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How to make data lakes reliable

byadmin
February 21, 2020
in Articles, Artificial Intelligence, Trends
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Data professionals across industries recognize they must effectively harness data for their businesses to innovate and gain competitive advantage. High quality, reliable data forms the backbone for all successful data endeavors, from reporting and analytics to machine learning.

Delta Lake is an open-source storage layer that solves many concerns around data lakes and makes data lakes reliable. It provides:

  • ACID transactions
  • Scalable metadata handling
  • Unified streaming and batch data processing
  • Delta Lake runs on top of your existing data lake and is fully compatible with Apache Spark™ APIs.

In this guide, we will walk you through the application of Delta Lake to address four common industry use cases with approaches and reusable code samples. These can be repurposed to solve your own data challenges and empower downstream users with reliable data.

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Learn how you can build data pipelines for:

  • Streaming financial stock data analysis that delivers transactional consistency of legacy and streaming data concurrently
  • Genomic data analytics used for analyzing population-scale genomic data
  • Real-time display advertising attribution for delivering information on advertising spend effectiveness
  • Mobile gaming data event processing to enable fast metric calculations and responsive scaling
How to make data lakes reliable
Download this free guide here.
Tags: data lakeData PipelineMetadatasurveillanceUSA

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Speechify adds voice typing and assistant to Chrome

Copilot exits WhatsApp on January 15 citing policy shift

Rockstar co-founder critiques EA and Microsoft’s AI expectations

Gemini’s upcoming Projects feature mirrors ChatGPT workspaces

OpenAI moves ChatGPT Voice into main chat thread

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