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Go to:GPUs have continued to rise in interest for organizations due to their unparalleled parallel processing power. Leveraging GPUs in an enterprise analytics initiative allows these organizations to gain a competitive advantage by processing complex data faster and extracting valuable insights against a larger corpus of data that can result in break-through insights. Both Databricks and…
There are useful timestamp functions in SQL, Python, and other languages. But, time series analysis is quite different. Times series data is often never-ending measurements in a points-in-time sequence. The data is almost painful to the human eye but fits well into computers. Time series analysis find correlations, conflicts, trends, or seasonal insights using sophisticated…
Kinetica is a high-speed analytical database for big data. Its integration with ChatGPT allows you to havea sophisticated analytical conversation with your data in English no matter the scale. This post will show you how to set up and use this integration. Step 1: Launch Kinetica Kinetica offers a “free forever” managed version with 10…
Window functions allow us to perform calculations on a subset of rows in a table, rather than the entire table. A window function performs a calculation across a set of rows that are related to the current row, based on a specified window of observations. They are used to calculate running totals, ranks, percentiles and…
Time-series data usually refers to any series of data points that come with a timestamp. You’ll find time-series data created by a wide range of sources including sensors on vehicles, weather stations, package tracking, fitness trackers and so on. Other sources of time-series data include financial market data, website traffic, server logs and more. By studying…