Florida Department of Education
Curriculum Framework 

Program Title:	Business Intelligence Specialist (Data Science Technician)
Career Cluster:	Information Technology

AS	
CIP Number	1530700101	
Program Type	College Credit	
Standard Length	60 credit hours	
CTSO	PBL, BPA 	
SOC Codes (all applicable) 	Assignment pending.	
CTE Program Resources 	http://www.fldoe.org/academics/career-adult-edu/career-tech-edu/program-resources.stml	

Purpose

This program offers a sequence of courses that provides coherent and rigorous content aligned with challenging academic standards and relevant technical knowledge and skills needed to prepare for further education and careers in the Information Technology career cluster; provides technical skill proficiency, and includes competency-based applied learning that contributes to the academic knowledge, higher-order reasoning and problem-solving skills, work attitudes, general employability skills, technical skills, and occupation-specific skills, and knowledge of all aspects of the Information Technology career cluster.

The content includes but is not limited to in-depth instruction on the activities performed data analysis; factors, issues, and constraints relating to the creation of reports; requirements for documenting specifications; identifying data sources and retrieval issues and methodologies; report delivery mechanisms; report modification and maintenance; data governance; quality control tests; data and report integrity; and the use of data science tools.

Additional Information relevant to this Career and Technical Education (CTE) program is provided at the end of this document.

Program Structure

This program is a planned sequence of instruction consisting of 60 credit hours.

Standards

After successfully completing this program, the student will be able to perform the following:

01.0	Define and describe the process of data analysis.
02.0	Describe the concepts of data science and how they are applied to data analysis.
03.0	Describe the implications of business intelligence analysis on an organization’s strategic marketing, organizational, and business plans.
04.0	Provide standard report specifications and generate standard or custom reports that summarize business, financial, or economic data for review by stakeholders.
05.0	Describe Security concerns associated with Data Science.
06.0	Define and differentiate among data constraints, filters, exception threshold, and data organization factors important in the creation of a report.
07.0	Locate, acquire, and model the data for analysis and output.
08.0	Compare and contrast the various forms for report presentation.
09.0	Describe the advantages and disadvantages for various report delivery mechanisms.
10.0	Reassess current business intelligence or trend data in support of altered information needs.
11.0	Analyze technology trends to identify markets for future product development or to improve sales of existing products.
12.0	Conduct or coordinate tests to ensure data analysis is consistent with defined needs.
13.0	Formulate and/or adhere to data governance policies and processes.
14.0	Identify and analyze industry or geographic trends with business strategy implications.
15.0	Describe best practices for change management to ensure data and report integrity and continuity.
16.0	Apply quality control standards and measures.
17.0	Compare and contrast the attributes and appropriateness of data analysis tools.
18.0	Describe the transformation and statistical functions used in Data Science.

Florida Department of Education
Student Performance Standards

Program Title:	Business Intelligence Specialist
CIP Number:		1530700101
Program Length:	60 credit hours
SOC Code(s):		

At the completion of this program, the student will be able to:	
01.0	Define and describe the process of data analysis.  The student will be able to:	
01.01	Describe the requirements of analysis planning. 	
01.01.1	Define the goals of the desired requirements.	
01.01.2	Select an appropriate analysis strategy.	
01.02	Describe the activities and goals of the design phase.	
01.02.1	Determine appropriate reporting format.	
01.02.2	Select appropriate reporting tool/form.	
01.02.3	Describe appropriate delivery mechanism.	
01.02.4	Define data criteria and constraints.	
01.02.5	Delineate report data definitions.	
01.03	Describe the activities and goals of the development phase.	
01.03.1	Identify available data sources and formats.	
01.03.2	Acquire data. 	
01.03.3	Analyze data.	
01.03.4	Create report.	
01.04	Describe the activities and goals of the evaluation phase.	
01.04.1	Define analytics/metrics suitable for evaluating accuracy and validity of results.	
01.04.2	Evaluate report output to assess whether intelligence is consistent with defined goals.	
01.04.3	Assess report performance and usability.	
01.05	Describe the activities and goals of the deployment and maintenance phase.	
01.05.1	Perform data reconciliation.	
01.05.2	Conduct periodic validation of reports with appropriate audiences and end-users.	
01.05.3	Track daily/weekly/monthly usage of data/reports.	
01.05.4	Determine proper “phasing out” thresholds for existing reports based on usage, data validity, and report reliability.	
01.05.5	Determine proper data archiving thresholds.	
02.0	
Describe the concepts of data science and how they are applied to data analysis.  The student will be able to:	
02.01	Define the role of data analysis in the decision-making process.	
02.02	Describe the domains of application of data science.	
02.03	Describe the sources of data and information used in the analysis of data.	
02.04	Describe the role and significance of data modeling, data warehousing, and data mining in data science.	
02.05	Describe the risks associated with data analysis (e.g., data validity, integrity, inappropriate analytics/metrics). 	
03.0	Describe the implications of business intelligence analysis on an organization’s strategic marketing, organizational, and business plans.  The student will be able to:	
03.01	Explain how business intelligence is used in creating, validating, and strengthening an organization’s strategic marketing plan.	
03.02	Explain how an organization’s internal processes, infrastructure, processes, and communication are impacted by the deployment of business intelligence.	
03.03	Explain how data science is used to facilitate an organization’s decision-making process.	
04.0	Provide standard report specifications and generate standard or custom reports that summarize business, financial, or economic data for review by stakeholders.  The student will be able to:	
04.01	Compare attributes and benefits of available data sources.	
04.01.1	RDBMS.	
04.01.2	Data warehouse and OLAP Cubes.	
04.01.3	Spreadsheet.	
04.01.4	XML.	
04.01.5	CSV.	
04.01.6	Web service.	
04.01.7	Raw Data and other (KML/Shape).	
04.02	Define report data elements/requirements (metadata).	
04.02.1	Dimensions.	
04.02.2	Type I (As is – current).	
04.02.3	Type II (Historical – slowly changing).	
04.02.4	Facts.	
04.02.5	Base.	
04.02.6	Summaries.	
04.02.7	Calculated fields.	
04.02.8	Periodicity.	
04.02.9	Relationships/JOINs.	
04.03	Describe how data is to be used.	
04.03.1	Data mining.	
04.03.2	Filtering.	
04.03.3	Exception threshold alerts.	
04.03.4	Aggregating.	
04.03.5	Snapshot.	
04.03.6	Dynamic.	
04.03.7	Historical/archive/disposal.	
04.04	Determine the form of analysis.	
04.04.1	Comparative analysis.	
04.04.2	Impact analysis.	
04.04.3	Correlational (affinity) analysis.	
04.04.4	Trending/Forecasting.	
05.0	Describe Security concerns associated with Data Science.  The student will be able to:	
05.01	Security Event and Event Management (SIEM).	
05.02	Threat detection and mitigation.	
05.03	Computer and network forensics.	
05.04	Security metrics.	
05.05	Fraud and loss analytics.	
05.06	Analysis of market.	
05.07	Risk measurement.	
05.08	Challenges.	
05.09	Applications.	
06.0	Define and differentiate among data constraints, filters, exception threshold, and data organization factors important in the creation of a report.  The student will be able to:	
06.01	Distinguish between data constraints and filters and their appropriate use.	
06.02	Describe how each of the following data constraints relates to the creation and/or delivery of a report.	
06.02.1	Size of recordset (scope & performance).	
06.02.2	Time/period (end points and span).	
06.02.3	Range (e.g., # of records).	
06.02.4	Data element (e.g., type, size).	
06.02.5	Localization (programming & display language).	
06.03	Describe how each of the following types of filters may be used to refine or enhance a report.	
06.03.1	Dimensions (Type I and Type II). 	
06.03.2	Facts (e.g., base, summaries, calculated fields).	
06.04	Illustrate how the use of an exception threshold contributes to the operational effectiveness of a report.	
06.04.1	Display or action dependent on threshold.	
06.04.2	Triggers alert or advance warning of approaching static threshold.	
06.04.3	Highlights results exceeding dynamic threshold.	
06.05	Compare and contrast the following forms of data organization in terms of representation and analysis of data results.	
06.05.1	GROUP BY.	
06.05.2	ORDER BY (SORT).	
06.05.3	Concatenation/substring.	
06.05.4	KRAN.	
07.0	Locate, acquire, and model the data for analysis and output.  The student will be able to:	
07.01	Identify the types of data that might be used to create business intelligence reports in support of the organization’s business and financial strategic goals.	
07.01.1	Inventory repositories.	
07.01.2	Sales data.	
07.01.3	Customer data.	
07.01.4	Employee/staffing data.	
07.01.5	Financial data.	
07.01.6	Spatial data	
07.01.7	Security and Risk	
07.02	Describe the risks and potential areas of concern related to the use of external data.	
07.02.1	Integrity/validity of data.	
07.02.2	Legality of data availability.	
07.02.3	Privacy issues of data acquired.	
07.02.4	Confidentiality of acquisition.	
07.03	Describe potential issues, concerns, and obstacles associated with the use of data sources.	
07.03.1	Data form.	
07.03.2	Data integrity.	
07.03.3	Normalization.	
07.03.4	Cleaning.	
07.04	Describe the role and implications of standardization relative to internal and external data sources.	
07.04.1	Describe the need for data typing and transformation.	
07.04.2	Describe the methods by which transformation may be accomplished.	
08.0	Compare and contrast the various forms for report presentation.  The student will be able to:	
08.01	Describe the form of data required for using a report generator.	
08.02	Describe the form of data required for using a spreadsheet.	
08.03	Describe the form of data required for using a database.	
08.04	Describe the form of data required for using an OLAP Cube or hypercube.	
08.05	Describe the attributes of a report suitable for presentation in HTML/Flash.	
08.06	Describe the form of data required for using a graph.	
08.07	Describe the form of data required using a dashboard interface.	
09.0	Describe the advantages and disadvantages for various report delivery mechanisms.  The student will be able to:	
09.01	Email.	
09.02	Web-based.	
09.03	Mobile device.	
09.04	Intranet.	
09.05	Print/PDF.	
09.06	Oral presentation.	
10.0	Reassess current business intelligence or trend data in support of altered information needs.  The student will be able to:	
10.01	Identify and relate report design constraints and their relationship to data.	
10.02	Evaluate current technology in terms of compatibility and capacity for meeting new or evolving information needs.	
10.03	Re-construct report based on alternative parameters.	
10.04	Adapt and validate report based on new requirements.	
11.0	Analyze technology trends to identify markets for future product development or to improve sales of existing products.  The student will be able to:	
11.01	Evaluate new technologies and products for applicability, capability, and capacity for current and future information needs.	
11.02	Create a proposal for introducing new, or adapting existing, business intelligence technology, including pricing, benefits summary, cost/benefit analysis, life cycle implications, and implementation plan.	
12.0	Conduct or coordinate tests to ensure data analysis is consistent with defined needs.  The student will be able to:	
12.01	Evaluate that reports meet requirements.	
12.02	Test metrics for accuracy and validity.	
12.03	Peer review.	
12.04	Use performance testing.	
12.05	Use performance tuning.	
13.0	Formulate and/or adhere to data governance policies and processes.  The student will be able to:	
13.01	Understand how information is disseminated to end-users.	
13.02	Adhere to policies, tool use, and processes related to data governance.	
14.0	Identify and analyze industry or geographic trends with business strategy implications.  The student will be able to:	
14.01	Compare and contrast key performance indicators appropriate to the industry.	
14.02	Define metrics to support analysis of targeted KPIs.	
14.03	Understand how the monitoring and analysis of key performance indicators strengthen or support the organization's goals and strategies.	
15.0	Describe best practices for change management to ensure data and report integrity and continuity.  The student will be able to:	
15.01	Authorize/permissions schema.	
15.02	Use internal controls.	
15.03	Impact analysis.	
15.04	Use Redundancy/archival policy.	
15.05	Assess readiness for change.	
15.06	Communicate changes.	
15.07	Separate duties (e.g., design, implementation, testing).	
16.0	Apply quality control standards and measures.  The student will be able to:	
16.01	Check data quality.	
16.02	Report quality.	
16.03	Analytic/metric quality.	
16.04	Check quality assurance.	
17.0	Compare and contrast the attributes and appropriateness of data analysis tools.  The student will be able to:	
17.01	Compare and contrast enterprise-based/integrated data science tools including, but not limited to, SAS, SAP, COGNOS, Hadoop, Cloudera.	
17.02	Compare and contrast native/client-based tools used in business intelligence analysis, including spreadsheets and SQL-compliant applications.	
18.0	Describe the transformation and statistical functions used in Data Science.  The student will be able to:	
18.01	Describe and apply the programming languages used in data science.	
18.02	Select an appropriate programming language and any desirable packages and apply the necessary transformation and statistical functions required to solve a problem.	

Additional Information

Laboratory Activities

Laboratory investigations that include scientific inquiry, research, measurement, problem solving, emerging technologies, tools and equipment, as well as, experimental, quality, and safety procedures are an integral part of this career and technical program/course. Laboratory investigations benefit all students by developing an understanding of the complexity and ambiguity of empirical work, as well as the skills required to manage, operate, calibrate and troubleshoot equipment/tools used to make observations. Students understand measurement error; and have the skills to aggregate, interpret, and present the resulting data. Equipment and supplies should be provided to enhance hands-on experiences for students.

Special Notes

General Education Course Requirements for AS and AAS Degrees
State Board of Education Rule 6A-14.030 (4) F.A.C. identifies 15 credit hours as the minimum amount of general education coursework required in the Associate of Science degree and the Associate of Applied Science degree. In addition, Rule 6A-14.0303 FAC implements section 1007.25 Florida Statutes and requires students entering a technical education degree program in the 2022-2023 academic year, and thereafter, to complete at least one identified core course in each subject area as part of the general education course requirements (15 credit hours total) before a degree is awarded) The core subject areas include: 
•	Communication. 
•	Humanities.
•	Mathematics. 
•	Natural Sciences.
•	Social Sciences.

Career and Technical Student Organization (CTSO)

Phi Beta Lambda (PBL) and Business Professionals of America (BPA) are the intercurricular career and technical student organizations providing leadership training and reinforcing specific career and technical skills.  Career and Technical Student Organizations provide activities for students as an integral part of the instruction offered.  

Accommodations

Federal and state legislation requires the provision of accommodations for students with disabilities to meet individual needs and ensure equal access. Postsecondary students with disabilities must self-identify, present documentation, request accommodations if needed, and develop a plan with their counselor and/or instructors. Accommodations received in postsecondary education may differ from those received in secondary education. Accommodations change the way the student is instructed. Students with disabilities may need accommodations in such areas as instructional methods and materials, assignments and assessments, time demands and schedules, learning environment, assistive technology and special communication systems. Documentation of the accommodations requested and provided should be maintained in a confidential file.

Certificate Programs

A College Credit Certificate consists of a program of instruction of less than sixty (60) credits of college-level courses, which is part of an AS or AAS degree program and prepares students for entry into employment (Rule 6A-14.030, F.A.C.).  This AS degree program includes the following College Credit Certificates:

Business Intelligence Professional (0552130101) – 20 credit hours 

Standards for the above certificate programs are contained in separate curriculum frameworks.

Additional Resources

For additional information regarding articulation agreements, Bright Futures Scholarships, Fine Arts/Practical Arts Credit and Equivalent Mathematics and Equally Rigorous Science Courses please refer to:
http://www.fldoe.org/academics/career-adult-edu/career-tech-edu/program-resources.stml