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Analytics

Kensu Named Challenger and Fast Mover in GigaOm Radar Report for Data Observability

Kensu announces that it has been named a Challenger and Fast Mover and is projected to be named a Leader within the coming 12 to 18 months in the GigaOm Radar Report for Data Observability. In the report, Kensu falls within the Innovation/Platform Play quadrant, having capabilities to stop data incidents from propagating and resolve them twice as fast.

The Pros and Cons of Point-to-Point Integration

Point-to-point integration is a method of connecting two or more software applications or systems together to exchange data seamlessly. It helps organizations break down data silos and enables the sharing of critical information across different systems. P2P integration eliminates the need for complex middleware or custom code, providing a more efficient and streamlined approach to data integration.

Unified Data Clears the Roadblocks of Your Hybrid Cloud Journey

Cloud computing is proliferating businesses across all industries. According to a recent survey by the Harvard Business Review, 81% of respondents said cloud is very or extremely important to their company’s growth strategy. Overall, nearly two-thirds of senior executives stated their businesses have accelerated their plans to migrate to the cloud.

Unlocking BigQuery: Achieving Speed and Scale with Data Observability and FinOps

See what’s new and look ahead to take advantage of the latest innovation from Unravel The demands of data analytics and AI are rising, making it more difficult to keep data pipelines running as they become more complicated. Customers are turning to modern data stacks such as Google Cloud BigQuery to keep up.

The CEOs of Fivetran & Snowflake discuss Shared Goals in Driving Data Excellence

George Fraser, Co-founder and CEO of Fivetran and Frank Slootman, Chairman and CEO of Snowflake sit down to discuss how the dynamic, award-winning partnership between the two companies helps to eradicate data silos once and for all. The conversation delves into Fivetran's pivotal role in constructing the vital pathways that seamlessly usher data into Snowflake, encompassing sources like Oracle, SQL Server, SAP Hana, Workday, Salesforce, and a myriad of others.

Introducing Versioned State Store in Kafka Streams

Since the introduction of stream processing, there have been three certainties in life: death, taxes, and out-of-order data. As a stream processing library built for Apache Kafka, Kafka Streams processes data in offset order. When out-of-order data is present, offset order differs from timestamp order and care must be taken to ensure that processing results respect timestamp order where appropriate.