Performance Standards:
Employees at all levels are expected to effectively work together to meet the needs of the community and the organization through work behaviors demonstrating the Department’s values. Employees are also expected to lead by example and demonstrate the highest level of ethics; carry out a continuous effort to improve operations, work processes; and, work cooperatively and collaboratively to support a data-driven and customer-focused service.
Job Performance Requirements (NFPA 1022 Standards):
1. General. The fire and emergency services analyst shall be proficient in the use of information systems and data analysis methods and techniques to query, analyze, and present data to assist the fire and emergency services organization in reporting and developing periodic reports, strategic plans, and standards of cover documents.
1.1. For qualification as a data analyst, the candidate shall meet the job performance requirements (JPRs) defined in Sections 2 through 8.
1.2. General Prerequisite Knowledge. Familiarity with analyzing information; specifically identifying, processing, querying, and visualizing data to assist the fire and emergency services organization in providing information required by external and internal agencies and for analytical and decision-making purposes; a pursuit of data integrity and sustainable data management for reliable, efficient, and long-term use.
1.3. General Prerequisite Skills. The ability to demonstrate formal training or workplace experience using datasets and data sources, as well as understanding their respective properties; investigate, organize, and present data as a comprehensible analysis; and produce documentation regarding data considerations and analytical processes.
2. Identify, Access, and Extract Data. This duty involves verifying data needs, parameters, and analytical limitations while establishing connections to one or more data sources and extracting the dataset.
2.1. Verify data needs, parameters, and analytical limitations, given a request for information, so that the scope, data requirements, and estimated level of effort required to perform the analysis are defined.
(A) Requisite Knowledge. Current data resources, the organization’s data sharing policies, and analytical processes.
(B) Requisite Skills. The ability to communicate clarifying questions.
2.2. Access one or more data sources, given a set of data parameters and appropriate access to data, so that the information is able to be assessed.
(A) Requisite Knowledge. Content of data sources, who to ask for any additional data source access, records management systems (RMS) and computer-aided dispatch systems (CAD) software, and internal and external data sources.
(B) Requisite Skills. The ability to request data from restricted data sources and review data from one or more sources using the data management software.
2.3. Extract data, given an established connection to data sources, so that a dataset is available for use independent of the system of origin.
(A) Requisite Knowledge. Database structure/schema, data relationship structures and types, conversion options, and RMS and CAD software.
(B) Requisite Skills. The ability to generate formatted data in a readable, accessible format and prepare data for validation.
3. Validate Data Extraction Process and Output. This duty involves inspecting and evaluating datasets to ensure any issues that might affect the validity of the analysis are identified and documented.
3.1. Inspect the output dataset, given a dataset and data systems, so that potential issues are identified and documented.
(A) Requisite Knowledge. Common data output issues.
(B) Requisite Skills. The ability to identify errors in data and issues in formatting.
3.2. Evaluate data quality issues, given appropriate data review tools and a dataset with known issues, so that scope of the issues is determined and corrective actions are documented.
(A) Requisite Knowledge. Organizational standards and typical data results.
(B) Requisite Skills. The ability to locate data quality issues in a dataset.
4. Resolve/Repair. This duty involves addressing data quality errors by transforming data, communicating data limitations and potential solutions, and verifying repairs.
4.1. Perform data wrangling, given a need to resolve anomalous and erroneous data, so that data analysis is valid and reliable.
(A) Requisite Knowledge. The organization’s guidelines, policies, or procedures for modifying data; dataset requirements and impact upon modification; and data wrangling techniques.
(B) Requisite Skills. The ability to access and operate data platforms and applications and transform data.
4.2. Communicate any limitations in the dataset, given anomalous and erroneous data, so that the causes and remedies are annotated and can be addressed by the owners of the data.
(A) Requisite Knowledge. Business, procedural, or operational processes that impact data quality; and understanding successful mitigation strategies.
(B) Requisite Skills. The ability to access and operate data platforms and applications, and to communicate the pertinent attributes of the dataset that impact the accuracy of the final analysis.
4.3. Verify repairs to a dataset were successful, given a repaired database, so that inconsistencies in the data are addressed.
(A) Requisite Knowledge. Dataset’s impact upon modification, and common dataset anomalies and errors.
(B) Requisite Skills. The ability to search for data in the database and transform data.
5. Organize the Data. This duty involves standardizing the data type and format and structuring the data for analysis.
5.1. Standardize data type and format, given a dataset and agency data conventions, so that data are put into a compliant type and format per agency requirements.
(A) Requisite Knowledge. Data typing and formatting, methods of storing data, and data elements.
(B) Requisite Skills. The ability to format and type data in platforms and applications used by the organization.
5.2. Structure data for analysis, given data from one or more sources, so that data from multiple sources can be used within the available analysis program.
(A) Requisite Knowledge. Database design and management, and relating information across different database objects and datasets.
(B) Requisite Skills. The ability to compile a dataset into a usable format for analysis.
6. Analyze Data. This duty involves analyzing nonspatial data through the determination of data analysis methods and techniques, performing the data analysis, and ensuring the analysis meets the requirements of the documented request according to the following JPRs.
6.1. Determine the analysis methods and techniques, given the available data and type of request, so that a systematic and objective approach is used and supports the project goals.
(A) Requisite Knowledge. Data analysis concepts and standards, and an understanding of commercially available or agency specific data analysis platforms/tools.
(B) Requisite Skills. The ability to apply appropriate analytical techniques or methods, select the most efficient analytical tool, and identify any additional resources to meet the project objectives.
6.2. Perform data analysis, given a request, access to applicable datasets, and analysis tools, so that the result(s) and process(es) satisfy the request.
(A) Requisite Knowledge. General statistical analysis methods.
(B) Requisite Skills. The ability to use an analytical tool and apply analytical techniques.
6.3. Perform quality assurance (QA), given data analysis results, so that the results meet the objectives of the original request.
(A) Requisite Knowledge. Relevant data elements, data domain application, and AHJ QA procedures.
(B) Requisite Skills. The ability to use QA techniques to identify areas of quality concern and recommend a course of corrective action.
7. Present Analysis. This duty involves developing the best method(s) to share an analysis and considering who will be consuming the information, in what environment, and through what type(s) of available media.
7.1. Design a method to communicate information, given presentation requirements and data artifacts from an analysis, so that the information is accessible and specific to the targeted audience.
(A) Requisite Knowledge. Characteristics of the audience, presentation opportunities and limitations, and presentation design and methodology.
(B) Requisite Skills. The ability to conduct research and apply data visualization techniques for different print and electronic media.
7.2. Communicate the results, given the results of an analysis, presentation tools, and an audience, so that the original request is addressed, any additional relevant information is outlined, and questions are addressed.
(A) Requisite Knowledge. Presentation and visualization tools.
(B) Requisite Skills. The ability to communicate orally, visually, and in writing the results of an analysis and related questions.
8. Documentation. This duty involves providing technical notes and process steps taken during the entire data staging and analysis process and creating a document that allows for reproduction and transparency of the results.
8.1. Produce technical notes, given details about data access, repairs, and data reliability, so that data considerations are documented for future reference, repeatability, and continued analysis.
(A) Requisite Knowledge. The organization’s documentation guidelines; the data access, extraction, and validation process; and the original scope and purpose of the data request.
(B) Requisite Skills. The ability to communicate technical notes in writing.
8.2. Compile analysis instructions, given the original request and technical notes, so that the organization has access to a transparent and reproducible record of the entire analysis process.
(A) Requisite Knowledge. The organization’s documentation guidelines and the data analysis process for the current project.
(B) Requisite Skills. The ability to communicate analysis instructions in writing, including organizing information chronologically.
The work is typically performed in an office, library, or computer.
