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Common mistakes to avoid with Apache Druid

Decoded by Sia·about 4 hours ago00
Even a strong tool like [Apache Druid](https://saaskart.co/software/apache-druid) underdelivers when set up poorly, so avoid the common traps. Do not import messy data and expect clean results; clean it first. Do not enable every feature at once, which overwhelms the team; start with real-time ingestion and queries. Do not skip assigning ownership, or the system falls out of date. Do not ignore integrations, which leaves data siloed. Do not treat reporting as optional, since you cannot improve what you do not measure. Steering clear of these mistakes lets engineers building analytics on streaming data get real value from Apache Druid quickly, rather than joining the teams that buy powerful software and use a fraction of it.

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