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The Impact of Generative and Predictive AI on Higher Education: Revolutionizing Administration, and Student Success and Student and Faculty Satisfaction

Impact of Generative and Predictive AI
Impact of Generative and Predictive AI

Generative and Predictive AI continues to emerge as a transformative force across multiple sectors, including higher education. With its ability to understand, learn, and create content, AI offers powerful solutions to streamline administrative processes, boost student success, and improve student and faculty satisfaction. 

Optimizing Administrative Operations

Higher education institutions manage a wide range of administrative tasks, often leading to inefficiencies. AI can automate many of these processes—such as scheduling, data analysis, and report creation. For example, AI solutions can: 

This automation not only alleviates administrative workloads but also enhances the speed and accuracy of decision-making.

Student and Faculty Satisfaction

AI can automate and optimize an institution’s course catalog, resulting in improved student and faculty satisfaction. As a result, Gen AI is capable of:

  • Generating and updating course descriptions, prerequisites, and availability
  • Analyzing students’ academic history and interests to recommend courses
  • Chatbots to answer questions and assist with course selection
  • Optimizing course scheduling by analyzing faculty availability and room capacity
  • Managing real-time catalog updates, tracking changes, and maintaining version control
  • Translating the catalog into multiple languages
  • Forecasting course demand based on enrollment patterns

Supporting Student Success

Improving student success through one-to-one support and early interventions is a key factor to success and retention. Predictive analytics leveraging AI can:

  • Identify at-risk students based on factors such as attendance, grades, and engagement
  • Early detection allows institutions to implement targeted interventions—such as tutoring or counseling—leading to higher retention rates and greater student satisfaction

Conclusion

In conclusion, Generative and Predictive AI continue to rapidly transform higher education by enhancing administrative efficiency, student success, and overall satisfaction for both students and faculty. By automating tasks, optimizing course offerings, and providing early intervention for at-risk students, AI-driven solutions streamline institutional processes while improving academic outcomes.

As AI continues to evolve, its role in higher education will only deepen, allowing institutions to operate more effectively, enhance student experiences, and ultimately support the achievement of educational goals on a broader scale.

If you want to learn more about Generative and Predictive AI, Datatelligent now offers a cost-effective training course specifically designed for higher education.

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Overcoming Higher Education Challenges with Effective Education Resource Strategies

Higher Education Resource Strategies
Higher Education Resource Strategies

Colleges and universities are facing an unprecedented number of challenges that threaten their long-term sustainability. Schools need to strategically assess their programs and operations to optimize their resources, stay competitive, and continue delivering quality educational experiences.

Current Challenges

  1. Enrollment Cliff: The “enrollment cliff” refers to the anticipated significant decline in high school graduates starting around 2025, mainly due to reduced birth rates following the 2008 economic downturn. Colleges, particularly small liberal arts schools, are already experiencing closures and faculty layoffs as they prepare for this demographic shift. School districts are also slashing budgets and making tough decisions about cuts to programs and services[1][2][3].
  2. New FAFSA Form Problems: The launch of a new Free Application for Federal Student Aid (FAFSA) form has led to delays and glitches, complicating the financial aid process for many students. As a result, students are now evaluating admission offers without knowing their financial aid packages, which is expected to worsen the enrollment cliff. The impact is most pronounced at more expensive colleges and those with a high percentage of students relying on financial aid. [4].
  3. Financial Strains: The depletion of COVID-19 relief funds has intensified financial strains on educational institutions. Many schools relied on these funds to cover budget shortfalls during the pandemic, and their absence is now forcing schools to make difficult financial decisions, including cutting programs, reducing staff, and exploring new revenue streams to stay financially stable [1][5].
  4. Declining Attitudes: There has been a cultural shift in attitudes toward the value of a college degree, particularly in the wake of the COVID-19 pandemic. Many students question whether the high cost of tuition is worth the investment, especially as they see peers finding success through alternative pathways such as vocational training. This skepticism contributes to declining enrollment numbers and is a significant challenge for higher education institutions seeking to attract and retain students[2][3]. 

Understanding Education Resource Strategies

At Datatelligent, we specialize in data analytics for higher education. We found that colleges and universities can successfully manage and overcome these challenges by developing sound education resource strategies supported by a comprehensive data analytics strategy.

Education resource strategies encompass a range of approaches and methodologies aimed at optimizing the use of financial, human, and physical resources in educational institutions. These strategies ensure efficient and effective allocation of resources to support teaching, learning, and institutional growth.

The Role of Data Analytics in Resource Optimization

Data analytics plays a pivotal role in developing and implementing education resource strategies. Institutions can make informed decisions that align with their strategic goals by analyzing student demographics, enrollment trends, course demand, and resource utilization. Below are a few ways data analytics can enhance education resource strategies:

  1. Enrollment Management: Predictive analytics can forecast enrollment trends, allowing institutions to plan for fluctuations and allocate resources accordingly, ensuring optimal use of classrooms, faculty, and facilities.
  2. Curriculum Development: Data-driven insights into student performance and course demand can guide curriculum development, helping institutions identify high-demand courses and areas needing improvement.
  3. Academic Planning: Effective academic planning is essential for the long-term success of any institution. Data analytics, incorporating regional employer data, can provide insights into future academic and training needs, helping institutions plan for new programs, faculty hiring, and resource allocation to meet future demands.
  4. Financial Planning: By analyzing financial data, institutions can identify cost-saving opportunities and areas where investments can yield the highest returns. This analysis includes optimizing staffing levels, managing operational costs, and strategically planning capital expenditures.
  5. Student Support Services: Data analytics can help institutions identify at-risk students and tailor support services to meet their needs. This targeted approach ensures that you allocate resources to interventions that significantly impact student success.

The Future of Education Resource Strategies

As higher education continues to evolve, the importance of effective education resource strategies cannot be overstated. Institutions that leverage data analytics to inform their decision-making processes will be better positioned to navigate future challenges and provide exceptional educational experiences.

At Datatelligent, we are committed to helping higher education institutions harness the power of data analytics to optimize their resources and achieve their strategic objectives. By developing and implementing tailored education resource strategies, we empower institutions to thrive in an increasingly competitive and dynamic environment.

In conclusion, when combined with advanced data analytics, education resource strategies can transform how higher education institutions manage their resources. By making informed decisions based on data-driven insights, institutions can enhance efficiency, improve student outcomes, and ensure long-term sustainability. If your institution is ready to take the next step in optimizing its resources and academic planning, contact Datatelligent today to learn how our solutions can help you achieve your goals.

Citations

[1] Schools are bracing for the looming “enrollment cliff”, Jennifer A. Kingston, Axios, July 3, 2024, https://www.axios.com/2024/07/03/education-enrollment-cliff-schools

[2] 2024 Higher Education Trends, Cole Clark, Megan Cluver, Tiffany Fishman, Danylle Kunkel, Deloitte Insights, April 19, 2024, https://www2.deloitte.com/us/en/insights/industry/public-sector/latest-trends-in-higher-education.html

[3] How Colleges Leverage Data to Retain Students as the Enrollment Cliff Looms, Lauren Glenn Manfuso, EdTech, May 21, 2024, https://edtechmagazine.com/higher/article/2024/05/how-colleges-leverage-data-retain-students-enrollment-cliff-looms

[4] FAFSA completions largely stalled in June, fueling enrollment concerns, Laura Spitalniak, Higher Ed Dive, July 10, 2024, https://www.highereddive.com/news/fafsa-completions-largely-stalled-june-fueling-enrollment-concerns-ncan/720908/

[5] Higher Education Faces Hurdles in 2024, Brian Mitchell, Forbes, February 14, 2024, https://www.forbes.com/sites/forbesbusinesscouncil/2024/02/14/higher-education-faces-hurdles-in-2024/

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Enhancing Academic Planning with Higher Education Data Management

Higher Education data management
Higher Education data management

In the rapidly evolving landscape of higher education, effective data management has become essential for universities striving to achieve excellence. The ability to harness data not only improves operational efficiency but also plays a pivotal role in academic planning, student success, and overall institutional performance. At Datatelligent, we specialize in higher education data management, offering solutions that empower universities to make informed decisions and drive continuous improvement.

The Importance of Data Management in Higher Education

Higher education data management involves collecting, storing, analyzing, and using data for academic and administrative support. Universities generate vast amounts of data daily, from student records and faculty information to research outputs and financial transactions. Efficiently managing this data is crucial for several reasons:

 

    1. Informed Decision-Making: Accurate and timely data allows university leaders to make evidence-based decisions. Whether it’s allocating resources, designing curricula, or setting strategic priorities, data-driven insights ensure that decisions are aligned with institutional goals.

    1. Improving Student Outcomes: Higher education data management enables universities to track student performance, identify at-risk students, and implement targeted interventions. By analyzing data on attendance, grades, and engagement, institutions can develop strategies to enhance student success and retention rates.

    1. Enhancing Operational Efficiency: Streamlined data processes reduce administrative burdens, allowing staff to focus on core activities. Automating routine tasks such as admissions, scheduling, and reporting frees up valuable time and resources, leading to increased productivity.

    1. Supporting Research and Innovation: Effective data management supports research activities by providing easy access to datasets, facilitating collaboration, and ensuring compliance with regulatory requirements. Researchers can leverage data to generate insights, secure funding, and drive innovation.

How Datatelligent Supports Higher Education Data Management

At Datatelligent, we understand the unique challenges faced by higher education institutions. Our comprehensive data management solutions are designed to address these challenges and support universities in achieving their academic and operational objectives. Here’s how we can help:

 

    1. Data Integration and Centralization: We assist universities in integrating data from disparate sources into a centralized system. This holistic approach ensures that all relevant data is easily accessible and eliminates silos, enabling a unified view of institutional performance.

    1. Advanced Analytics and Reporting: Our advanced analytics tools allow universities to extract actionable insights from their data. We provide customizable dashboards and reports that enable stakeholders to monitor key metrics, track progress, and identify trends.

    1. Data Governance and Security: Ensuring the integrity and security of data is paramount. Datatelligent implements robust data governance frameworks and security protocols to protect sensitive information and ensure compliance with regulatory standards.

    1. Scalable Solutions: Our solutions are scalable to accommodate the evolving needs of higher education institutions. Whether a university is expanding its programs, increasing student enrollment, or enhancing research capabilities, our data management systems can scale accordingly.

    1. Expert Support and Training: We offer ongoing support and training to ensure that university staff are equipped with the knowledge and skills to effectively manage and utilize data. Our team of experts is available to provide guidance, troubleshoot issues, and facilitate continuous improvement.

Real-World Impact of Effective Data Management

The impact of effective higher education data management can be profound. Universities that leverage data to inform their strategies can achieve remarkable results, including:

 

    • Improved Student Retention and Graduation Rates: Identifying at-risk students helps improve retention and graduation rates, boosting student success and institutional reputation.

    • Enhanced Research Output: Comprehensive data and analytics tools enable researchers to conduct studies, secure funding, and advance knowledge.

    • Optimized Resource Allocation: Data-driven decisions ensure efficient resource allocation, maximizing their impact on academic programs and student services.

    • Increased Operational Efficiency: Automation and streamlined processes reduce administrative overhead, enabling staff to focus on strategic initiatives and student engagement.

Why Choose Datatelligent?

Datatelligent stands out as a trusted partner in higher education data management. Our deep understanding of the sector, combined with our cutting-edge technology and commitment to customer success, makes us the ideal choice for universities seeking to enhance their data capabilities. By partnering with Datatelligent, institutions can unlock the full potential of their data, drive continuous improvement, and achieve their academic and operational goals.

In conclusion, effective data management in higher education is a critical enabler of success. From improving student outcomes to supporting research and optimizing operations, the benefits are far-reaching. Datatelligent’s comprehensive solutions empower universities to harness the power of their data, making informed decisions and driving excellence across all areas of their institution.

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Optimizing Education Resource Strategies for Academic Success

Education Resource Strategies
Education Resource Strategies

Effective education resource strategies are crucial for universities aiming to optimize their operations, enhance student success, and achieve their academic missions. At Datatelligent, we specialize in providing innovative solutions that help universities manage their resources more effectively, ensuring that every dollar spent and every hour invested contribute to the institution’s goals. In this blog, we will explore the importance of robust education resource strategies and how Datatelligent can support universities in implementing these strategies to achieve excellence.

Understanding Education Resource Strategies

Education resource strategies encompass the planning, allocation, and management of an institution’s financial, human, and physical resources. These strategies ensure that resources are used efficiently and effectively to support academic programs, student services, research initiatives, and operational functions. Key components of education resource strategies include:

 

    1. Financial Management: Efficient budgeting, forecasting, and financial planning are essential for maintaining fiscal health. Universities must allocate funds strategically to support priority areas, manage costs, and ensure long-term sustainability.

    1. Human Resource Management: Attracting, retaining, and developing talented faculty and staff are critical for delivering high-quality education. Effective human resource strategies include recruitment, professional development, performance management, and succession planning.

    1. Infrastructure Management: Universities must maintain and optimize their physical infrastructure, including classrooms, laboratories, libraries, and student housing. This involves regular maintenance, upgrading facilities, and ensuring that spaces meet the needs of the academic community.

    1. Technology Integration: Leveraging technology to enhance teaching, learning, and administration is a key aspect of modern education resource strategies. This includes investing in digital learning platforms, data management systems, and cybersecurity measures.

The Role of Data in Education Resource Strategies

Data plays a central role in developing and implementing effective education resource strategies. By analyzing data on financial performance, human resources, facility usage, and technology adoption, universities can make informed decisions that optimize resource allocation and utilization. Key benefits of data-driven resource strategies include:

 

    1. Informed Decision-Making: Data-driven insights enable university leaders to make evidence-based decisions that align with institutional goals. For example, financial data can inform budget allocation, while human resource data can guide recruitment and retention efforts.

    1. Improved Efficiency: Analyzing data on resource usage helps identify inefficiencies and areas for improvement. For instance, analyzing classroom occupancy rates can inform decisions on space utilization, reducing wasted resources.

    1. Enhanced Accountability: Data transparency promotes accountability by providing clear metrics for performance evaluation. Stakeholders can track progress, assess the impact of resource investments, and ensure that resources are used effectively.

    1. Strategic Planning: Data supports long-term strategic planning by providing insights into trends, opportunities, and challenges. Universities can develop proactive strategies to address emerging needs and capitalize on future opportunities.

How Datatelligent Supports Education Resource Strategies

At Datatelligent, we offer comprehensive solutions that empower universities to develop and implement effective education resource strategies. Our expertise in data management and analytics enables institutions to harness the power of their data for optimal resource planning and utilization. Here’s how we can help:

 

    1. Data Integration and Centralization: We assist universities in integrating data from various sources into a centralized system. This unified approach ensures that all relevant data is easily accessible, facilitating comprehensive analysis and informed decision-making.

    1. Advanced Analytics and Reporting: Our advanced analytics tools provide customizable dashboards and reports that deliver actionable insights. University leaders can monitor key performance indicators, track resource usage, and identify opportunities for optimization.

    1. Financial Planning and Analysis: We offer solutions for budgeting, forecasting, and financial analysis that support strategic financial management. Our tools enable universities to allocate funds effectively, manage costs, and ensure financial sustainability.

    1. Human Resource Analytics: Our human resource analytics solutions help universities attract, retain, and develop top talent. By analyzing data on recruitment, performance, and professional development, institutions can optimize their human resource strategies.

    1. Facility and Infrastructure Management: We provide tools for monitoring and managing physical infrastructure, ensuring that facilities meet the needs of the academic community. Our solutions support maintenance planning, space utilization analysis, and capital project management.

    1. Technology Integration and Support: We assist universities in leveraging technology to enhance education and administration. Our solutions include digital learning platforms, data management systems, and cybersecurity measures that support effective technology integration.

Real-World Impact of Effective Education Resource Strategies

The impact of effective education resource strategies can be transformative for universities. Institutions that adopt data-driven approaches to resource management can achieve remarkable results, including:

 

    • Increased Operational Efficiency: Optimizing resource allocation and utilization reduces waste, lowers costs, and improves productivity, enabling universities to deliver high-quality education more efficiently.

    • Enhanced Student Success: By investing resources strategically in academic programs, student services, and support initiatives, universities can improve student retention, graduation rates, and overall success.

    • Strengthened Financial Health: Robust financial management ensures that universities maintain fiscal stability, manage risks, and achieve long-term sustainability.

    • Improved Campus Facilities: Effective infrastructure management ensures that facilities are well-maintained, meet the needs of the academic community, and support a conducive learning environment.

Why Choose Datatelligent?

Datatelligent is a trusted partner for universities seeking to optimize their education resource strategies. Our deep understanding of the higher education sector, combined with our advanced technology and commitment to customer success, makes us the ideal choice for institutions aiming to enhance their resource management capabilities. By partnering with Datatelligent, universities can leverage data-driven insights to achieve their academic and operational goals.

In conclusion, effective education resource strategies are essential for universities striving for excellence. By adopting data-driven approaches to financial, human resource, infrastructure, and technology management, institutions can optimize resource allocation, enhance student success, and achieve their academic missions. Datatelligent’s comprehensive solutions empower universities to develop and implement these strategies, driving continuous improvement and academic excellence.

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How Education Tech Companies Enhance Student’s Success

Higher Education Tech Companies
Higher Education Tech Companies

In today’s educational landscape, achieving students’ success is more crucial than ever. Education Tech Companies like Datatelligent, specialize in helping universities manage their data to improve student outcomes. By using advanced technology, we enable institutions to streamline operations, boost academic performance, and make informed decisions that lead to greater student success.

The Role of Education Tech Companies in Students Success

Education tech companies like Datatelligent provide innovative solutions to improve students’ success. Let’s explore how we contribute to this goal.

What is Student Success?

Students success means helping students achieve their academic goals, personal growth, and career readiness. It involves giving students the resources and support they need to thrive in their studies and future careers.

Why is Students Success Important?

Focusing on students success benefits both students and universities. It leads to higher graduation rates, better job placements, and a positive reputation for the institution. Effective data management plays a crucial role in achieving these outcomes.

How Datatelligent Supports Students Success

Partnering with Datatelligent offers numerous advantages for universities aiming to enhance students success. Here’s how we help:

Improved Data Accuracy

Accurate data is essential for tracking student progress and identifying areas where support is needed. Our automated data management systems reduce human error, ensuring reliable data that universities can trust.

Enhanced Decision-Making

Our advanced analytics tools provide actionable insights. Universities can make informed decisions based on real-time data, whether it’s adjusting academic programs, improving student services, or identifying at-risk students.

Increased Efficiency

Universities handle numerous administrative tasks that can divert attention from student support. By automating routine tasks and streamlining processes, we help universities save time and resources. This allows staff to focus more on initiatives that directly impact students success.

Targeted Support and Interventions

Data-driven insights help universities identify at-risk students and tailor support programs to their needs. By understanding the data, universities can provide targeted interventions, ensuring that every student has the opportunity to succeed.

Datatelligent: Your Partner in Achieving Students Success

At Datatelligent, we are committed to helping universities harness the power of their data to promote students’ success. Our tailored solutions address the unique needs of each institution. Here’s what we offer:

Data Integration and Management

We integrate various data sources to create a unified, accessible data platform. This ensures all your data is in one place, easy to access and manage.

Advanced Analytics

Our predictive analytics tools provide actionable insights. By analyzing historical data and identifying trends, we help universities plan for the future and make data-driven decisions that enhance students’ success.

Data Security

Ensuring that all data is securely stored and compliant with regulatory standards is a top priority. We implement robust security measures to protect sensitive information and ensure compliance with regulations.

Tailored Solutions

Every university is unique, and so are their data needs. We work closely with each institution to understand their specific challenges and provide customized solutions. Whether it’s improving data accuracy, enhancing decision-making, or increasing efficiency, we have the expertise and technology to help.

Success Stories: How Datatelligent Has Made a Difference

University A

University A struggled with managing student records and tracking academic performance. By partnering with Datatelligent, they integrated their data sources, automated data management processes, and gained valuable insights into student performance. This led to more targeted support for students and improved academic outcomes.

University B

University B faced challenges with providing targeted support to at-risk students. Our advanced analytics tools provided the data they needed to identify at-risk students and develop intervention programs. This resulted in higher retention rates and better student outcomes.

University C

University C needed to enhance their career readiness programs. By providing robust data sets and advanced analytics tools, we helped them track student progress and align their programs with job market demands. This improved job placement rates and student satisfaction.

Conclusion

As the education sector continues to evolve, partnering with education tech companies like Datatelligent can make a significant difference in achieving student succes. By improving data accuracy, enhancing decision-making, increasing efficiency, and promoting better student outcomes, Datatelligent is your ideal partner in fostering students success.

Let us help you unlock the full potential of your university’s data to achieve greater performance and success. Contact Datatelligent today to learn more about how we can support your institution in promoting students success and navigating the complexities of data management and academic planning.

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Blog Higher Education

University Research Partners: A New Era of Data-Driven Decision Making 📈

University Research Partners
University Research Partners

In today’s rapidly evolving higher education landscape, universities are increasingly seeking partnerships to leverage data for better insights and decision-making. These collaborations, known as University Research Partners, can take several forms, each with unique benefits for the institution. 🤝

What is a University Research Partner?

University Research Partners are organizations that collaborates with an educational institution on research initiatives. These partners can range from other academic institutions to industry leaders and data analytics companies.

    • External Focus: Some partners work with universities to conduct case studies within real-world industries. This offers students valuable hands-on experience and exposure to current industry practices 💼, while providing the partner with fresh perspectives and research findings.

    • Internal Focus: Other partners specialize in analyzing a university’s internal data. This includes student performance, enrollment trends, faculty productivity, and resource utilization. By uncovering patterns and insights within this data 🔍, these partners help universities optimize operations, improve student outcomes, and make informed strategic decisions.

Datatelligent: Leading the Way in University Data Analytics 🚀

Datatelligent has positioned itself as a premier research partner for universities seeking to harness the power of their internal data. We offer a comprehensive solution that leverages existing learning management systems (LMS) like Canvas, Moodle, or Blackboard, as well as other data sources within the university ecosystem.

Our Approach:

    1. Data Integration: We seamlessly integrate with your LMS and other platforms to gather comprehensive data on student engagement, course performance, and faculty interactions.

    1. Data Warehousing: We utilize cutting-edge Snowflake technology to store and manage your data securely and efficiently. This scalable data warehouse provides a solid foundation for in-depth analysis and reporting.

    1. Data Visualization: We employ powerful visualization tools to transform raw data into actionable insights. Our custom solutions allow you to easily monitor key metrics, identify trends, and make data-driven decisions. 📊

    1. Machine Learning: We leverage advanced machine learning models to uncover hidden patterns and correlations within your data. This enables us to predict student outcomes, identify at-risk students, and personalize learning experiences.

Benefits for Universities:

    • Improved Student Success: Identify and address challenges early on, leading to higher retention rates and graduation rates.🎓

    • Enhanced Faculty Effectiveness: Provide faculty with insights into student performance and engagement, enabling them to refine their teaching methods. 👩‍🏫

    • Data-Driven Decision Making: Equip administrators with comprehensive data to inform strategic planning and resource allocation.

    • Competitive Advantage: Stay ahead of the curve by leveraging data to drive innovation and continuously improve.

The Future of University Research Partnerships

As the importance of data in higher education continues to grow, so too will the role of university research partners like Datatelligent. By partnering with us, universities can unlock the full potential of their data, drive meaningful change, and create a brighter future for their students and faculty. ✨

Ready to learn more? Contact Datatelligent today to schedule a consultation and discover how we can help your university thrive in the data-driven age.

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AI Events & Webinars Higher Education Insights Student Retention Students at Risk

Demystifying AI: Practical Ways to Get Started with AI in Data Analytics

DEMYSTIFYING AI: PRACTICAL WAYS TO GET STARTED WITH AI IN DATA ANALYTICS – 7.24.24 @ 2:00 pm CT

Our recent survey shows a lot of interest in AI, but organizations have not progressed beyond the Novice level of implementing AI in data analytics. 

As with any new technology, while there is a lot of potential value, it can be difficult to know where to start. 

In this informative webinar, hear real-world examples from others who are implementing AI at their institutions and get some practical tips on how to get started and be successful with AI.

Attendees will learn about:

  • The current state of AI in Higher Education
  • Key requirements for AI success
  • Lessons from an AI POC at UAB and Cornell College
  • Examples of AI use cases
  • Five steps to getting started with AI

Event Details

Featured Speakers:

  • Scott Sorenson, AVP, Data Operations and Business Transformation, University of Alabama Birmingham
  • Jodi Schafer, Senior Director, Berry Career Institute, Cornell College

Event Title: Demystifying AI: Practical Ways to Get Started with AI in Data Analytics

Date / Time: July 24, 2024, from 2:00 to 3:00 pm CT

Location: Zoom meeting

Register Today!
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Blog Higher Education Industry Snowflake

AIR Forum 2024: Insights and Takeaways

AIR Forum 2024 Insights and Takeaways
AIR Forum 2024 Insights and Takeaways

AIR Forum 2024: Insights and Takeaways

INTRODUCTION

The AIR Forum 2024 was a resounding success, bringing together professionals from the field of higher education analytics. As we engaged with attendees, several key themes emerged, shedding light on the current landscape and future trends in data analytics for higher education.

KEY TAKEAWAYS
  1. Carnegie Mellon’s Data Lake
    1. The buzz around Carnegie Mellon University’s presentation was exciting! Attendees couldn’t stop discussing their innovative approach to data analytics. Specifically, they highlighted using Snowflake, a centralized data lake, to unify disparate data sources. This approach resonated strongly with our own Datatelligent Platform for Higher Education. Clearly, there’s a growing need for data-informed decision-making in educational institutions.
  2. AI Awareness vs. Implementation
    1. While everyone acknowledges the potential of artificial intelligence (AI), practical implementation remains cautious. Attendees expressed a desire to leverage existing data and tools effectively rather than diving headlong into AI solutions. Our recent survey on data analytics in higher education confirmed this trend; awareness and interest in AI are high, but adoption remains gradual.
  3. Balancing Choices, Costs, and Flexibility
    1. The data analytics landscape offers an array of solutions, but institutions grapple with trade-offs. Budget constraints drive the need for cost-effective options, while flexibility is crucial for accommodating future growth. Striking the right balance between affordability and scalability is a priority.
CONCLUSION

The AIR Forum 2024 underscored the importance of data-informed decision-making in higher education. As we navigate this dynamic field, let’s continue to explore innovative solutions, collaborate, and adapt to meet our institutions’ evolving needs.

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Unified Cloud Data Platform in Just 90-Days

Setting Up a Unified Data Platform in 90-Days
Setting Up a Unified Data Platform in 90-Days

Unified Cloud Data Platform in Just 90-Days

INTRODUCTION

In today’s data-informed landscape, educational institutions face a dual challenge. They must manage vast amounts of information while ensuring seamless access and security. The promise of a unified cloud data platform—a centralized hub for data storage, processing, and analytics—holds immense potential. But can it truly be deployed within a tight 90-day window?

This article delves into the intricacies of integrating a unified cloud data platform specifically tailored for higher education. We’ll explore the critical components, address common roadblocks, and provide a roadmap to success. IT administrators, data scientists, and academic leaders must understand the nuances of this transformational journey to ensure a successful implementation.

So, fasten your seatbelt as we embark on a 90-day adventure—a sprint toward data unification that promises efficiency, insights, and a competitive edge. Let’s explore how proper planning, strategic execution, and collaboration can make this ambitious goal a reality.

ASSESS AND PLAN

First, meet with the key academic, administrative, and IT stakeholders and rank-order their priorities, needs, and desired outcomes. For example, one goal may be to improve student retention by 15%. You would then determine the data and data sets required to track each student’s retention.

SPONSORSHIP FROM THE LEADERSHIP AND FUNDING

Once the priorities and desired outcomes have been determined (e.g., improved student retention, analysis of the admission funnel to improve enrollment, a better understanding of enrollment, prediction of when a faculty member or advisor should engage with an at-risk student, etc.), sponsorship will be a critical success factor in this initiative. Most data initiatives fail partly due to a lack of leadership support; enlisting operational leaders to champion the project will help smooth over any obstacles you may face during the project, including obtaining the necessary funds. After you secure funding for the 90-day project, consider requesting funding for the nine months remaining in the year to develop the analytic solutions that will deliver the desired outcomes. Obtaining funding for the full 12 months is ideal to avoid going back to the well for additional dollars.

SET UP THE DATA PIPELINES AND THE CLOUD DATA PLATFORM
Next, select the tools and technologies needed to integrate the data and build the data platform. For data pipeline tools, consider Azure Data Factory and Logic Apps, which work well with student information systems (SIS) platforms such as Banner, Jenzabar, Workday, Colleague, Slate, and PowerFAIDS. These tools are also compatible with learning management systems (LMS) like Canvas, Blackboard, and Moodle, and data stored in operational data stores (ODS), Excel, and SharePoint. These platforms accommodate diverse data sources, including dining hall swipe data, to determine if students are socially connected. Third-party sources such as National Student Clearinghouse, IPEDS, student surveys, faculty evaluations, Google Analytics, and social data for recruitment channel analysis can also be integrated.
 
The number of data sources is not limited, but keep in mind that the goal is to have the data lake live in 90 days, so you will want to limit the number of data sources in this initial 90-day period.
 
For the cloud data platform, consider Snowflake. It works great with Tableau and Power BI because you can get insights from data sets of all sizes. Additionally, Snowflake’s pay-as-you-go model means you only pay for the storage and compute that you use, making it very cost-effective compared to traditional data warehouses.
 
SET UP THE DATA LAKE IN THE CLOUD PLATFORM

Once the tools are connected, set up the data lake in the cloud data platform. To meet your 90-day goal and desired outcomes, take only the necessary tables from the SIS, LMS, CRM, etc., to deliver the desired analytic outcomes. Once the data is in the data lake, you can now perform data transformations, creating the datasets that will drive your analytic solutions.

RESULTS, VALUES, AND ACCEPTANCE

As you approach the 90-day initiative’s conclusion, reconnecting with the stakeholders and leadership to share the results is crucial. Here’s a summary of the key achievements:

  • Successful Setup
    • Data Pipelines: Establish robust data pipelines.
    • Cloud Data Platform: Implemented a scalable cloud data platform.
    • Data Lake: Created a centralized data lake.
  • Data Integration:
    • Connected 2-3 key data sources,
    • Configured data pipelines to automatically refresh the data lake regularly.
  • Centralized Repository:
    • Developed a single data lake repository for the centralization and collection of data.
  • Preparation for Analytics:
    • Prepared datasets with predefined key metrics that will automatically feed into analytics solutions in the next phase (e.g., admissions funnel, enrollment trends, at-risk students, student success, etc.) running in Tableau or Power BI.

Sharing these accomplishments not only highlights the progress made but also sets the stage for the next phase of development. This will ensure continued momentum and support from leadership and stakeholders.

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Blog Higher Education Industry

Top Data Challenges in Higher Education

Top Data Challenges in Higher Education
Top Data Challenges in Higher Education

Top Data Challenges in Higher Education

INTRODUCTION

I’ve been in my current position at Datatelligent for a little over a year as a business development representative and have talked to many different leaders in higher education. My job is to hear the data challenges that individuals might be facing and discover strategies and solutions for institutions to turn these challenges into strengths. I’ve sat in hours of meetings, webinars, and speeches. Also, I have listened to Directors of Institutional Research, Directors of Institutional Effectiveness, and CIOs spill their challenges to me and strategize what steps they need to take to put a plan in place to improve their data maturity. From my discoveries, I’ll provide the top three data challenges currently in Higher Education for 2024. Also, I want to give some tips on how to avoid these challenges based on what I’ve learned.

DATA SILOS

For one thing, if you’re currently involved in higher education or have been in the past, I’m sure you experienced data silos or have heard from fellow peers the headache it can cause daily. Here are some of the headaches:

  • Fragmented Decision-making: Data silos hinder collaboration and lead to fragmented decision-making within institutions.
  • Inefficient Reporting: Siloed data is crucial for generating accurate reports, but it is time-consuming and error-prone.
  • Personalization Obstacles: Integrated data is crucial for personalized student experiences, but silos prevent the practical tailoring of services.
  • Strategic Implications: Addressing data silos requires breaking down barriers, investing in infrastructure, and fostering a data-driven culture.

In 2024, we want our day-to-day operation to go smoothly and get all the data we need at our fingertips. Data silos have been throwing a wrench in this for a long time and are a top three challenge, I hear.

DATA SECURITY AND PRIVACY
Equally as crucial as siloed data, data security and privacy are critical aspects of higher education. As institutions collect and manage vast amounts of student and organizational data, safeguarding this information becomes paramount. Cyber threats can put a lot of stress on schools in order to protect information from being stolen. Data security involves safeguarding institutional assets through access controls, encryption, firewalls, and regular audits. On the other hand, data privacy ensures confidentiality and compliance with regulations like GDPR and FERPA. Transparency and ethical handling are key—like sealing letters in envelopes and treating data responsibly. Together, data security and privacy create a well-guarded digital library, allowing students, faculty, and staff to learn and collaborate without fear.
 
TURNING DATA INTO ACTION

Lastly, you collect all the data you need, but using it effectively is another challenge. Many schools fail to transform the data into meaningful actions that drive positive outcomes. It requires defining clear objectives, selecting the right analytic tools, and translating insights into actionable steps. Balancing ethical considerations and fostering a data-driven culture are essential for success. Turning data into action is mentioned when talking to many individuals in higher education who don’t know the correct steps to take.

HOW CAN I AVOID THESE?

As I’ve mentioned, I have listened to countless meetings and read about many possible solutions for these challenges. Some things I recommend for becoming a more data-informed institution are:

  • Consolidate Data: Bring together data from disparate tools and datasets into a central data warehouse with good reporting tools. We at Datatelligent can help with this and recommend using a cloud-based data warehouse called Snowflake. Snowflake has great elastic scalability, robust security features, and seamless integration with popular BI tools and data services. This allows institutions to gain a more holistic view of learning processes and support mechanisms. How universities can break down data silos and generate new insights | THE Campus Learn, Share, Connect (timeshighereducation.com)
  • Advanced Reporting Tools: Advanced reporting tools like Tableau and Power BI can be beneficial for summarizing, visualizing, and comparing data. These tools provide better insights than standard tabular reports. At Datatelligent, we can help with this by having our own Datatelligent Platform for Higher Education that can consolidate data and provide data visualization tools like Tableau and Power BI.
  • Privacy Offices: Establish privacy offices and full-time privacy positions within institutions. Develop and improve privacy and practices.
  • Compliance Management: Manage Compliance across campus operations by understanding and adhering to privacy legislation and regulations.
  • Data-Driven Thinking: Leverage data analytics by encouraging data-driven thinking. Areas where data analytics can be beneficial include personalized learning experiences, academic analytics, and critical care assessments. Towards Evidence-Based, Data-Driven Thinking in Higher Education | SpringerLink
  • Optimize Data Strategy: Focus on data governance, create data leadership, establish actionable data strategies, utilize a cloud data platform to centralize data, create an analytics team, and implement data visualization tools like Power BI and Tableau.
CITATIONS:
  1. Burns, Sean. “The Evolving Landscape of Data Privacy in Higher Education.” Educause, November 19, 2020. https://www.educause.edu/ecar/research-publications/the-evolving-landscape-of-data-privacy-in-higher-education/introduction
  2. Komljenovic, Janja. “The future of value in digitalized higher education: why data privacy should not be our biggest concern.”  Springer Link, November 19, 2020. https://link.springer.com/article/10.1007/s10734-020-00639-7
  3. Gibson, David. “Big Data in Higher Education: Research Methods and Analytics Supporting the Learning Journey.” Springer Link, July 5, 2017. https://link.springer.com/article/10.1007/s10758-017-9331-2
  4. Florea, Diana and Florea, Silvia.  “Big Data and the Ethical Implications of Data Privacy in Higher Education Research.” MDPI, October 21, 2020. https://www.mdpi.com/2071-1050/12/20/8744
  5. Times Higher Eduation. “Five actions for data-led transformation in Higher Education.” https://www.timeshighereducation.com/hub/p/five-actions-data-led-transformation-higher-education
  6. Masterson, Douglas, PhD, Davis, Christopher M., PhD, and Carbonaro, Suzanne, MEd. “Transforming Data into Meaningful Information.” The Society for College and University Planning, Jan-Mar 2023. https://www.scup.org/resource/journal-transforming-data-into-meaningful-information/
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