Kinetica ’s Post

Turbodata staging layer. The staging layer can be used to get json or odbc data across multiple companies. For real time transactions querying takes place directly through staging layer(without going through ods layer-historical)https://lnkd.in/g2iwGGqe Implications Turbodata can be used for real time and historical extracts both operational and historical mis

💻 On-demand webinar https://bit.ly/3Vf2rR2 A common data environment (CDE) is the foundation for information management across infrastructure organisations, from engineering and construction to asset owner operations and maintenance. Data integration is about bringing information together from a CDE and providing users with a unified view of information.    Working with customer examples this on-demand webinar shows you how you can use FME to enable seamless data integration from CDEs. #FMEWebinar #FMETraining #FMETools #FME

#ETL Techniques Webinar Part 3 - Mastering Large Datasets Join Orbweaver's Chief Architect, David Antosh, and Wilmer Companioni, Director of Business Development, as they discuss ETL pipeline management fundamentals and overcoming the challenges of large datasets unique to the electronics industry. Understand the impact of realistic testing, effective metrics, and adaptable data models to keep up with the rapid growth and change in the industry. Learn more and listen to the full webinar at https://lnkd.in/e5d9H99Y #electronicsindustry #dataquality #dataoptimization #digitaltransformation

Data lakehouse architectures are gaining popularity due to the flexibility and cost effectiveness that they offer. The link that bridges the gap between data lake and warehouse capabilities is the catalog. The primary purpose of the catalog is to inform the query engine of what data exists and where, but the Nessie project aims to go beyond that simple utility. In this episode Alex Merced explains how the branching and merging functionality in Nessie allows you to use the same versioning semantics for your data lakehouse that you are used to from Git.

A new version of the schema for data solution automation is ready 🎉! Another step towards completing the end-to-end automation of everything data 😀. Details and examples are in this blog post: https://lnkd.in/gKKXjrKc. Building your own data automation framework, using any of the open source tools, or Agnostic Data Labs? Check it out. Get it from Github (https://lnkd.in/g4Ukm_uw) or NuGet (https://lnkd.in/ghvfu-MZ)!

data.projectpi.xyz Introducing the new Pi Pool dashboard: We've migrated our data from pools.projectpi.xyz to data.projectpi.xyz. You can now track all your Pi Pool metrics seamlessly under the Pi Pool section. docs.projectpi.xyz -Updated documentation We look forward to sharing more detailed updates in the near future! ⚙️ #PulseChain

As we gear up for mainnet, we're enhancing our dashboard to create a comprehensive hub for both Pi Pool metrics and #PulseChain updates. Our documentation is also being streamlined to ensure everything is user-friendly, organized, and easy to navigate. #ProjectPi #10in5 #PulseChain #LiquidStaking

Want to know more about data lakehouse architectures? Check out this podcast with Tobias Macey and Dremio's Alex Merced!

A Deep Dive Into Data Orchestration With Airbyte, Airflow, Dagster, and Prefect https://lnkd.in/duPUwvVM This article delves into the integration of Airbyte with some of the most popular data orchestrators in the industry – Apache Airflow, Dagster, and Prefect. We'll not only guide you through the process of integrating Airbyte with these orchestrators but also provide a comparative insight into how each one can uniquely enhance your data workflows. We also provide links to working code examples for each of these integrations. These resources are designed for quick deployment, allowing you to seamlessly integrate Airbyte with your orchestrator of choice.

THREAD®️ together your Dataiku datasets and created definitions to formalize a catalog for improved understanding and governance. A free, lightweight cataloging tool, THREAD®️ ties together your data lineage and provides a single location to document data connected to Dataiku. Give THREAD®️ a try: https://lnkd.in/eVy9Y-Z8 #Cataloging #Data #Governance #Value