Gartner predicts that global cloud revenue will be up by $66 billion this year, and by 2025, more than 95% of new digital workloads will be deployed on cloud-native platforms.
As companies ingest more and more data, it becomes more challenging to make it useful due to rapid increases in data volume, velocity, and variety. Event sourcing and stateful stream processing are functions databases and data warehouses weren’t designed for.
Data pipelines are essential to unleashing the potential of data and can successfully pull from multiple sources. However, the process of setting up these pipelines can be time and labor-consuming with a high probability of future failures, unless continuously looked over and improved by dedicated data scientists.
Our friend, Ori Rafael, CEO of Upsolver and advocate for engineers everywhere, released his new book “Unlock Complex and Streaming Data with Declarative Data Pipelines.” Ori discusses why declarative pipelines are necessary for data-driven businesses and how they help with engineering productivity, and the ability for businesses to unlock more potential from their raw data.
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