Oracle 1z0-1041-23 Exam With Confidence Using Practice Dumps

Usage tracking is a feature of Oracle Analytics Cloud that enables you to collect and analyze information about how users interact with your analytics content and resources. Usage tracking is available only for Enterprise Edition, as this is a more advanced and scalable edition than Professional Edition. To enable usage tracking, you need to create a new connection pool in the Oracle Analytics Developer Client tool, which is a desktop application that allows you to create and manage data models for Oracle Analytics Cloud. You also need to configure the Usage Tracking Connection Pool setting in the console, which is a web-based interface that allows you to administer Oracle Analytics Cloud instances and services. After making any change to this setting, you need to restart your Oracle Analytics Cloud instance for the change to take effect. References: [Oracle Help Center], [Oracle Help Center], [Oracle Help Center]

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. References: [Oracle Help Center], [Oracle Help Center], [Oracle Help Center]

Data wrangling is a process of transforming and enriching data to make it more suitable for analysis or visualization. Some statements that are true about data wrangling are:

• In data wrangling, transformations available are dependent on the data type. For example, you can apply different transformations to numeric, text, date, or location data types.
• It is used to curate data sets that can be used for complex visualizations. For example, you can use data wrangling to create calculated columns, merge or split columns, group or aggregate values, filter or sort rows, or join or union data sets. References: [Oracle Analytics Cloud - Data Visualization User’s Guide], [Oracle Analytics Cloud - Data Visualization User’s Guide]