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What is Data Analytics, and how is it used to make better business decisions? Explain its key techniques and applications with examples.
What are the main differences between batch processing and real-time processing in data analytics?
How do you perform feature engineering in time-series data?
What is the significance of A/B testing in optimizing data-driven decisions?
What is the role of Natural Language Processing (NLP) in data analytics?
How does the use of distributed computing frameworks like Apache Spark improve data analytics?
Explain the concept of Big Data and its challenges in the context of data analytics.
What are the different types of machine learning models used for predictive analytics?
Explain how data integrity is maintained in a multi-source data environment.
What is an anomaly detection system, and how would you implement it in Python?
