstudio, Milan ? Time: Starting at 9:00 AM This global event brings together industry experts and leaders to explore the latest innovations in #data, #AI and #analytics. It’s an incredible opportunity to learn how organizations are tackling their most pressing data challenges and how we can provide support by leveraging the Databricks platform to unlock the full potential of their data. ???? Don’t miss the chance to meet our team! Let’s shape the future of data and AI together!?? Oriana Palmisano Antonino Ingargiola Alberto Firpo

?? Excited to see that our Agile Nomads initiative has been highlighted in today's article by HRHeroes, focusing on the evolution of agile work and the growing importance of flexibility in the workplace. Agile Nomads, our unique initiative, is now in its 4th edition. This program empowers all Agilers to work remotely from inspiring destinations like the Canary Islands, combining #teambuilding, professional #growth and personal enrichment. ?? The article also explores broader trends in agile work, with Italy seeing 3.55 million #remoteworkers in 2024, and flexible models becoming a cornerstone of modern business strategies. Want to know more about our vision and how we’re redefining agile work? Check the first comment for the link to the full article (in Italian). #weareagilers

?? Are you navigating the complexities of cost management in cloud-based data platforms? Ugo Ciracì's latest article, "Data Product FinOps Architecture for Data Products," provides a comprehensive reference architecture to help organizations achieve cost #efficiency through better design and ownership principles. Highlights from the article: ? Understand the Bounded Ownership Design Principle (BODP) to align cost ownership with #data, #metadata, software and infrastructure. ? Explore practical models for cost attribution—from owned and shared resources to rule-based assignments. ? Learn how to design a #FinOps-ready #dataplatform architecture that supports efficient cost monitoring and allocation. ? Gain insights into the relationship between #dataproducts and the Total Cost of Ownership (TCO), emphasizing the importance of data modeling in cost optimization. Whether you're implementing #DataMesh, #Lakehouse or #DataWarehouse paradigms, this guide equips you with the tools and principles to enhance visibility, control and accountability for your cloud costs. ?? Curious to know how to take your data platform's FinOps strategy to the next level? Read the full article here. The link is in the first comment. ??

?? We're thrilled to share a new Episode of Data Architecture Elevator, Espresso Format ? In this episode, we’re diving into #PlatformEngineering, what it is, how it works and why it’s reshaping the tech landscape. ?? ??? Our host, Antonio Murgia, sits down with Andrea Novara, an expert in the field, to explore: ? A clear definition of Platform Engineering. ? Key practices and actionable insights. ? How this approach is evolving alongside ever-changing technologies. Whether you’re a tech enthusiast or a #Data professional, this episode is packed with valuable takeaways! ?? Tune in now on your favourite #podcast platform and elevate your understanding of modern data practices: #YouTube (video!): https://lnkd.in/epkNZx37 #Spotify: https://lnkd.in/epbhhxdm #Podbean: https://lnkd.in/e9fBkAyi #Amazon: https://lnkd.in/e7r65cQu #Apple: https://lnkd.in/e8CCSKty

?? We’re delighted to give a warm welcome to the newest #agilers who have recently joined us: ?? Marco Liverani – Data Analyst ?? Fabio Furnari – Data Analyst ?? Giulio Damiano Gentile – Data Engineer ?? Edson Lucas – Data Engineer ?? Andrea Nerla – Data Engineer ?? Filippo Mameli – Data Engineer ?? Fabio Carta – ML Engineer Our team is expanding, and we’re more inspired than ever to tackle innovative challenges together. ?? Interested in being part of a dynamic, forward-thinking company? Check out our Careers Page to discover opportunities to join the journey! ?? #dataengineering #hiring #datascience #dataarchitecture

It was 5 AM when my phone buzzed with that dreaded alert: "Pipeline Execution Time Exceeded 6 Hours." As I dragged myself to my laptop, I couldn't help but think about how many data engineers face this exact scenario. Data engineering isn’t just about building pipelines! As a data engineer since more than 6 years, I’ve experienced a lot of data pipelines getting into junk as either they tend to be bulky or not well optimised. In today's data-driven world, pipeline performance isn't just a technical metric—it's a business imperative. Let me share why optimization matters through real-world impacts: ** Cost of Inefficiency - A retail client once spent $50,000/month on cloud computing, only to discover 40% was wasted on inefficient pipelines - Marketing teams waiting hours for customer segmentation updates, missing crucial campaign windows - Data scientists unable to iterate on models due to slow feature engineering pipelines I got a chance to explore Agile Lab. Agile Lab approaches pipeline optimization with a methodology that transformed our operations: 1. Diagnostic Excellence ->SLA Analysis: Deep dive into performance requirements ->Baseline Metrics: Establishing clear benchmarks for: - Read/Write IO patterns - Shuffle operations - Processing throughput - Data skew patterns - Step-by-step execution times 2. Optimization Strategy ->Operation Reorganization: - Intelligent query optimization - Strategic data partitioning - Minimizing shuffle operations - Enhancing data locality 3. Resource Management ->Smart Parallelism: - Right-sizing compute resources - Optimizing worker nodes - Balancing cost vs performance Here are some examples to showcase the real Impact Across Industries: TeleCom Consider a telecom provider processing billions of call records daily. After optimization: - Processing time reduced from 6 hours to 2 hours - Cost savings of 20% - Real-time fraud detection became possible Manufacturing A global manufacturer transformed their supply chain analytics: - Production line data processing reduced to near real-time - Predictive maintenance accuracy improved by 25% - Inventory optimization saving millions annually Here’s how Agile Lab approach consistently delivers: - 20% average cost reduction - 25% improvement in data quality - 20% revenue increase through faster insights The future of data pipeline optimization isn't just about faster processing—it's about: - Sustainable computing practices - Intelligent resource allocation - Predictive pipeline management - AI-driven optimization Data pipeline optimization is a business transformation journey. Whether you're dealing with terabytes or petabytes, the principles remain the same: measure, optimize, and iterate. Remember: The best data pipeline is one you don't have to worry about. It just works. Read more about Agile Lab: https://lnkd.in/gFDiCrYB #data #engineering #datapipeline #datamining #business

?? Get ready to explore the vital world of #DataPrivacy! In this latest episode of the Data Architecture Elevator, Paolo Platter hosts Antonio Murgia and Francesco Valentini as they dive into the complexities of protecting personal and sensitive data. From modern challenges to cutting-edge solutions, they show how leading technologies tackle real-world #privacy issues. ?? Key Topics Include: -Solutions from industry top leaders -Insights from experts in the field. ?? Tune In on Your Favorite Platform: #YouTube (video): https://lnkd.in/dGm7nzZv #Apple: https://lnkd.in/dKmVEQyR #Amazon: https://lnkd.in/dsX88yNF #Podbean: https://lnkd.in/dcjPSe8f #Spotify: https://lnkd.in/dFaxHxC8 Don’t miss this must-listen episode for anyone invested in data privacy and #innovation. Subscribe today to stay informed on the latest in #dataarchitecture! #podcast #Accelario, #TonicAI, #SDV, #Snowflake, #Databricks, #Iceberg, #DeltaLake, #Dreamio, #Denodo, #Spotfire

Data Mesh is one of the most talked-about paradigms in #datamanagement today. But as many organizations attempt the transition, confusion often arises, especially when it comes to the #dataproduct.? In his latest article, "The Data Product Trap", Paolo Platter dives deep into the core components of a real data product and the common pitfalls that can derail a #datamesh implementation. ? From data product infrastructure and #metadata to business logic and change management, Paolo explains why simply packaging datasets and assigning an owner is not enough. If your organization is looking to create genuine value from its data mesh, this is a must-read. ?? Read the full article! The link is in the first comment ??