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The Importance of AI-Powered Analytics in Higher Education

The Importance of AI-Powered Analytics in Higher Education

The future of AI is now

At Datatelligent, we look to the future for ways to help our customers solve decades-old Higher Education problems. We hear a lot of questions lately about AI and what it means for Institutional Research. Questions like, “How can Generative AI and Large Language Models help our analytics? Will adding AI extract the predictive insights we need to help students and help us with retention, recruitment, and funding?”

Well, it’s funny you should ask. On November 15, 2023, we are hosting a webinar on these very topics with our most AI-innovative partner, Snowflake. Elevate Education: AI Solutions for Higher Education.

Snowflake is moving fast, at Chicago-blizzard pace, embracing all that’s AI and announcing earlier this month, during Snowday, a host of new AI tools.  We will in turn innovate with our Higher Education customers and implement these tools into the Datatelligent Unified Data Platform.

The Definition of AI in Higher Education

AI-powered analytics is the use of artificial intelligence to analyze large datasets to identify patterns, trends, and insights. Here are some of the areas will innovate with AI-powered analytics with our higher education customers:

  • Student success: AI-powered analytics can be used to identify students who are at risk of dropping out or failing a course. This information can then be used to provide targeted interventions, such as tutoring or academic advising.
  • Student Recruitment and Enrollment: considered one of the holy grails of analytics, identify the best mix of students who will benefit and are succeed from the specialties offered by the institution. Closely related, AI can help identify so you can focus recruitment on the students that will help your institution win and retain their grant funding.
  • Enrollment Trends: Identifying the trends early that will impact future enrollment. Linking to all sorts of internal and external data sources, AI-powered insights helps plan for student recruitment in fast-changing demographics.
  • Faculty Planning: Recruitment doesn’t stop with students. AI can help with faculty planning, identifying the educational specialties that are in demand now and in the future. Recruitment efforts and education certifications can be planned years in advance.
  • Personalized learning: Personalized learning experiences can be created for students using insights from AI-powered data. This can be done by adapting course materials, providing individualized feedback, and recommending additional resources.
  • Administrative efficiency: Why not have that AI-bot be the helpful assistant it wants to be, automating scheduling, grading, and admissions processing? This can free up time for faculty and staff to focus on more strategic initiatives.
The Challenges of AI

Of course, AI is not the magic pill to make all our analytic and Institutional Research headaches go away. At Datatelligent, we help mitigate the challenges AI-powered analytics brings to higher education:

  • Data quality: AI-powered analytics immediately bring up Data Quality.  Institutions need to ensure the data is accurate, complete, and consistent, or your “insights” will be none of these.
  • Bias: AI algorithms can be biased, which can lead to unfair or inaccurate results. Data Analysts need to be aware of the potential for bias and make sure a human takes steps to mitigate it.
  • Ethics: The use of AI in higher education raises a number of ethical concerns, such as the potential for surveillance and discrimination. Institutions need to develop clear ethical guidelines for the use of AI in higher education. At Datatelligent, we have a well-developed AI Governance and Ethics framework.

Overall, AI-powered analytics has the potential to revolutionize higher education. As with any revolution there are always challenges, which is why it’s best to align with an ally before overthrowing any king. We’ll be talking about the AI Revolution on November 15. We hope to see you at the Datatelligent and Snowflake AI Solutions for Higher Education webinar.

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Empowering Faith-Based Organizations with Data: How Tableau and Snowflake can Increase Data Maturity

Empowering Faith-Based Organizations with Data: How Tableau and Snowflake can Increase Data Maturity

Faith-based organizations play a significant role in communities all around the world. These organizations have unique challenges when it comes to data management and analysis, as they often rely on volunteers and need more resources. However, modern tools such as Tableau and Snowflake can help faith-based organizations increase their data maturity and make more informed decisions.

Tableau is a data visualization tool that allows organizations to create interactive and engaging data visualizations. On the other hand, Snowflake is a cloud-based data warehouse that provides a secure and scalable platform for storing and analyzing data. Faith-based organizations can use these tools together to gain insights into their operations and make data-driven decisions.

Here are a few ways that faith-based organizations can use Tableau and Snowflake to increase their data maturity:

  1. Track and analyze donations: One of the most critical aspects of any faith-based organization is donations. With Tableau and Snowflake, organizations can track and analyze donations over time to understand trends and patterns. They can create dashboards that show how much money they have received, where it came from, and how it was used. This can help them make more informed decisions about fundraising and budgeting.
  2. Monitor participation: Faith-based organizations rely on attendance and engagement to gauge the effectiveness of their programs. With Tableau and Snowflake, organizations can track attendance and engagement metrics over time. They can create dashboards that show how many people attended each event, how engaged they were, and how long they stayed. This can help them identify which programs are most effective and where they need to make improvements.
  3. Monitor volunteer engagement: Volunteers are a critical part of many faith-based organizations, and it can be challenging to track their recruitment, training, assignments, and recognition. Tableau and Snowflake can help organizations evaluate volunteer performance by tracking hours worked, tasks completed, and opportunities for volunteer training or recognition. Data-driven volunteer management helps direct attention to the volunteers who might need additional support.
  4. Analyze program effectiveness: Faith-based organizations run a variety of programs, from education and outreach to charity and support services. With Tableau and Snowflake, organizations can analyze the effectiveness of these programs by tracking metrics such as program attendance, participant feedback, and outcomes for service recipients. This can help organizations identify which programs are most effective and where to improve.
  5. Monitor and improve operations: Like any organization, faith-based organizations have operational challenges that can be difficult to manage. With Tableau and Snowflake, organizations can track operational metrics such as budget, staff time, and inventory. They can create dashboards that show how these metrics change over time, identify areas of concern, and make data-driven decisions to improve operations.

Tableau and Snowflake are powerful tools that can help faith-based organizations increase their data maturity and make more informed decisions. Faith-based organizations can gain insights into their operations and make data-driven decisions by tracking donations, attendance, volunteer performance, program effectiveness, and operational metrics. With the right tools and strategies, faith-based organizations can use data to improve their programs and services and positively impact their communities.

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This article highlights the profound influence of generative and predictive AI on higher education. It discusses how these technologies are streamlining administrative tasks, enhancing student success through early interventions, and improving overall satisfaction for both students and faculty. Institutions are leveraging AI for better decision-making, personalized learning experiences, and optimized course offerings, all of which contribute to a more efficient and effective educational environment.

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