Matia

ICYMI: February meant big releases at Matia, helping data teams work even smarter ? New RETL Destinations – Activate data from your warehouse to Mixpanel, Slack or Amplitude (plus dozens of others) ?? Global search, supercharged – Newly designed search mean you can surface anything in Matia in seconds ?? Issues & notifications – Stay ahead with real-time alerts in one central dashboard and bi-directional, real-time slack notifications ? Asset Draft Mode – **WIP**, we got you. Experiment, iterate, and collaborate more effectively an save your in process connectors, no do-overs required Check out the full breakdown of our latest updates and see how Matia is powering next-level data operations. #ICYMI #DataOps #Matia #ProductUpdates #DataIntegration

One of the biggest questions I get from customers is how to save on Snowflake costs. While using Matia can help indirectly lower Snowflake costs (more on that later), it’s not inherently a cost optimization platform like SELECT and many other strong platforms on the market. There are things you can do today without investing in any additional tools that will most likely dramatically lower your bill. One of the biggest hidden cost drivers in Snowflake? Inefficient joins. When joins aren't optimized, they slow down queries, consume more compute resources, and inflate warehouse costs. Many teams don’t realize that their Snowflake bill is silently growing because of suboptimal joins. The key to reducing this unnecessary cost is helping Snowflake’s optimizer make better decisions. How to Optimize Joins and Cut Costs ?? Define Primary and Foreign Key Constraints Even though Snowflake does not enforce them, adding constraints gives the optimizer better insights into table relationships. This reduces unnecessary processing leading to faster joins. ?? Use Unique Constraints When Snowflake knows a column is unique, it avoids full-table scans and speeds up distinct lookups. This significantly improves performance on large datasets. ?? Optimize Clustering Keys Clustering large fact tables on common join keys such as customer_id or order_id improves data locality. This means Snowflake scans less data when processing joins, reducing compute costs. ?? Choose the Right Join Strategy Snowflake automatically selects a join type, but understanding how they work helps you structure data more efficiently from Broadcast to Merge to Hash. ?? Leverage Materialized Views for Heavy Joins If you frequently join the same tables, a materialized view stores the results so queries can skip recomputing expensive joins each time. ?? Take Advantage of Snowflake’s Result Caching Snowflake caches query results for 24 hours. If you are running the same joins repeatedly, reusing queries instead of writing variations ensures you get near-instant results at no extra cost. The Business Impact? Lower Costs and Faster Queries Optimizing joins does not just improve performance. It directly reduces your Snowflake compute costs. For a deeper dive into optimizing Snowflake joins, check out the article:

First AI takes our jobs, now it's coming for happy hour (maybe...) Plus we love Databricks' automatic liquid clustering release and some fun Matia updates from one of the fastest moving product and engineering teams we've ever seen. Check out the latest thoughts on data (and anything else we find interesting) from Benjamin Segal ?? ?? ?? ??

With global data volumes set to hit 200 zettabytes this year, traditional ETL pipelines are struggling to keep up. That’s why Change Data Capture (CDC) has become essential. Instead of costly full refreshes, CDC streams database changes in real time, keeping data lakes, warehouse, and AI models up to date without slowing down critical systems. ?? Why CDC is a game-changer: ? Eliminates expensive full refreshes & reduces query load ? Improves real-time analytics & AI model updates ? Supports high-throughput, low-latency pipelines ? Enables modern architectures with Kafka, Snowflake Streams & more We put together a deep dive on CDC. ?? Read it below (ungated - no forms)

Scaling a logistics company ? Not easy. But Solvento made it happen—while cutting data warehouse costs and ensuring real-time freight payment tracking. They switched from a legacy OS solution to Matia, and here were some of the results: ?? 63% faster sync times moving data from PostgreSQL & MySQL to Redshift ?? 20% lower warehousing costs ? 50% faster incident response with integration failures resolved in half the time See how Solvento built a more efficient, scalable data stack with Matia. Link in comments

A fun night with Snowflake User Group - Tel Aviv. Thanks for hosting a great talk with Geva Segal. Here’s what he covered ?? ETL vs. ELT—because acronyms are fun, but making the right choice matters. ?? Why everyone at a company is a data stakeholder—sales, support, product, marketing—you name it—because reliable data powers every decision. ?? The challenges we faced at Matia and how Snowflake helped us tackle them. ?? Best practices for ETL—from knowing when to Merge vs. Append to keeping your security team happy with RBAC, plus some Snowflake favorites like Data Share perks, transient tables, network hacks, and even a touch of Copy Zero magic—because every optimization counts. More to come ?

?? Alert fatigue is real. ?? Compounded with the fact that you probably have at least 6 different tools you’re getting alerts from. We feel for you, data teams. You don’t need more tools sending more alerts. You need one place that actually makes sense of it all. ??Introducing Matia’s enhanced Issues & Notifications, our newest product release. Here's what you get: ? ETL & Reverse ETL issues, schema changes, and data quality alerts—in one platform.? ? Real-time Slack notifications with actual solutions, not just “something’s broken.”? ? No more bouncing between tools—see, diagnose, and fix everything right inside one dashboard. Start managing your data. Not your tools. Learn more about this latest platform enhancement in the link below.? ?#dataengineering #ETL

?? Netsuite Connector now live ??

?? Attention TLV Data Community ?? Join us at the next Snowflake User Group - Tel Aviv on March 4th. Multi-tenancy and data ingestion/ETL at scale are critical for modern data teams. Our CTO, Geva Segal, will be diving deep into strategies for optimizing ingestion, managing multi-tenant architectures, and reducing operational complexity, all powered by Snowflake. ?? Come ready with questions and let’s talk about making data work smarter, not harder. ?? Link to signup: https://lnkd.in/gC2ZVC7Q #SnowflakeTLV #DataEngineering #DataOps

You know you're a data engineer when... ?? ?An analyst pings you to get "just a few tables" to the warehouse and you know it's going to take all day ?? ?You're tired of explaining to people that data warehouses don't hold every piece of data your company owns ? You see SELECT * in production and physically cringe ? You've been personally victimized by a schema change ? No one (even engineers) really understands what you do What would you add?