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influxdata

The "Now" Problem: Why BESS Operations Demand Last Value Caching

Feb 26, 2026 By Suyash Joshi In InfluxData
Battery Energy Storage Systems (BESS) represent one of the most unforgiving environments for real-time data. Unlike a passive asset, a battery is a complex electrochemical system where safety and revenue are determined by split-second decisions. In this context, “average” latency can become a serious problem. Performance depends entirely on one key question.
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InfluxDB 3 Core vs. Enterprise

Feb 13, 2026 By InfluxData In InfluxData
In this video, Senior Developer Advocate Cole Bowden walks you through the key similarities and differences that exist in InfluxDB 3 Core and InfluxDB 3 Enterprise. As an open source offering, Core thrives at data collection on the edge and providing real-time insights into fresh data, while Enterprise includes support, compaction for performant historical analysis over wide windows, better scaling and security for enterprise-scale operations.
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influxdata

How to Use Pandas Time Index: A Tutorial with Examples

Feb 5, 2026 By Company In InfluxData
Time series data is everywhere in modern analytics, from stock prices and sensor readings to web traffic and financial transactions. When working with temporal data in Python, pandas provides powerful tools for handling time-based indexing through its DatetimeIndex functionality. This tutorial will guide you through creating, manipulating, and extracting insights from pandas time indexes with practical examples.
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influxdata

Exponential Smoothing: A Guide to Getting Started

Feb 3, 2026 By Community In InfluxData
Exponential smoothing is a time series forecasting method that uses an exponentially weighted average of past observations to predict future values. In other words, it assigns greater weight to recent observations than to older ones, allowing the forecast to adapt to changing data trends. In this post, we’ll look at the basics of exponential smoothing, including how it works, its types, and how to implement it in Python.
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