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Live vs Extract In Data Analytics

Live Vs Extract seems like you're referring to two different approaches in data analytics: live analytics and extract analytics. - Data Analytics Training

Let me clarify these concepts for you:

1. Live Analytics:

 - Also known as real-time analytics, this approach involves analyzing data as it is generated or collected in real time.

 - Live analytics is essential for scenarios where immediate insights are needed to make decisions or take actions.

 - It often involves processing and analyzing data streams as they are generated, allowing for quick responses to changing conditions or events.

 - Examples include monitoring social media feeds for real-time sentiment analysis, tracking website traffic in real time, or analyzing sensor data from IoT devices as it is generated. - Data Analytics Course in Hyderabad

2. Extract Analytics:

 - This approach involves extracting data from a source and then analyzing it. The extraction process typically occurs periodically, rather than in real time.

 - Extract analytics is commonly used for historical analysis, reporting, and business intelligence where real-time processing is not critical.

 - Data is usually extracted from various sources, transformed into a suitable format, and loaded into a data warehouse or analytical database for analysis.

 - Examples include running monthly sales reports, analyzing quarterly financial data, or performing yearly trend analysis on customer behavior. - Data Analytics Course

Both approaches have their own advantages and use cases:

1. Live Analytics Pros:

 - Immediate insights and responses to real-time events.

 - Well-suited for applications where timely decision-making is crucial.

2. Live Analytics Cons:

 - May require more resources for real-time processing.

 - Complexity in handling large volumes of streaming data. - Data Analytics Training in Hyderabad

3. Extract Analytics Pros:

 - Suitable for historical analysis and long-term trends.

 - Less resource-intensive since data processing doesn't need to happen in real time.

4. Extract Analytics Cons:

 - May not be suitable for scenarios where real-time insights are critical.

 - The delay between data collection and analysis.

In many cases, a combination of both live and extract analytics is used to cater to different business needs. - Data Analytics Online Training Institute

 

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