IoT data is becoming increasingly prevalent, with an estimated 30.9 billion connected devices worldwide by 2025, generating vast amounts of time series data that require efficient storage and management to maintain bottom-line performance. Selecting the right tools for IoT data analysis from the outset can significantly ease data processing and reduce costs. Time series databases like InfluxDB are well-suited for this type of data due to their ability to query based on time, making it easier to analyze and visualize large datasets. High-volume ingestion tools such as Telegraf help manage the constant influx of data, while cleaning and downsampling can optimize storage and improve performance. Real-time monitoring is crucial for quick decision-making, and historical aggregation and cold storage are essential for long-term data analysis and preservation. By choosing the right tools and following best practices, organizations can efficiently process IoT data and make informed decisions.