Salesforce Certified CRM Analytics and Einstein Discovery Consultant (Analytics-Con-201) Exam Topics and Questions
These Salesforce Certified CRM Analytics and Einstein Discovery Consultant (Analytics-Con-201) exam topics are organized according to official exam domains to help candidates quickly verify coverage and focus on assessment rather than theory. Each domain is paired with topic-wise Salesforce Certified CRM Analytics and Einstein Discovery Consultant (Analytics-Con-201) sample questions that reflect how objectives are tested in the actual exam. This structure enables efficient review, targeted self-assessment, and rapid identification of weak areas when preparing for the Salesforce Certified CRM Analytics and Einstein Discovery Consultant certification exam.
Let's Practice Free Salesforce Certified CRM Analytics and Einstein Discovery Consultant (Analytics-Con-201) Questions Aligned with Official Exam Topics
Exam Contains: 6 Topics
Topic Content
Data Layer encompasses the fundamental processes of extracting and loading data from various sources using Data Manager to establish datasets within CRM Analytics applications. This includes implementing and managing data refresh strategies for synchronization and dataflows or recipes while adhering to system limits and operational constraints. Professionals must perform essential data transformations within dataflows and recipes to align with specific business requirements and analytical needs. Extended metadata management is critical, involving the customization of dataset labels, values, and color schemes...
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Sample Questions for Topic 1 : Data Layer
Q1
You need to customize dataset metadata in CRM Analytics to improve usability for business analysts. Which extended metadata management activities should you perform?
Topic Content
Security encompasses the implementation of comprehensive access controls and data protection measures across governance and CRM Analytics platforms. This includes configuring user, group, and profile-based security settings to meet organizational governance requirements and protect sensitive analytics assets. Row-level security must be implemented through dataset security configurations, utilizing sharing inheritance mechanisms and security predicates to ensure users only access data appropriate to their role and responsibilities. Application sharing policies should be established and enforced based on specific user and group requirements,...
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Topic Content
Admin/Configuration encompasses enabling CRM Analytics with appropriate permission sets and licenses based on business and access requirements. Candidates must demonstrate the ability to design solutions using CRM Analytics that effectively manage data sync, dataflows, and recipes within specified limits. Knowledge of CRM Analytics API capabilities and their practical applications in various scenarios is essential. Additionally, professionals should understand how to migrate CRM Analytics configurations and deployments across different environments to support organizational growth and change management. This includes managing licenses,...
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Topic Content
Analytics Dashboard Design encompasses the ability to analyze business requirements and determine dashboard scope while validating and prioritizing design specifications to ensure alignment with organizational goals. This involves creating effective dashboards that satisfy business needs by adhering to CRM Analytics best practices and applying sound UX design principles to enhance user experience and data accessibility. Professionals must demonstrate competency in selecting and configuring standard CRM Analytics templated applications that appropriately address specific business requirements without unnecessary customization. The focus is...
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Topic Content
Analytics Dashboard Implementation encompasses configuring dashboards aligned with business requirements using appropriate query types and widget-level parameters to ensure accurate data representation. Developers must create dynamic selection and result interactions across various query types to enable seamless data exploration and filtering capabilities. Advanced analytical techniques including windowing functions and time series analysis within compare tables should be leveraged to provide deeper insights and trend analysis. Dashboards must be designed as actionable tools with full accessibility integration into Lightning pages, allowing...
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Topic Content
Einstein Discovery enables users to build predictive models by evaluating datasets and selecting from three prediction types: numeric, binary, or multi-classification approaches. Professionals analyze model results against business requirements and recommend data enhancements to stakeholders for improved accuracy. The process involves iteratively adjusting data parameters, adding or removing relevant columns and datasets to optimize model performance based on derived insights and outcomes. Users can activate prediction capabilities directly on Lightning record pages throughout Salesforce and CRM Analytics platforms for seamless...
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