Start learning 50% faster. Sign in now
Stream processing involves continuously analyzing data as it arrives, which is ideal for real-time applications. It processes data in real-time, as opposed to waiting for a complete dataset, making it highly efficient for scenarios requiring immediate insights, such as fraud detection, social media analytics, and sensor data analysis. Stream processing frameworks include Apache Storm, Flink, and Spark Streaming. Batch Processing: Involves processing data in large chunks rather than continuously. It is not real-time. MapReduce: A programming model used for batch processing large datasets, not real-time processing. Hadoop: A framework that supports batch processing but not real-time stream processing. HDFS: The Hadoop Distributed File System (HDFS) is for storing large data sets, not processing them.
Which of the following statement is not true?
Which of the following methods to measure seasonal variations comparatively utilizes the given data less?
Laspeyre's formula has ___________ bias and Paasche's formula has _________ bias.
At the centre multipurpose socio-economic surveys are mainly conducted by -
From a population containing 30 units, 5 units are drawn by simple random sampling without replacement. The probability same specified unit included in ...
As per the Agricultural Census 2015-16, total number of operational land holdings in Rajasthan was -
Infant mortality rate is the ratio of -
For the given 6 values 15, 24, 18, 33, 42, 54, the three yearly moving averages are -
A given data has mean = 6.5, median = 6.3 and mode = 5.4. It represents -
Supply Curve is a part of -