Analytics

Fivetran announces upcoming integration with Polaris catalog.

Imagine a world where ALL your data works for you. We’ve already seen remarkable things happen with structured data at Qlik. Our associative engine was crafted to handle structured data in an exceptional way. Calculating, processing, and associating tabular data with precision. But here’s the catch: 80% of the world’s data is unstructured, and Forrester predicts this amount will double this year.

Keboola offers a robust virtual branching environment, enabling users to seamlessly create a shadow copy of their entire Keboola Project. This allows for development and testing of changes without affecting the production environment. These development branches contain a copy of the underlying project data, ensuring that when a pipeline is executed in the development branch, the production data remains unaffected.

In today's data-driven world, Power Query has become an indispensable tool for professionals dealing with data analysis and manipulation. However, it's crucial to understand the limitations of Power Query to maximize its potential and complement it with more advanced tools when necessary.

Cloudera’s data-in-motion architecture is a comprehensive set of scalable, modular, re-composable capabilities that help organizations deliver smart automation and real-time data products with maximum efficiency while remaining agile to meet changing business needs. In this blog, we will examine the “why” behind streaming data and review some high-level guidelines for how organizations should build their data-in-motion architecture of the future.

Modern data platforms enable enterprises to extract valuable business insights from data, sourced from various origins. Data engineers, data scientists, and other data practitioners utilize both data streaming and batch processing frameworks as a means to provide these insights. While batch processes work on historical data, stream processing extracts insights in real time, enabling businesses to react faster with respect to changing events.

We are proud to announce the release of Apache Kafka 3.8.0. This release contains many new features and improvements. This blog post will highlight some of the more prominent features. For a full list of changes, be sure to check the release notes. See the Upgrading to 3.8.0 from any version 0.8.x through 3.7.x section in the documentation for the list of notable changes and detailed upgrade steps. In a previous release, 3.6, Tiered Storage was released as early access feature.

I’m happy to share that Snowflake has signed the Cybersecurity and Infrastructure Security Agency (CISA) Secure By Design Pledge as we champion the advancement of industry standards for security in technology design. The CISA pledge to foster tech-ecosystem security deeply aligns with Snowflake’s own product design ethos, where security is built in from the start.

Ensuring data integrity is crucial for accurate decision-making and regulatory compliance. Poor data quality costs businesses an average of $15 million annually. This highlights the need for robust analytics testing. This article explores the importance of analytics testing. It discusses key use cases and common challenges. Strategies to improve analytics testing processes will be provided. These will help maintain data integrity without expanding the in-house QA team.