Anomaly Detection is the algorithm that would be the best fit for creating a model that identifies customers with multiple potential fraudulent transactions in Oracle Analytics Cloud. Anomaly Detection is a machine learning technique that allows you to detect outliers or anomalies in your data that deviate from the normal or expected behavior. You can use Anomaly Detection to create a model that scores each customer based on their transaction history and flags those who have unusually high or low values as potential fraudsters. The other algorithms, such as Support Vector Machine, Decision Tree, and Logistic Regression, are not the best fit for this purpose. Support Vector Machine is a machine learning technique that allows you to classify data into two or more categories based on a linear or nonlinear boundary. Decision Tree is a machine learning technique that allows you to create rules or conditions for splitting data into branches or nodes based on certain criteria. Logistic Regression is a machine learning technique that allows you to predict the probability of an event occurring based on one or more variables. Reference: [Oracle Help Center], [Oracle Help Center], [Oracle Help Center]

To investigate why a user cannot get answers when using Day by Day with Oracle Analytics Cloud Professional Edition, you can do the following steps:
Verify that the user has been assigned the BI Content Author and Bl Data Load Author roles. These roles are required to access and use Day by Day features, such as asking questions using natural language or voice, or getting personalized insights based on usage patterns.
Inspect the data set and check the access control. You need to make sure that the user has sufficient permissions to view and query the data set that they asked a question about.
Inspect the data set and make sure that it is certified, indexed for searching, and English language is selected. These are some of the criteria that make a data set eligible for Day by Day queries. You can use the Manage menu in Data Sets to check and modify these settings. Reference: [Oracle Day By Day User's Guide], [Oracle Day By Day User's Guide], [Oracle Day By Day User's Guide]

Using the explain feature and adding the relevant visualizations to a canvas are two methods that will help you build visualizations that will help your client understand their data better in Oracle Analytics Cloud. The explain feature is a feature that allows you to automatically generate insights and recommendations for your data based on various factors, such as Basic Facts, Key Drivers, Segments, and Anomalies. Basic Facts are summary statistics that describe your data, such as count, sum, average, minimum, and maximum. Key Drivers are variables that have a strong influence or correlation with your data, such as product category, customer segment, or region. Segments are groups of data points that have similar characteristics or patterns, such as high-value customers, low-performing products, or seasonal trends. Anomalies are data points that deviate significantly from the normal or expected behavior of your data, such as outliers, spikes, or drops. You can use the explain feature to quickly identify these factors and create visualizations that highlight them. You can also add the relevant visualizations to a canvas, which is a workspace where you can arrange and display your visualizations in a meaningful way. You can choose from various types of visualizations, such as charts, graphs, maps, tables, and more. You can also customize your visualizations by applying filters, calculations, aggregations, and other functions to your data. You can use these methods to create visualizations that will help your client understand their data better and discover new insights. Reference: [Oracle Help Center], [Oracle Help Center], [Oracle Help Center]

Data Preparation in OAC uses obfuscation to protect sensitive information such as SSN, credit card number, and customer number. Obfuscation is a technique that replaces the original values with random or masked values that preserve the format and length of the original values. This way, you can hide or anonymize sensitive information while maintaining its usability for analysis or visualization. Reference: Oracle Analytics Cloud - Data Visualization User's Guide, Oracle Analytics Cloud - Data Visualization User's Guide

To display the report in the click event drilled down in the same window, you can set the drill in place option in section properties. This option allows you to replace the original report with the drilled report in the same section of the dashboard page. You can also use breadcrumbs to navigate back to the original report. Reference: Oracle Analytics Cloud - Data Visualization User's Guide, Oracle Analytics Cloud - Data Visualization User's Guide