Learn how to implement data time travel with Ducklake and Tigris to easily recover from database mishaps. This guide demonstrates how Ducklake creates snapshots for every `INSERT` or `DELETE` operation, allowing you to explore your analytics database as it was before disaster struck.| Tigris Object Storage Blog
Combine SQL and object storage data seamlessly with DuckLake, a data lakehouse solution that works with Tigris. Query big and small data without egress fees and simplify your data analytics workflows.| Tigris Object Storage Blog
Reading Time: 4minutesImagine you’re a financial analyst at a pension fund, racing against the clock to deliver a major corporate client’s portfolio breakdown before fiscal year end. You’re juggling CRM data, financial market reports, and a tangle of Excel exports. Or picture... The post Beyond the Lakehouse: Denodo’s RAG-Driven Data Revolution appeared first on Data Management Blog - Data Integration and Modern Data Management Articles, Analysis and Information.| Data Management Blog – Data Integration and Modern Data Management Articles...
Learn 5 key considerations for building a scalable, cost-effective GCP data lake. Optimize performance, storage, and analytics on Google Cloud.| HatchWorks AI
Learn the key differences between data lakes, warehouses, and marts, their use cases, and best practices to choose the right data solution.| HatchWorks AI
In industrial operations, getting data to the cloud is critical to gain insights for increased productivity. Getting the data is simpler; the challenge today is making that data useful once it gets there. Too often, companies race to implement cloud connectivity, collect massive volumes of OT data, and then find themselves stuck. The dashboards don’t… The post Why context is everything: Avoiding data swamps in the cloud appeared first on Cirrus Link.| Cirrus Link
AI analytics today allow us to break down and analyze all parts of a business. Today, we will quickly talk about using a data lake and data pipelines to help streamline data analytics. Every internal and external interaction can be scrutinized and perfected to create a well-oiled, efficient machine. Consumer data, inventory management, market trends, […] The post Streamlining Data Analytics with Data Pipelines and a Data Lake appeared first on ProcureSQL Data Architect as a Service.| ProcureSQL Data Architect as a Service
Data lake architecture has recently become a hot topic. These days, businesses use data to define their internal business objectives and metrics.| Apiumhub
The data lakehouse has emerged as a powerful and popular data architecture, combining the scale of data lakes with the management features of data warehouses.| Data Management Blog - Data Integration and Modern Data Management Articles, ...
Gartner® has had a long history of analyzing the potential of a logical approach to data management. In the context of data management, “logical” doesn’t mean “sensible” so much as the opposite of “physical”.| Data Management Blog - Data Integration and Modern Data Management Articles, ...
Discover how multiple storage backends support in lakeFS provides a capability that unifies data management across all your storage systems.| Git for Data - lakeFS
AI data storage solutions are a key component of the modern AI landscape. Discover benefits, common challenges, and best practices. Read more| Git for Data - lakeFS
Learn how to get started with data lake implementation. Explore the essentials to enhance your data management strategies.| Git for Data - lakeFS
The latest release of the Vertica analytical database, now OpenTextTM VerticaTM includes a lot of features that Vertica customers have been eagerly awaiting like: Resharding the database as needed Rollback snapshots that capture a moment in time without a whole other data copy Workload routing so you can automate directing specific queries to just the right compute for that type of job. And more ...| OpenText™ Vertica™
IBM has taken another open source technology provider into its portfolio, acquiring Ahana, one of the leading vendors behind the massively parallel distributed in-memory SQL query engine Presto. Presto, first created and still actively developed at Meta, has attracted a broad array of open source contributors, and is championed by several vendors. It has alsoContinue reading "IBM and Ahana – A Lakehouse Down Payment"| IT Market Strategy
Oh my my look what the cat dragged in| Port 1433
Tom Breur 31 August 2019 The job market is “hot”, and data science skills are in high demand. Yet many junior data scientists are struggling to get ahead. How can that be? Is it because ever…| Data, Analytics and beyond