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Delta Live Tables Announces New Capabilities and Performance Optimizations
Since the availability of Delta Live Tables (DLT) on all clouds in April (announcement), we’ve introduced new features to make development easier, enhanced automated infrastructure management,...
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Introducing MLflow Pipelines with MLflow 2.0
Since we launched MLflow in 2018, MLflow has become the most popular MLOps framework, with over 11M monthly downloads! Today, teams of all sizes use MLflow to track, package, and deploy models....
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Designing a Java Connector for Delta Sharing Recipient
Making an open data marketplace Stepping into this brave new digital world we are certain that data will be a central product for many organizations. The way to convey their knowledge and their assets...
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Recap of Databricks Machine Learning announcements from Data & AI Summit
Databricks Machine Learning on the lakehouse provides end-to-end machine learning capabilities from data ingestion and training to deployment and monitoring, all in one unified experience, creating a...
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Open Sourcing All of Delta Lake
The theme of this year’s Data + AI Summit is that we are building the modern data stack with the lakehouse. A fundamental requirement of your data lakehouse is the need to bring reliability to your...
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Introducing Spark Connect – The Power of Apache Spark, Everywhere
At last week’s Data and AI Summit, we highlighted a new project called Spark Connect in the opening keynote. This blog post walks through the project’s motivation, high-level proposal, and next steps....
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Using Airbyte for Unified Data Integration Into Databricks
Today, we are thrilled to announce a native integration with Airbyte Cloud, which allows data replication from any source into Databricks for all data, analytics, and ML workloads. Airbyte Cloud, a...
View ArticleDatabricks Ventures Invests in Tecton: An Enterprise Feature Platform for the...
Operational machine learning, which involves applying machine learning to customer-facing applications or business operations, requires solving complex data problems. Data teams need to turn raw data...
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6 Guiding Principles to Build an Effective Data Lakehouse
In this blog post, we will discuss some guiding principles to help you build a highly-effective and efficient data lakehouse that delivers on modern data and AI needs to achieve your business goals. If...
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Using Spark Structured Streaming to Scale Your Analytics
This is a guest post from the M Science Data Science & Engineering Team. Modern data doesn’t stop growing “Engineers are taught by life experience that doing something quick and doing something...
View ArticleHunting for IOCs Without Knowing Table Names or Field Labels
There is a breach! You are an infosec incident responder and you get called in to investigate. You show up and start asking people for network traffic log and telemetry data. People start sharing...
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Disaster Recovery Automation and Tooling for a Databricks Workspace
This post is a continuation of the Disaster Recovery Overview, Strategies, and Assessment blog. Introduction A broad ecosystem of tooling exists to implement a Disaster Recovery (DR) solution. While no...
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Scanning for Arbitrary Code in Databricks Workspace With Improved Search and...
How can we tell whether our users are using a compromised library? How do we know whether our users are using that API? These are the types of questions we regularly receive from our customers. Given...
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Building a Cybersecurity Lakehouse for CrowdStrike Falcon Events Part II
Visibility is critical when it comes to cyber defense – you can’t defend what you can’t see. In the context of a modern enterprise environment, visibility refers to the ability to monitor and account...
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Sync Your Customer Data to the Databricks Lakehouse Platform With RudderStack
Collecting, storing, and processing customer event data involves unique technical challenges. It’s high volume, noisy, and it constantly changes. In the past, these challenges led many companies to...
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Databricks SQL Highlights From Data & AI Summit
Data warehouses are not keeping up with today’s world: the explosion of languages other than SQL, unstructured data, machine learning, IoT and streaming analytics have forced customers to adopt a...
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Parallel ML: How Compass Built a Framework for Training Many Machine Learning...
This is a collaborative post from Databricks and Compass. We thank Sujoy Dutta, Senior Machine Learning Engineer at Compass, for his contributions. As a global real estate company, Compass processes...
View ArticleHow the Lakehouse Empowered Rogers Communications to Modernize Revenue Assurance
This is a guest post from Duane Robinson, Sr. Manager of Data Science at Rogers Communications. At Rogers Communications, we take pride in ensuring billing accuracy and integrity for our customers....
View ArticleKey Retail & Consumer Goods Takeaways From Data + AI Summit 2022
Retail and Consumer Goods companies showed up big at Data + AI Summit this year! With incredible breakout sessions to a keynote and panel of top retail speakers like the VP of Ads Engineering at...
View ArticlePower to the SQL People: Introducing Python UDFs in Databricks SQL
We were thrilled to announce the preview for Python User-Defined Functions (UDFs) in Databricks SQL (DBSQL) at last month’s Data and AI Summit. This blog post gives an overview of the new capability...
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