Anomaly Detection is well-suited for detecting unusual patterns, making it effective in identifying fraudulent activities in a telecommunications setting. Clustering, Classification, and Regression have different purposes and may not be as effective for fraud detection.

Apache Spark is a common tool used for ETL processes in data warehousing. It provides a fast and general-purpose cluster computing system for big data processing and analytics.

Conversion Rate is a critical metric to prioritize when aiming to improve online customer engagement. It measures the percentage of users who take a desired action, such as making a purchase or signing up. A higher conversion rate indicates better engagement and effectiveness of the online platform. Other metrics like CTR, Bounce Rate, and CLV provide valuable insights but may not directly reflect engagement effectiveness.

The primary goal of time series analysis is to identify patterns and trends over time, helping analysts understand the underlying factors influencing the data and make predictions for future events based on historical observations.

Exponential smoothing is a technique used in time series analysis to emphasize longer-term trends or cycles by giving more weight to recent observations. It's valuable for forecasting and trend analysis.

Distributed Hash Tables (DHTs) are commonly used in distributed computing to manage scalable, partitioned, and replicated data. DHTs provide a decentralized way to distribute and locate data across multiple nodes in a network, ensuring efficient access and fault tolerance.

An API key is used as a form of authentication to control access to an API. It serves as a unique identifier for a user or application and helps ensure that only authorized entities can access the API's resources.

Text normalization is essential for handling slangs and abbreviations. It involves steps like converting text to lowercase, removing special characters, and standardizing abbreviations to ensure uniformity in the data.

To merge datasets in dplyr with different key column names, you can use the rename() function to rename the key columns in one or both datasets, ensuring they match. This allows you to then use the standard left_join() or other merge functions.

A global e-commerce platform with high availability and scalability requirements would benefit from a Distributed Database architecture. Distributed databases distribute data across multiple servers or locations, ensuring both availability and scalability for a large user base and global operations.

The P-value is used in hypothesis testing to assess the evidence against a null hypothesis. A small P-value suggests that the null hypothesis is unlikely, leading to the rejection of the null hypothesis in favor of the alternative hypothesis.

Filtering is used in advanced reporting to dynamically narrow down and analyze data based on user-defined parameters. This allows users to focus on specific aspects of the data for a more detailed analysis.