tl;dr:In a data-centric era, efficiently collecting and querying data from diverse sources is paramount. Zoe Steinkamp emphasizes the importance of best practices in data collection, such as optimizing ingestion pipelines and advanced querying. With varied data streams like IoT and cloud computing, single-database storage is outdated. Instead, strategies like effective data modeling and understanding data sources are vital. Tools like InfluxDB, a time series database, and Pandas, a Python library, facilitate data management and analysis. Leveraging multiple data sources optimizes cost, efficiency, and user experience.
tl;dr:Best practices for building IoT analytics include storing data in a time series database, using efficient ingestion methods, cleaning data before storage, downsampling for easier analysis, monitoring data in real time, and storing historical data in cold storage or a data lake for analysis. Choosing the right tools from the start will save time and improve efficiency.