Matillion’s Post

Total Wine & More, Paxos, Sharp HealthCare and dbt Labs shared how they found ways to reduce costs in the data workflow and get more out of their existing investments. 📈 At Sharp HealthCare, the optimization effort wasn’t about saving money – their expenditures stayed flat. Instead, it was about doing more with the same price. With dbt Cloud, the team unlocked new agility and possibilities for delivering value. The IDE and the new CI/CD process were especially impactful. ✅ “I can bring in business analysts now - they can get into dbt Cloud, create models, and deploy them to Snowflake,” said Clay Townsend, principal data architect at Sharp HealthCare. “And I’m aware of it. I can see the code. We have automated tests firing. You get all these passive benefits that we didn’t have before.” 🔥 https://lnkd.in/dA_4HRUf

Amazon Glue’s visual workflows provide your organization with an accessible solution for the seamless ingestion of diverse data sources. Are you interested in learning how you can start your data discovery journey? We invite you to read the following article by Noah Shaw, exploring how technical and non-technical personnel can get started ingesting this data today. To learn more about how Ippon Technologies and Amazon Glue can help you shape your data ecosphere, visit: https://lnkd.in/dETZMhpU #aws #awspartner #glue #cloud #data #ippontech #ippontechblog

Sharing my latest blog post which offers a deep dive into the capabilities of Snowflake Dynamic Tables and how Dynamic Tables revolutionize data engineering by automating transformations with SQL, delivering real-time insights and slashing data pipeline complexity in the Snowflake AI data cloud. I hope this information is beneficial for the Snowflake community. Stay tuned for more updates and feel free to share this with anyone who might find this useful. https://lnkd.in/gzqWDWjH #Snowflake #LTIMindtreeXSnowflake #FutureFasterTogether

Check out my most recent article on AWS Glue! ☁

If you are anything like me, you try not to experience getting sucked into what feels like "hype." Yet, these shifting waters where Data and Analytics are concerned have many existing assessments. Joe Reis 🤓 has a recent post about what is termed the MDS or "Modern Data Stack." This at it's most conceptual level being some version of cloud infrastructure with some amount of consolidation of data sources across applications and systems. If you read further, more is revealed for some modern history. My only remaining question is: How can EFS replace such an acronym? Everyday Financial Sense being a concept near and dear to my heart as a hoped for rationale embedded in a sense of opportunity inside the engines of commerce. See the full post here: https://lnkd.in/eJFw3Hei

Looking for a comparison of two excellent cloud data platforms? Check out this informative summary of Databricks and Snowflake! While both platforms are excellent, they each have different approaches and excel at different use cases. This article provides a comprehensive comparison of the two platforms to help you decide which one is best for your business needs. Check it out here: https://lnkd.in/gyCeFJyg #datafabric #moderndataarchitecture #datalakehouse #dataarchitecture #datalake #datawarehouse #dataengineering #ELT #ETL #streaminganalytics #nearrealtime #datapipeline #clouddatawarehouse #datamesh #deeplearning

Confused between which cloud data platform suits your business needs the best? In this blog on Databricks v/s Snowflake written by Lakshmi Haswitha Madupalli, we explain how the two stand out with their unique capabilities. Databricks excels in data engineering, real-time analytics, and machine learning, while Snowflake offers top-tier security, scalable warehousing, and support for diverse data formats. Choosing between them hinges on your specific data types, budget, and compliance requirements. Read the entire blog to understand how these platforms can transform your data management and drive informed decisions! 🚀 🔗 https://lnkd.in/gW_XPW2T #Databricks | #Snowflake | #DataScience | #DataEngineering | #DataAnalysis | #Analytics | #MachineLearning | #DataAnalytics | #Data

Your large, complex analytical workloads might be driving up your cloud data warehouse costs. 🤑 Next Wednesday, Starburst and GigaOm are discussing a recent field test that proves how Starburst can complete your data warehouse strategy - providing greater access to sources outside the warehouse and similar performance directly on the lake. Register below. #trino #datalake #datawarehouse #bigdata #sql #analytics

Exciting update for Dremio Cloud users! 🎉 Introducing Dremio Arctic as the default catalog for new projects. 📚 Enhance your semantic layer experience with data as code management and automatic maintenance of your Apache Iceberg tables. 🏔️ Start building your data lakehouse effortlessly and empower your data consumers like never before! 🔗 Learn more: https://bit.ly/3KZo1Vq #DremioArctic #DataLakehouse #EmpowerData

👉 Choosing the Perfect Database for Real-Time Analytics Choosing the right database can make or break your data strategy. In a recent blog post by the one and only Sarung Tripathi from SingleStore, the key criteria for evaluating real-time analytics databases are highlighted: 👉 data size, 👉data ingestion, 👉query execution, 👉query complexity, and 👉concurrency. Real-world examples from companies like IEX Cloud, Heap, Adobe, and GoGuardian illustrate how different databases measure up against these criteria, with SingleStore often emerging as a top performer. If you're navigating the complex landscape of database selection, this blog offers valuable insights and success stories. Read more here: Choosing Your Next Database https://lnkd.in/dAtgAumA #DataAnalytics #BigData #DatabaseSelection #RealTimeAnalytics #TechInsights