OpenText는 수십 년간의 전문 지식을 통해 데이터를 활용하고, 사람과 프로세스를 연결하며, 신뢰할 수 있는 AI를 강화합니다
기업 전체의 데이터를 매끄럽게 통합하여 정보 단절을 없애고, 협업을 강화하며, 리스크를 최소화하세요
데이터를 AI가 활용 가능하고 구조화되고, 접근 가능한, 최적화된 정보로 변환하세요
규제 및 준수 요구 사항을 충족하고 정보의 수명 주기 전반에 걸쳐 보호하세요
OpenText는 사람들이 콘텐츠를 관리하고, 작업을 자동화하며, AI를 사용하고, 협업하여 생산성을 높일 수 있도록 지원합니다
전 세계 수천 개의 기업이 OpenText의 혁신적인 솔루션으로 성공을 거두고 있는 방법을 확인해 보세요
직원은 OpenText의 가장 큰 자산으로, OpenText 브랜드와 가치의 생명입니다.
OpenText가 사회적 목표를 발전시키고 긍정적인 변화를 가속화하기 위해 어떤 노력을 하고 있는지 알아보세요
디지털 혁신을 이루기 최적인 솔루션과 전문성을 갖춘 OpenText 파트너를 만나보세요
새로운 방식으로 정보 보기
비즈니스, 데이터 및 목표를 파악하는 AI
더 빠른 의사 결정을 만나보세요. 안전한 개인 AI 비서가 업무를 시작할 준비가 되었습니다.
공급망을 위한 생성형 AI로 더 나은 인사이트를 얻어보세요.
AI 콘텐츠 관리 및 지능형 AI 콘텐츠 어시스턴트를 통해 효율적으로 작업하세요.
더 빠른 앱 제공, 개발 및 자동화된 소프트웨어 테스트를 만나보세요.
고객 성공을 위해 고객 커뮤니케이션과 경험을 개선해 보세요.
사용자, 서비스 상담원 및 IT 직원이 필요한 답을 찾을 수 있도록 권한을 부여하세요.
새로운 방식으로 정보 보기
비즈니스, 데이터 및 목표를 파악하는 AI
더 빠른 의사 결정을 만나보세요. 안전한 개인 AI 비서가 업무를 시작할 준비가 되었습니다.
공급망을 위한 생성형 AI로 더 나은 인사이트를 얻어보세요.
AI 콘텐츠 관리 및 지능형 AI 콘텐츠 어시스턴트를 통해 효율적으로 작업하세요.
더 빠른 앱 제공, 개발 및 자동화된 소프트웨어 테스트를 만나보세요.
고객 성공을 위해 고객 커뮤니케이션과 경험을 개선해 보세요.
사용자, 서비스 상담원 및 IT 직원이 필요한 답을 찾을 수 있도록 권한을 부여하세요.
한 번만 연결하면 안전한 B2B 통합 플랫폼으로 모든 대상과 연결할 수 있습니다.
AI가 활용 가능한 콘텐츠 관리 솔루션으로 지식 재구성
기업 보호를 위한 통합 사이버 보안 솔루션
AI 기반 DevOps 자동화, 테스트 및 품질을 통해 더 나은 소프트웨어를 더 빠르게 제공
잊을 수 없는 고객 경험으로 대화 재창조
IT 운영의 비용과 복잡성을 줄이기 위해 필요한 명확성 확보
검증된 OpenText 정보 관리 기술을 사용하여 맞춤형 애플리케이션 구축
사용자 정의 애플리케이션 및 워크플로를 지원하는 실시간 정보 흐름을 제공하는 OpenText Cloud API를 사용하여 원하는 방식으로 구축
안전한 정보 관리가 신뢰할 수 있는 AI를 만나다
데이터와 AI의 신뢰를 높이는 통합 데이터 프레임워크
데이터 언어로 에이전트를 구축, 배포 및 반복할 수 있는 공간
AI를 강화하기 위해 데이터 수집 및 메타데이터 태그 지정 자동화를 지원하는 도구 세트
거버넌스를 사전 예방적이고 지속 가능하게 만드는 서비스 및 API 제품군
AI 여정을 도와주는 전문 서비스 전문가
새로운 방식으로 정보 보기
비즈니스, 데이터 및 목표를 파악하는 AI
더 빠른 의사 결정을 만나보세요. 안전한 개인 AI 비서가 업무를 시작할 준비가 되었습니다.
공급망을 위한 생성형 AI로 더 나은 인사이트를 얻어보세요.
AI 콘텐츠 관리 및 지능형 AI 콘텐츠 어시스턴트를 통해 효율적으로 작업하세요.
더 빠른 앱 제공, 개발 및 자동화된 소프트웨어 테스트를 만나보세요.
고객 성공을 위해 고객 커뮤니케이션과 경험을 개선해 보세요.
사용자, 서비스 상담원 및 IT 직원이 필요한 답을 찾을 수 있도록 권한을 부여하세요.
OpenText는 주요 클라우드 인프라 제공업체와 협력하여 어디서나 OpenText 솔루션을 실행할 수 있는 유연성을 제공합니다
OpenText는 최고의 엔터프라이즈 앱 제공업체와 협력하여 비정형 데이터를 활용함으로써 더 나은 비즈니스 인사이트를 제공합니다
Nottingham Trent UniversitySophisticated data analytics from OpenText help enhance programs to reduce student dropout rates

Improve the ability to reduce student dropout rates.
NTU has always had a low drop-out rate, notes Mike Day, the university’s Director of Information Systems. At about 7 percent, Day says, the university dropout rate is “better than sector average.”
But NTU knows better than to assume that its current success will continue—particularly as its student body demographic evolves. NTU’s enrollment is growing. It expects to add around 2,000 students over the next few years.
Equally significant, the percentage of students the university classifies as “widening participation” students will likely rise. Students in this category typically come from lower socioeconomic areas. Often, they represent the first generation in their families to attend university. As a result, these students may lack confidence in their ability to navigate the university system. They may not take advantage of its academic and counseling support systems. “We’ve come to call them ‘doubter students’”, says Day. “When they struggle, they believe it’s their fault, and so they typically don’t ask for help.”
NTU’s challenge was to identify which students were either struggling or—better yet—at risk of encountering academic challenges. If it could identify those students quickly enough, it could intervene by proactively reaching out to them to offer guidance and support.
With around 28,000 students, Nottingham Trent University (NTU), located in the Midlands region of Central England, is one of the largest universities in the United Kingdom. It also has one of the U.K.’s best employability records. Nearly 93 percent of NTU’s students earn their degrees; 94 percent of its graduates either find full-time work or continue their education within six months of completing their NTU studies.
NTU’s success in launching students’ careers is partly a reflection of its history, focus, and culture. The university has a strong history in the fields of design and polytechnic studies. Its manifesto, Creating the University of the Future, states that every NTU course should reflect strong links to employers; NTU meets this objective by cultivating strong, collaborative relationships with the business community.
But NTU relies on more than manifestos and relationships to serve its students. It also leverages technology—including a cutting-edge analytics application powered by OpenText™ Knowledge Discovery.
OpenText Knowledge Discovery [IDOL] is helping us improve student engagement—which makes us an even better university.
The university started by considering the data footprint students leave as they move about the university campuses and use its facilities and services. Students swipe their smart cards to enter buildings, use printers, use libraries, and access learning management systems. “We wanted to see whether those things would give us some indication as to how well students were engaged in their studies and therefore whether they’re struggling or not,” says Day.
While some of the university’s 600TB of student data is structured, much of it is not. The university discovered that it was virtually impossible to integrate its disparate datasets using traditional business intelligence tools. So instead, NTU engaged with OpenText™ partner DTP Solutionpath to implement an OpenText Knowledge Discovery business analytics application. To build the solution, NTU provided DTP Solutionpath with five years’ worth of back data. Then, working closely with the university’s IT team, the vendor used OpenText Knowledge Discovery analytics to create what Day calls “a model of engagement”: data combinations that indicate levels of student engagement— or disengagement. DTP Solutionpath also built a dashboard that lets students visualize their engagement. It is a very simple visualization, Day explains.
“It’s two lines on a chart. One of those lines is the average engagements of the cohort on a course-by-course basis. The other line is the individual student’s engagement compared to that average engagement in the course.”
Another, equally important aspect of the modeling was student privacy. The university had to make sure the application was in full compliance with U.K. Data Protection law. In addition, NTU worked with its students and staff to understand how they would view its data collection and analysis procedures. “We worked very hard … to understand what would be acceptable and what wouldn’t,” explains Day, noting that this understanding is “perhaps even more important than the strict legal position.” The university found that if students understood that the intent was to help them succeed, they were supportive of the project.
With the model complete and the student body on board, the university launched a series of 12-month pilots. The pilots followed students who enrolled in specific courses. Within six months of beginning the pilots, the university had its answer. The OpenText Knowledge Discovery analytics tool works: it detects that students are disengaging from their studies one to two months earlier than would otherwise be noticeable by teachers or staff.
And earlier detection supports more effective intervention. “In more than 90 percent of the cases we have seen so far,” Day says, “early conversations result in an immediate upturn in student engagement. We’ve seen some very real tangible results and we saw those very early on.”
In addition to the quantifiable results, the pilot demonstrated a number of intangible benefits. The university’s academic tutors began using the engagement metrics as a starting point to discuss and share best practices. The metrics also prompted tutors to reach out to students who might be in need of academic help. As a result, Day says, the relationships between students and tutors have become more fruitful and positive.
The application has also shown signs of encouraging healthy competition among the students, as they strive to improve their engagement metrics relative to their peers.
The pilots were so successful, in fact, that NTU deployed the program across the entire university six months sooner than it originally planned and is now in its second academic year of operation.
The university is also sharing what it has learned with other U.K. institutions. It is working with DTP Solutionpath to create a model that other universities can replicate.
“It starts with a readiness exercise,” Day explains, “because this is not about technology … it’s about how ready you are, as an organization, to address things like privacy and ethics.”
Day views its program, in fact, as a “kind of bridgehead” that will allow NTU to apply cutting-edge data analytics to other aspects of the university enterprise. For example, NTU might be able to gain a deeper understanding in the factors that predict student success, to help it match its recruiting efforts to its academic programs. OpenText Knowledge Discovery analytics might also help NTU better understand how students fare after graduation, as the basis for refining its job counseling and career advisement services.
Even without these future use cases, the OpenText Knowledge Discovery solution delivers clear benefits to Nottingham Trent. Recruiting students costs money; minimizing student dropout rate is therefore good business practice.
Perhaps more importantly, the solution benefits NTU students. The university’s yearly tuition is £9,000 (USD 13,760) plus board. If students earn their degrees and find employment after graduation, chances are very high they will recoup that investment. If they drop out, on the other hand, they risk finding themselves trapped in a downward economic spiral of unemployment and debt. “It means perhaps a diminished potential for them over their lifetime of career, monetization of income, and contribution to society,” notes Day.
Thanks to OpenText Knowledge Discovery, fewer NTU students face this risk—which is a win for the students, a win for the university, and a win for the economic future of the United Kingdom.

Nottingham Trent University has an excellent reputation for preparing students for post graduation employment. But the university wants to keep improving its graduation rate, even as it increasingly recruits students that are at greater risk of dropping out. So it implemented a sophisticated data analytics application from OpenText Knowledge Discovery Platform that allows it to more quickly detect issues with student engagement, which in turn enables the university to intervene in time to keep its students on track.