Chaos Genius

Chaos Genius is proud to sponsor the #DataAISummit by Databricks!! Crazy excitement about Data & AI ROI as organizations embark on their AI journeys. If you're attending and looking to optimize your costs on Databricks, visit us at booth #81 Team Chaos Genius - Amatullah Sethjiwala Sahan Penakalapati Manas Solanki Kartikay Bagla Varun Purushotham Bhargav S. kumar Debanjan Dey Amogh Dhar Diwan Amrasha Srivastava Preeti Shrimal Poorva Mendiratta #chaosgenius #databricks #DataAISummit #finops #Moscone

Nothing beats the community spirit of the Data Heroes- Community for Data Folks. This evening we caught up on a quick discussion led by Manas Solanki and influenced by Mani on ClickHouse and its fitment for real-time analytical use cases. We compared Pinot, Druid and discussed the pros/cons. True to the community spirit, this session was not recorded to foster an open collaboration. Ananth P. and Aswin James Christy Nayagam will lead next Friday's community event where we develop evaluation criteria for the Data Observability space. Comment to get your invite!

Loading data into #Snowflake tables has never been easier with the INSERT INTO command. This powerful command allows you to:  📥 Insert single or multiple rows of data  🔄 Update existing tables with new info  📝 Replace or overwrite existing data when needed If you’re a #DataAnalyst, #DataEngineer, or just starting your #Snowflake journey, you need to understand the ins and outs of using the Snowflake INSERT INTO command for efficient #DataManagement. Curious to learn about syntax, performance, examples, and best practices? Check out the article below to fully understand how to use the Snowflake INSERT INTO command and take your data-loading skills to a whole new level! Dive in! 👇 https://lnkd.in/gajk5Sza

#AI is rapidly progressing, with #LargeLanguageModels (#LLMs) leading the way. Take #SnowflakeArctic and #DBRX — they're making headlines with their exceptional capabilities. In this piece, we'll compare these two LLM giants across 10 key areas: ⚡ Architecture ⚡ Number of parameters ⚡ Hardware infrastructure ⚡ Development timeline ⚡ Cost ⚡ Training tokens ⚡ Code generation benchmark ⚡ Programming and mathematical reasoning ⚡ IFEval common-sense reasoning benchmark ⚡ MMLU benchmark ...and more! Read on to find out about the fundamental differences between Snowflake Arctic and Databricks DBRX. Dive right in! 👇 https://lnkd.in/gaAd4FGW

#Snowflake rolled out its powerful enterprise-grade #OpenSource AI model — #SnowflakeArctic — just a few months ago (in April). What sets it apart is its unique and innovative #Architecture — a Dense-MoE Hybrid transformer. It's massive, with 480 billion parameters distributed among 128 experts, utilizing a top-2 gating mechanism to activate approximately 17 billion parameters during inference. And the result? Arctic blows away other models, both open source and #ClosedSource making it the perfect choice for enterprise-level applications. Check out the article below to learn everything about Snowflake Arctic. Dive in! 👇 https://lnkd.in/gQBGGBK9

#DatabricksDashboards are powerful #DataVisualization and #Analysis tools. With these #Dashboards, you can create custom, interactive visuals directly within the #Databricks platform—no need to install or use any third-party tools. Everything you need is all baked in one place! In this article, you'll learn: 📊 What exactly is a Databricks dashboard? 📊 Various dashboard options available in Databricks 📊 How Databricks Dashboards differ from Lakeview Dashboards 📊 Step-by-step guide to creating your very own Databricks dashboard …and so much more! Check out the full article below to learn everything you need to know about creating and customizing your own dashboards. Dive right in!👇 https://lnkd.in/gCqjuQRq

Selecting the right #DataTypes in #Databricks is extremely crucial. The wrong choice can slow down #QueryPerformance and degrade #DataQuality. In our latest article, we dissect #DatabricksDataTypes — from numeric, string, binary, and date & time, to more complex types like arrays, maps, and structs. In this article, you'll learn: 👉 What are Databricks data types? 👉 Which data types are supported by Databricks? 👉 Which data types are not supported by Databricks? 👉 Databricks Data Type Mappings and Conversions 👉 Best practices for selecting Databricks data types. …and much more! Check out this article to learn everything you need to know about Databricks data types! Dive right in! 👇 https://lnkd.in/gN_wbkjU

Back in March, #Databricks launched #DBRX—a super-advanced state-of-the-art open language model that's truly next-level. This new model marks a major step forward for #OpenSource #LLMs. What’s really cool is that DBRX outperforms nearly all established open source models and even rivals #ClosedSource giants like #GPT4, #Gemini, and #Mistral across various benchmarks. Want to know what makes #DatabricksDBRX so awesome? We've got you covered! Check out the full article below to learn everything you need to know about it. https://lnkd.in/g3w845G7

Stuck trying to choose the right #StorageFormat for your open #DataLakehouse? Psst... it's a common headache! There are loads of options— #DeltaLake, #ApacheIceberg, and #ApacheHudi —all with their own benefits. It's a tough choice. But here's the good news: #DeltaUniForm (Delta Lake Universal Format) is here to help! Delta UniForm enables interoperability between Delta Lake, Apache Iceberg, and Apache Hudi without creating extra #Data copies. It uses shared #ApacheParquet files and generates the necessary #Metadata for each format, allowing users to access and operate on a single copy of data across different #Ecosystems. In this article, we cover: 👉 What is Delta Lake? 👉 What is Apache Iceberg? 👉 What is Apache Hudi? 👉 What is Delta UniForm? 👉 Features and benefits of Delta UniForm 👉 Performance and scalability of Delta UniForm 👉 Step-by-step guide to creating a new Delta Table with Delta UniForm ...and more! Check out the full article below to learn everything you need to know about Delta UniForm. Dive right in! https://lnkd.in/ge2zSMwT

If you’re using #Databricks and need a robust #DataGovernance solution, #UnityCatalog is the answer. Unity Catalog is a unified governance solution for managing #Data and #AI assets within the Databricks platform. It provides centralized #AccessControl, #Auditing, #DataLineage, and #DataDiscovery capabilities across #DatabricksWorkspaces. In this article, we cover: 🔒 What is Databricks Unity Catalog? 🔒 Architecture breakdown of Databricks Unity Catalog 🔒 How to create a Unity Catalog metastore (AWS) 🔒 Step-by-step guide to set up and manage Unity Catalog 🔒 How to control access to data and other objects in Unity Catalog 🔒 Databricks Unity Catalog best practices and limitations …and much more! Check out this article to learn everything about Unity Catalog! Dive right in! https://lnkd.in/gDnx5c-B