1. Use basic statistics (standard deviation, average and other measures like z score derived from std deviation and average) — This can be done in Imply pivot and is covered in Part 2 of this post.
  2. Use a forecasting model and detect anomalies based on how much a specific metric deviates from forecast — This can be done using a tool like Sherlock with druid and is covered in part 3 of this post.
  3. Use machine learning (clustering and classification especially) — This is covered in my…

  1. How many transactions completed payment?
  2. How many transactions which were initiated on a mobile device were cancelled?
  3. How many transactions paid by card completed payment?
  4. How many transactions that were created in the last month completed within the month?


Vijay Narayanan

Currently working as lead solution engineer at Imply. Been in the data space for about 20 years at Cloudera, Informatica and other companies

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