Aggregate Analyses Sample Clauses

Aggregate Analyses. SAP Ariba may use transaction information relating to use of the SAP Ariba Cloud Services to prepare analyses. The analyses prepared are aggregated and do not contain personal data nor Customer Confidential Information. Examples of analyses include: optimizing systems and technical resources and support, research and development of Cloud and Consulting Services, verification of security and data integrity, internal demand planning, industry and macroeconomic statistics and anonymous benchmarking with other Customers. SAP Ariba may report aggregated and anonymous statistics about use of the SAP Ariba Cloud Service publicly.
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Aggregate Analyses. SAP may use transaction information relating to use of the Cloud Services to prepare analyses. The analyses prepared are aggregated and do not contain personal data nor Customer Confidential Information. Examples of analyses include: optimizing systems and technical resources and support, research and development of Cloud Services and Consulting Services, verification of security and data integrity, internal demand planning, industry and macroeconomic statistics and anonymous benchmarking with other Customers. SAP may report aggregated and anonymous statistics about use of the Cloud Service publicly.
Sample 1
Aggregate Analyses. SAP Ariba may use transaction information relating to use of the SAP Ariba Cloud Services to prepare analyses. The analyses prepared are aggregated and do not contain personal data nor Customer Confidential Information. Examples of analyses include: optimizing systems and technical resources and support, research and development of Cloud and Consulting Services, verification of security and data integrity, internal demand planning, industry and macroeconomic statistics and anonymous benchmarking with other Customers. SAP Ariba may report aggregated and anonymous statistics about use of the SAP Ariba Cloud Service publicly. 聚合分析。SAP Ariba 可以利用与使用 SAP Ariba 云服务相关的交易信息来准备分析。准备好的分析会聚合在一起，但不包含个人数据或客户保密信息。分析示例包括：优化系统和技术资源与支持、研发云服务和咨询服务、验证安全性和数据完整性、制定内部需求计划、进行行业和宏观经济统计以及与其他客户的匿名对标。SAP Ariba 可以公开报告有关 SAP Ariba 云服务使用情况的匿名聚合统计数据。
Sample 1
Aggregate Analyses. SAP Ariba may use transaction information relating to use of the SAP Ariba Cloud Services to prepare analyses. The analyses prepared are aggregated and do not contain personal data nor Customer Confidential Information. Examples of analyses include: optimizing systems and technical resources and support, research and development of Cloud and Consulting Services, verification of security and data integrity, internal demand planning, industry and macroeconomic statistics and anonymous benchmarking with other Customers. SAP Ariba may report aggregated and anonymous statistics about use of the SAP Ariba Cloud Service publicly. 7.3 종합 분석. SAP Ariba 는 분석 준비를 위해 SAP Ariba 클라우드 서비스의 사용과 관련한 트랜잭션 정보를 사용할 수 있습니다. 작성된 분석은 종합되며, 개인 정보 또는 고객 비밀 정보를 포함하지 않습니다. 분석의 예에는 시스템 및 기술적 자원과 지원의 최적화, 클라우드/컨설팅 서비스의 연구 및 개발, 보안 및 데이터 무결성 확인, 내부 수요 계획, 업계 및 거시경제 통계, 다른 고객과의 익명 벤치마킹이 포함됩니다. SAP Ariba 는 SAP Ariba 클라우드 서비스의 사용에 관한 종합된 익명 통계를 공개적으로 보고할 수 있습니다.
Sample 1
Aggregate Analyses. SAP may use transaction information relating to use of the Cloud Services to prepare analyses. The analyses prepared are aggregated and do not contain personal data nor Customer Confidential Information. Examples of analyses include: optimizing systems and technical resources and support, research and development of Cloud Services and Consulting Services, verification of security and data integrity, internal demand planning, industry and macroeconomic statistics and anonymous benchmarking with other Customers. SAP may report aggregated and anonymous statistics about use of the Cloud Service publicly. 8.3 종합 분석. SAP 는 분석 준비를 위해 클라우드 서비스의 사용과 관련한 트랜잭션 정보를 사용할 수 있습니다. 작성된 분석은 종합되며, 개인 정보 또는 고객 비밀 정보를 포함하지 않습니다. 분석의 예에는 시스템 및 기술적 자원과 지원의 최적화, 클라우드 서비스/컨설팅 서비스의 연구 및 개발, 보안 및 데이터 무결성 확인, 내부 수요 계획, 업계 및 거시경제 통계, 다른 고객과의 익명 벤치마킹이 포함됩니다. SAP 는 클라우드 서비스의 사용에 관한 종합된 익명 통계를 공개적으로 보고할 수 있습니다.
Sample 1

Related to Aggregate Analyses

  • Statistical Analysis 31 F-tests and t-tests will be used to analyze OV and Quality Acceptance data. The F-test is a 32 comparison of variances to determine if the OV and Quality Acceptance population variances 33 are equal. The t-test is a comparison of means to determine if the OV and Quality Acceptance 34 population means are equal. In addition to these two types of analyses, independent verification 35 and observation verification will also be used to validate the Quality Acceptance test results.

  • Statistical Sampling Documentation a. A copy of the printout of the random numbers generated by the “Random Numbers” function of the statistical sampling software used by the IRO.

  • Data Analysis In the meeting, the analysis that has led the College President to conclude that a reduction- in-force in the FSA at that College may be necessary will be shared. The analysis will include but is not limited to the following: ● Relationship of the FSA to the mission, vision, values, and strategic plan of the College and district ● External requirement for the services provided by the FSA such as accreditation or intergovernmental agreements ● Annual instructional load (as applicable) ● Percentage of annual instructional load taught by Residential Faculty (as applicable) ● Fall Full-Time Student Equivalent (FFTE) inclusive of dual enrollment ● Number of Residential Faculty teaching/working in the FSA ● Number of Residential Faculty whose primary FSA is the FSA being analyzed ● Revenue trends over five years for the FSA including but not limited to tuition and fees ● Expenditure trends over five years for the FSA including but not limited to personnel and capital ● Account balances for any fees accounts within the FSA ● Cost/benefit analysis of reducing all non-Residential Faculty plus one Residential Faculty within the FSA ● An explanation of the problem that reducing the number of faculty in the FSA would solve ● The list of potential Residential Faculty that are at risk of layoff as determined by the Vice Chancellor of Human Resources ● Other relevant information, as requested

  • Justification and Anticipated Results The Privacy Act requires that each matching agreement specify the justification for the program and the anticipated results, including a specific estimate of any savings. 5 U.S.C. § 552a(o)(1)(B).

  • DATA COLLECTION AND ANALYSIS The goal of this task is to collect operational data from the project, to analyze that data for economic and environmental impacts, and to include the data and analysis in the Final Report. Formulas will be provided for calculations. A Final Report data collection template will be provided by the Energy Commission. The Recipient shall: • Develop data collection test plan. • Troubleshoot any issues identified. • Collect data, information, and analysis and develop a Final Report which includes: o Total gross project costs. o Length of time from award of bus(es) to project completion. o Fuel usage before and after the project.

  • How to Update Your Records You agree to promptly update your registration records if your e-mail address or other information changes. You may update your records, such as your e-mail address, by using the Profile page.

  • MATERIAL SAFETY DATA SHEETS Contractor is required to ensure Material Safety Data Sheets (“MSDS”) are available, employees are trained in the use of MSDS, and MSDS are in a readily accessible place at the Site. This requirement applies to all materials with an associated MSDS per the federal “Hazard Communication” standard or employees’ Right-to-Know laws. Contractor is also required to ensure proper labeling and training on any substance brought onto the Site and that any person working with the material (or who is subject to possible exposure by use of the material or contact with the material), is informed of the possible and/or real hazards of the substance, and follows proper handling and protection procedures.

  • SERVICE MONITORING, ANALYSES AND ORACLE SOFTWARE 11.1 We continuously monitor the Services to facilitate Oracle’s operation of the Services; to help resolve Your service requests; to detect and address threats to the functionality, security, integrity, and availability of the Services as well as any content, data, or applications in the Services; and to detect and address illegal acts or violations of the Acceptable Use Policy. Oracle monitoring tools do not collect or store any of Your Content residing in the Services, except as needed for such purposes. Oracle does not monitor, and does not address issues with, non-Oracle software provided by You or any of Your Users that is stored in, or run on or through, the Services. Information collected by Oracle monitoring tools (excluding Your Content) may also be used to assist in managing Oracle’s product and service portfolio, to help Oracle address deficiencies in its product and service offerings, and for license management purposes.

  • Program Evaluation The School District and the College will develop a plan for the evaluation of the Dual Credit program to be completed each year. The evaluation will include, but is not limited to, disaggregated attendance and retention rates, GPA of high-school-credit-only courses and college courses, satisfactory progress in college courses, state assessment results, SAT/ACT, as applicable, TSIA readiness by grade level, and adequate progress toward the college-readiness of the students in the program. The School District commits to collecting longitudinal data as specified by the College, and making data and performance outcomes available to the College upon request. HB 1638 and SACSCOC require the collection of data points to be longitudinally captured by the School District, in collaboration with the College, will include, at minimum: student enrollment, GPA, retention, persistence, completion, transfer and scholarships. School District will provide parent contact and demographic information to the College upon request for targeted marketing of degree completion or workforce development information to parents of Students. School District agrees to obtain valid FERPA releases drafted to support the supply of such data if deemed required by counsel to either School District or the College. The College conducts and reports regular and ongoing evaluations of the Dual Credit program effectiveness and uses the results for continuous improvement.

  • SMALL BUSINESS PARTICIPATION AND DVBE PARTICIPATION REPORTING REQUIREMENTS a. If for this Contract Contractor made a commitment to achieve small business participation, then Contractor must within 60 days of receiving final payment under this Contract (or within such other time period as may be specified elsewhere in this Contract) report to the awarding department the actual percentage of small business participation that was achieved. (Govt. Code § 14841.)

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