Cliff Robbins

We demonstrate how to store data similar to that of a schema-less graph database and execute traversal queries using the latest property graph features of relational databases.

15

Streamline your data management with Orbit ELT Data Pipelines for Amazon Redshift. Automate and sync your data seamlessly, ensuring real-time insights and efficient reporting. Learn how to unlock the full potential of your data warehouse with our expert guide. https://hubs.la/Q02yXW890 #Orbitanalytics #DataManagement #AmazonRedshift #ELT #DataAnalytics #CloudData #DataIntegration #DataWarehouse #BigData #CloudComputing #DataScience

11

1 Comment

An update on the latest book and the steps that remain before _Business Success with Open Source_ is available in print. https://lnkd.in/g3fbPUKK #OpenSource

15

DataForge today Unveils Major Product Enhancements: LLM-powered Assistant, Complex Data Handling, and Native Kafka Integration at Databricks Data + AI Summit 2024. Visit us at Booth 2 to explore our latest innovations. #DataAISummit #Databricks #DataForge #DataForgeCloud #dataintelligence #dataengineering #orchestration #etl

11

Travis Cox, our Chief Technology Evangelist, explains the SQL Bridge Module, often called a “Swiss Army Knife” for efficiently moving data between PLCs and SQL databases. It leverages Ignition’s native database connectivity to map data to any tables you want, in any format that you want. The module acts as a transaction manager for logging data with additional context, calling stored procedures, and synchronizing data bi-directionally. Learn more about this module: https://bit.ly/3JntYtr

86

5 Comments

Reduce your Report creation time with copilot for DAX management.

2

🤖 Do you use AI/ML professionally or personally? Either way, it's probably best for you to know AI ethics. Read up on Responsible and Explainable AI ⬇️

11

Don’t complicate things with graph DBs, QLs, or graph analytics. Brian Godsey, PhD explains why you don’t need a laundry list of tools for building graph RAG systems and how a simplified approach yields better results for GenAI use cases. #GenAI #RAG

20

Weekend is here, going to continue with my text export comparisons to see what's really changed. Still working on BO's. I'm seeing a lot of changed objects with no object label or modify date change. So obviously there were properties that were updated via SQL. The release team builds the upgrade OM off of modified date so these would all be missed. I went back through my install logs to see if I could find any direct SQL that may be responsible. Looks like I'll need to platform upgrade previous version and then check to see if the install some how makes this change so that it isn't needed in the OM. I'll wait to do that until after I finish my analysis. As usual I will post some of my findings on X as I go along so as not to spam my timeline here. Anything significant that I find I will also post here to support my followers in Brazil who are blocked from using X. Also my X account is relatively new so I don't have a lot of followers there yet. If you enjoy my posts, please subscribe to my X account. Thanks.

12

Building reliable data products requires more than just gathering and processing data—it demands testing. Just like in software development, testing data products ensures accuracy, integrity, and trustworthiness of insights. By catching issues early, testing prevents costly errors, enhances user trust, and drives better decision-making across the organization. At Coginiti, we see testing as a cornerstone of quality data solutions. Check out how you can easily implement testing for your data and analytic teams using CoginitiScript: https://lnkd.in/efJEhH4B #DataProducts #DataQuality #Testing #Analytics

8

In a new step-by-step tutorial, John Leung demonstrates how you can build, trigger, and parameterize a time-series data pipeline in Azure.

11

New feature release - Job metrics timeline view! Ever wonder why your Databricks job performance changes over time? You may ask yourself questions such as: “Why is my runtime increasing since last week?” “Is the cost of this job also increasing?” “Is the input data size changing?” “Is my job in danger of crashing?” Understanding why your job performance is changing is critical to both optimize costs and prevent crashes. In this post we show a new visualization timeline features to help engineers find root causes quickly. Try it out today with Gradient! #dataengineering https://lnkd.in/ebPjtU7y

7

5 Comments

If you want a deep dive in RAG?! Go watch this Ignite session on-demand! 👉https://lnkd.in/grzYsknh Farzad Sunavala did an awesome job on this presentation! #AzureAI #LlamaIndex #RAG #AIInnovation Be aware not an introduction level!

12

Unexpected and expected outcomes emerged when testing the same star schema data structures and queries across five different database technologies with comparable capacities: • SQL Server 2019 • SQL Server 2022 • Synapse Dedicated SQL Pool • Azure Managed Instance • Microsoft Fabric Looking forward to doing the same with Snowflake.

5

In today's Using Monkey Tools video, we explore the FREE SmartFile function, which accepts a file path and returns the file. Why is this so special? Three reasons: ✅ You don't need to pick the specific data source connector, just pass the function a valid file path. ✅ It can deal with a file path that switches between a local hard drive or SharePoint file path ✅ Coupled with the free Parameter Table & Function, it allows you to build dynamic file paths that are relative to where your solution is stored. If you build solutions for others and are tired of walking the user through changing the file paths when they receive their solution, this function is for you. And I'll show you exactly how to set it up to work: https://lnkd.in/g2kHvHCn

3

While the MySQL v8 releases are bug fixes and security releases only, MySQL 9.0 Innovation is a new version with additional features—as well as some changes that may require attention when upgrading. https://bit.ly/463tQu3 via InfoWorld #MySQL #OpenSource

6

1 Comment

Always nice to see approachable and easy-to-follow guides for data engineering beginners. 👍 After introducing how to build your first data platform using MySQL, Apache Doris, and Apache Flink, Mohamed Amine Turki moves a little upstream and explains on Change Data Capture (CDC) with step-by-step instructions. https://lnkd.in/g9igQNjY (P.S. Apache Doris provides a Flink-Doris-Connector with built-in CDC support: https://lnkd.in/gmPESd3V) #dataengineering #beginner #Flink #CDC

21

1 Comment