What are streaming analytics.

Streaming analytics refers to the process of analyzing and extracting insights from real-time data streams. It involves continuously processing and analyzing data as it is generated, allowing organizations to make immediate and informed decisions based on the insights gained.

Here are the steps to understand streaming analytics:

1. Data Collection: The first step is to collect data from various sources, such as sensors, social media feeds, or IoT devices. This data is typically in the form of continuous streams, rather than static datasets.

2. Data Ingestion: Once the data is collected, it needs to be ingested into a streaming analytics platform. This involves transferring the data from its source to the analytics system, where it can be processed and analyzed.

3. Data Processing: In this step, the streaming analytics platform processes the incoming data in real-time. It applies various techniques, such as filtering, aggregation, and transformation, to extract meaningful information from the data streams.

4. Real-time Analysis: After processing the data, the streaming analytics platform performs real-time analysis to uncover patterns, trends, and anomalies. This analysis can involve statistical algorithms, machine learning models, or custom business rules.