A look at best practices, no-code and low-code platforms you can use, common visualization types, criteria for good data visualization and more. Organizations regularly generate an overabundance of data that is essential for decision-making. Data visualizations play an important role in helping people understand complex data and observe patterns and trends over a period of time.
Recently InfluxData announced SQL support in InfluxDB Cloud, powered by IOx. Users can now use familiar SQL queries to explore and analyze their time series data. The SQL support was introduced along with the usage of Apache Arrow. Apache Arrow is an open source project used as the foundation of InfluxDB’s SQL support. Arrow provides the data representation, storage format, query processing, and network transport layers. Apache Flight SQL provides a method for interacting with Arrow via SQL.
Simplified analysis. Enhanced visualizations, alerting capabilities, advanced data forwarding, and more. Great news! We have published a new update with many exciting new features and optimizations.
Users have been generating increasing amounts of data in the past few years, partly due to rapid digitalization since the pandemic. As a result, increasing numbers of analytics applications are capitalizing on these data assets. However, building scalable systems is no trivial task and incidents are inevitable. Complex systems generate data in the form of logs, traces, metrics, and more, which organizations often find themselves sprinting through. Such logs are a powerhouse of valuable information.