What Comes Under Big Data?

Big data typically refers to large volumes of structured and unstructured data that can be mined and analyzed to reveal patterns, trends, and insights that can inform decision-making. For details, You can even check in-depth knowledge on Hadoop Ecosystem toolsand its concepts such as HDFS, YARN, MapReduce with the Big data Certification.

It encompasses a wide range of data types, sources, and formats, including:

1. Structured data: This is data that is organized and easily searchable, such as data in spreadsheets and databases.

2. Unstructured data: This refers to data that does not have a clear structure or format, such as social media posts, emails, and videos.

3. Semi-structured data: This is data that has some structure but is not fully organized, such as XML files and JSON documents.

4. Sensor data: This is data that is generated by devices and sensors, such as GPS data, weather data, and healthcare monitoring data.

5. Machine data: This is data generated by machines, such as log files and transaction data.

6. Social media data: This includes data from social media platforms, such as Twitter, Facebook, and Instagram.

7. Text data: This is data in the form of text, such as emails, customer feedback, and survey responses.

8. Audio and video data: This includes data in the form of audio and video recordings, such as podcasts, webinars, and training sessions.

9. Internet of Things (IoT) data: This is data generated by connected devices, such as smart home devices, wearables, and industrial sensors.

Analyzing and making sense of big data can involve using advanced analytics tools and techniques, such as machine learning algorithms, data mining, and predictive analytics.