Redpanda Data’s Post

The "modern data stack" promised a scalable, composable data platform that gave everyone the flexibility to use the best tools for every job. The reality was that it left data teams in the position of spending all of their engineering effort on integrating systems that weren't designed with compatible user experiences. The team at 5X understand the pain involved and the barriers to productivity and set out to solve it by pre-integrating the best tools from each layer of the stack. In this episode founder Tarush Aggarwal explains how the realities of the modern data stack are impacting data teams and the work that they are doing to accelerate time to value.

Prioritizing Data Quality Harmony’s data engineering team aggregates and cleanses diverse data sources to construct a single dataset. From here, proprietary algorithms normalize, transform, and scale raw data into standardized metrics. #HarmonyAnalytics #DataQuality #DataEngineering #BusinessIntelligence

Smart Data City (SDC) is Nuklai vision of building a unified smart data ecosystem. SDC will create an inclusive, collaborative data ecosystem where institutions, individuals and project creators come together for innovation and multi-faceted creativity. #Nuklai has already achieved resounding success, including the launch, the first smart data research projects and the first builders willing to work on Nuklai. Nuklai Smart Data Layer 1: A Flexible Foundation for Innovation. - This layer is currently in the preliminary testing phase and will soon move into the Nuklai Helix Testnet, providing a dedicated dual-network architecture for smart data. It will also support multiple programming languages for smart contracts. - The Smart Data Layer 1 framework improves data management and security for collaboration, and enables developers to create innovative projects based on the Nuklai network. It also provides the foundation for a strong and flexible smart data ecosystem. Smart Data Onboarding and Querying: Seamless Integration and Insights. Nuklai is developing connectors to seamlessly publish data from managed environments (e.g. cloud) and introducing improved querying and deep contextualisation capabilities in the Nuklai application. This will enable users to combine data from different sources. These enhancements will simplify data integration and analysis, opening up new opportunities for deeper insights from intelligent data and more sophisticated AI training. For organisations looking to make better use of their data, this will be a game changer. App Migration Testnet: Optimized Operations and User Experience. Testnet’s App Migration test network provides a seamless transition from the Avalanche core network to the Nuklai Helix test network. Nuklai is developing functionality to integrate all existing and new capabilities into the Nuklai network and application. This transition will allow the application to operate on the Nuklai network where operations can be optimised for collaboration and data sharing. Some operations can be made gas-free or more efficient depending on specific requirements, which will greatly improve the user experience. Nuklai is excited and can’t wait to realise the vision of the Smart Data City ecosystem through the Nuklai roadmap. #SmartData | $NAI

Organizations with petabytes of data can’t be bound to specific tooling. This big data pipeline is designed for tech leaders to seamlessly “lift and shift” 🔄 as new technologies and data sources are introduced. 🛠️ Learn how we built a first-of-its-kind, flexible, open-source big data pipeline. Watch the “Data Pipeline Modernization at Scale” talk here: https://lnkd.in/e9JztSpX #BigData #SoftwareEngineering #pythonprogramming

The data landscape is evolving fast! Key trends for Business Analysts: GenAI impacts strategy and customer service, emphasizing data ethics. Hybrid/multi-cloud environments drive data mesh and fabric architectures for better accessibility. Check out the DBTA 100 for top data management innovators. Stay ahead in the data-driven world! Link: https://lnkd.in/gbpMB4Jr #sceds #econlib #businessanalytics #data #datamanagement #bigdata #daf #nsbmgreenuniversity

SentinelOne Data Lake: AI-Powered Unified Data Lake Data to Actionable Intelligence Centralize and Transform Data for Cost-Effective, High-Performance, Security and IT Analytics. #datalake #ai

From the article: Over the course of ~7 years, “modern data stack” went through a cycle: from descriptive technical term to meme / market trend to ecosystem. Today, IMHO, it’s no longer useful in any of those roles. Today, I’m swearing off using the term “modern data stack” and I think you probably should too. This week my issue of the Analytics Engineering Roundup is part history, part strategy, part call-to-action. I'd love your thoughts if you manage to get through all 3,000 words :D

This is an article I recommend reading. When do we drop off the "modern" moniker and call it a data stack? We are now several years into this phase. Also, many millions of dollars have been on transformations. The narrative needs to be adjusted. What makes something "modern" in 2024? Many data teams have started on their journey or are midway through data modernization efforts. Now, businesses will start to ask questions about their investments in these data platforms. ➢ "At what point do we become modern?" ➢ "Are we modern yet?" ➢ "What benefit(s) has this modernization provided the business?" Don't forget the other question that will be asked, "Does this modern data stack allow us to do AI?" Perhaps we read the room a bit and see if our messaging starts to deteriorate over time. Are we using the same phrases and talking points that we used 4 years ago? The economy, marketplaces, and industries have changed. #showthemoney #controlthenarrative

What's your take on the future of data fabric? How do you see AI shaping data management? Malcolm Hawker, Head of Data Strategy at Profisee, addressed it best at this year’s Data Hero Summit. 🚀 "The data fabric is about a lot more than just an integration layer. In my mind, the data fabric is a data management architecture where data itself informs its classification and use." Share your thoughts in the comments! 💬📢 Don’t forget to sign up to watch the full on-demand video at 👉 https://ow.ly/5LI850QgQza    #DataHeroSummit #MasterDataFabric #AIinDataManagement 

Interesting post by Tristan Handy. We published something similar last week -- https://lnkd.in/eNsGy_Ys. Below are thoughts ⬇ “When facing the proliferation of tools that came with MDS, it is easy to lose focus on what is important and succumb to the pursuit of the next shiny object. In order to not lose track of what matters, I always go back to first principles. You’re building an infrastructure and to do so, you need: movement, storage, processing and a bit of observability. Focus on getting those fundamentals right. Only then you need to figure out the tools to interact with the data and extract insights from it. That’s when you need to think about the persona working with that data, and that’s what should drive your choice, not the fancy marketing of yet another solution.” Michel Tricot, Co-founder & CEO at Airbyte. https://lnkd.in/ee4c_TSe