- Overview of Actimize framework and its components (e.g., ERCM, RCM, SAM, CDD, WLF)
- Understanding how these components work together for anti-money laundering and fraud detection
- Developing skills in Java, SQL, PL/SQL, Python, R, or other relevant languages
- Using programming languages for Actimize development and integration
- Extracting, transforming, and loading data into Actimize using ETL processes, platforms, or APIs
- Mapping and standardizing data across different sources, applying necessary transformations or conversions
- Working with Actimize tools and languages (e.g., RCM Designer, RCM Java Plugins, Actimize Web Services)
- Designing, developing, testing, and deploying Actimize solutions
- Applying data cleansing and validation techniques to ensure data quality and accuracy
- Implementing data validation and business rules for compliance and reliable data integration
- Using data governance frameworks and practices to monitor and manage the data integration process
- Defining data standards, naming conventions, and data dictionary for consistency and clarity
- Employing data profiling techniques and tools to gain insights into data quality and patterns
- Monitoring data flows, detecting anomalies, and taking proactive measures to ensure data integrity
- Collaborating with stakeholders, data providers, and IT teams to address challenges effectively
- Maintaining clear documentation of data sources, integration processes, mappings, and transformations
- Designing the data integration architecture with scalability and flexibility in mind
- Considering future data sources or changes and designing the integration process accordingly
- Overview of Actimize certification options
- Preparation strategies for Actimize or related technology certifications
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