Systems | Development | Analytics | API | Testing

Introducing Confluent Cloud Freight Clusters

We’re excited to introduce Freight clusters—a new type of Confluent Cloud cluster designed for high-throughput, relaxed latency workloads that is up to 90% cheaper than self-managing open source Apache Kafka®. Freight clusters utilize the latest innovations in Confluent Cloud’s cloud-native engine, Kora, to deliver low cost networking by trading off ultra low latency performance.

Improving LLM Accuracy & Performance - MLOps Live #28 with Databricks

Watch session #28 in our MLOps Live Webinar Series featuring Databricks where we discuss improving LLM accuracy & performance. Hear Margaret Amori (Databricks), Vijay Balasubramaniam (Databricks) , and Yaron Haviv (Iguazio) share best practices and pragmatic advice on successfully improving the accuracy and performance of LLMs while mitigating challenges like risks and escalating costs. See real examples including techniques to overcome common challenges using tools such as Databricks Mosaic AI and their new open LLM, DBRX.

Snowflake Data Clean Rooms for Marketing

In less than 5 minutes, Ankur Abhishek, Senior Product Manager at Snowflake, demostrates how Snowflake Data Clean Rooms can be used for audience overlap, audience lookalike, and attribution analysis. As Kamakshi Sivaramakrishnan, Senior Director of Product Management at Snowflake, explains, "This is the full marketing lifecycle brought in its entirety in a Snowflake clean room, run securely with multiple parties collaborating with each other. This is demystifying clean rooms.".

Data Integrity vs. Data Quality: Here's How They Are Different

Data integrity refers to protecting data from anything that can harm or corrupt it, whereas data quality checks if the data is helpful for its intended purpose. Data quality is a subset of data integrity. One can have accurate, consistent, and error-free data, but it is only helpful once we have the supporting information for this data. Data integrity and quality are sometimes used interchangeably in data management, but they have different implications and distinct roles in enhancing data usability.

What is Data Preprocessing? Definition, Importance, and Steps

Did you know data scientists spend around 60% of their time preprocessing data? Data preprocessing plays a critical role in enhancing the reliability and accuracy of analytics. This blog will discuss why data preprocessing is essential for making data suitable for comprehensive analysis.

Logi Symphony Has You Prepared for New Cookie Restrictions

Embedding analytics into your application? New browser restrictions are on the way for Google Chrome that can block some third-party content that uses cookies from being accessible to users by default, in addition to restrictions in Safari and Firefox you may have already seen.

Exposed: How Secure Are Your Embedded Analytics Really?

The ever-growing threat landscape of hackers, cyberattacks, and data breaches makes data security a top priority, especially when integrating analytics capabilities directly into customer-facing applications. To make informed decisions, it’s crucial to understand how embedded analytics platforms function from a security standpoint.