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[column 12 layout="standard"]
Data Analytics
The science of analyzing raw data in order to make conclusions about that information.[/column]
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[column 12]
Problem Analysis and Planning
Prioritizes requests, articulates the problem and assesses potential solutions using data and advanced analytics.[/column]
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[column 12]
Business Problem Analysis
The ability to understand a business problem and determine whether the problem is amenable to an analytics solution.
Obtains or receives problem statement.
Defines expected business benefits.[/column]
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[column 12]
Design Analysis
Translates business requirements into a technical analytic plan that includes things like scoping, ordering, and justification of milestones
Reformulates problem statement as an analytics problem.
Proposes a potential analytics solution.
Defines key metrics of success/Determine the best way to evaluate the results.[/column]
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[column 12]
Data Analysis
The ability to work effectively with data to identify and create solutions.[/column]
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[column 12]
Data Identification
Identifies what data is required to answer a question.
Prioritizes data needs and sources.
Creates data extraction and transformation methods.
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[column 12]
Data ExplorationAcquires and explores the data to characterize and prepare data for analytics.
Acquires, cleans and merges data.
Identifies relationships in the data.
Generates descriptive statistics.
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[column 12]
Modeling
Develops, trains and tests models.
Identifies model structures.
Runs and evaluates the models.
Calibrates models and data.
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[column 12]
Quantitative and Qualitative AnalysisPerforms analysis, implements approaches to help solve the business problem.
Identifies available problem-solving approaches (methods).
Builds or applies appropriate algorithms (includes descriptive and inferential statistics, and advanced analytics).
Selects software tools.Tests and selects approaches (methods).
Performs statistical analysis.Hypothesis testing.
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[column 12]
Deployment
The ability to incorporate into the business to help solve the business problem.
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[column 12]
Documents Findings
Performs data visualization and technical communication.
Documents and reports findings (e.g., insights, results, business performance).
Performs business validation of the model.
Creates report with findings.
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[column 12]
Communicates Findings and Recommendations
Packages and describes, in business terms, what the findings mean.
Navigates the business’s organizational structure.
Makes technical topics accessible to non-technical people.
Considers how the results can be acted upon and operationalized.
Calculates ROI.
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[column 12]
Operationalization Performs data visualization and technical communication.
Documents and reports findings (e.g., insights, results, business performance).
Performs business validation of the model.
Creates report with findings.
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[column 12]
Data Product Life-Cycle Management
The ability to manage the model life cycle to evaluate business benefit of the model over time.
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[column 12]
Data Governance Manages the availability, usability, integrity and security of data used in an enterprise.
Establishes a data governance team and assigns roles and responsibilities.
Identifies HIPPA and other confidential information.
Creates and implements a compliance process.
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[column 12]
Project Execution and Maintenance
Manages knowledge, change, quality processes, evaluation and personnel.
Incorporates into the business’s workflow and other technical systems.
Recalibrates and maintain the model.
Ensures product maintenance and durability.
Performs business impact assessment - evaluates the business benefit over time.
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