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With the year coming to a close, many look back at the headlines that made major waves in technology and big data – from Spark to Hadoop to trends in data science – the list could go on and on. 2016 will be the year of the “logical datawarehouse.”
Versioning also ensures a safer experimentation environment, where data scientists can test new models or hypotheses on historical data snapshots without impacting live data. Note : Cloud Datawarehouses like Snowflake and Big Query already have a default time travel feature. FAQs What is a Data Lakehouse?
By leveraging Google-like smart search to find data assets; using automation and self-learning instead of burdening people with the need to manually update metadata in multiple places; and ensuring that metadata is maintained by the whole data community and is not dependent on a centralized IT team.
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