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the order of the rows on your Netflix home page, issuing content licenses when you click play, finding the Open Connect cache closest to you with the content you requested, and many more). Can we leverage this lineage solution to help forecast SLA misses and address Data Lifecycle Management questions (job cost, table cost, and retention)?
LinkedIn introduced Couchbase as a centralized caching tier for scaling member profile reads to handle increasing traffic that has outgrown their existing database cluster. The new solution achieved over 99% hit rate, helped reduce tail latencies by more than 60% and costs by 10% annually. By Rafal Gancarz
A common theme across all these trends is to remove the complexity by simplifying data management as a whole. In 2018, we anticipate that ETL will either lose relevance or the ETL process will disintegrate and be consumed by new dataarchitectures. Unified data management architecture.
A few questions to ask yourself when considering the information architecture of your appinclude: Do you have different user groups trying to accomplish different things? Batch processing data may provide a similar impact and take significantly less time. Additionally, we set up a nightly batch job to pre-cache results.
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