Using Our Data Systems

Excel is a well-known Microsoft software that is designed for basic data analysis, calculation, data visualization and identifying trends and patterns of data. This particular software can be used to download data in certain formats, and can use processes such as powerquery or pivot tables to sort/analyse data. Some of the elements that it’s know for are:

• • Data Management: Excel allows users, through formatting and formulas to organise and manipulate small datasets that don’t change or contain live data.

• • Data analysis: With it’s powerful formulas and functions, excel allows users to perform data analysis, identify trends and make informed decisions.

• • Data Visualisation: With charts, graphs, and pivot tables, Excel helps visualise data to uncover trends and patterns.

• • Numerical calculations: Excel has multiple formulas available to help with budgeting, forecasting and financial reporting. Although this does not replace University standard approaches for financial reporting, it can be useful for small budgeting.

If you are interested in using Excel to analyse data, Microsoft’s guidance can help you get started: Analyse Data in Excel (web | Microsoft Support).

Elements to consider with Excel:

While Excel is highly versatile, over-reliance (such as building work processes) on it can lead to significant issues:

• • Duplicate Data Sources: Teams may inadvertently create multiple versions of the same dataset, leading to inconsistencies and confusion between live and static data.

• • Single Points of Failure: Relying solely on Excel for critical processes can create vulnerabilities, as a single corrupted file or error can disrupt operations. Single points of failures can also come from individuals. If a system is set up and only one person understands how it works, can lead to challenges when these systems break.

• • Scalability Issues: Excel is not designed to handle extremely large datasets or complex data relationships, which can result in performance bottlenecks.

• • Lack of Collaboration: Excel’s file-based nature can hinder real-time collaboration and version control, especially in larger teams.

To mitigate these risks, we recommend that you use Excel to support your data analysis but NOT as a replacement or duplication of already available sources of data in the University Dashboards or OneUni. 

Microsoft Copilot is an AI-powered tool that can help you analyse data more efficiently. Copilot can be a good option for getting quick insights into your data, but results can vary and it is your responsibility to check the output of data. This can be achieved by uploading documentation in our secure University of Lincoln environment, which can include student data. As long as you are signed in to your university account, your data will not be saved outside of our University.

What Could You Use Copilot For?

Potential options include:

• • Data Summarisation: Quickly summarise large datasets to highlight key insights.

• • Data Visualisation: Create charts and graphs to visualise data trends and patterns.

• • Data Cleaning: Identify errors or inconsistencies in your data.

• • Statistical Analysis: Perform basic statistical analyses like averages, medians, and standard deviations.

• • Predictive Analysis: Use historical data to make predictions about future trends.

• • Automated Reporting: Generate reports based on your data.

Be mindful of what data you upload, respecting student and staff confidentiality. Always check any outputs for errors or ‘AI hallucinations’. Remember, Copilot enhanced data analysis is a quick starting point, and any outputs should be verified before use.

Use Cases:

Resource Allocation:

• • Analyse usage data to optimise the allocation of resources like classrooms and equipment.

• • Predict future resource needs based on historical data.

Survey Analysis:

• • Summarise responses from surveys to gather actionable insights.

• • Visualise survey results to communicate findings effectively.

Attendance Tracking:

• • Clean and analyse attendance data to monitor student engagement.

• • Predict attendance trends to plan for future academic terms.

Example Prompts:

• • “Summarise the average grades for each course.”

• • “Calculate the pass rate for each course.”

• • “Create a pie chart showing the allocation of lab equipment across departments.”

• • “Predict the future demand for library resources based on historical data.”

• • “Summarise the responses from the student satisfaction survey.”

• • “Analyse the feedback on online learning tools and present the findings.”

• • “Predict future attendance trends based on historical data.”

Tips:

• • Be Specific: The more specific your command, the better Copilot can assist you.

• Explore Features: Experiment with different commands or ask Copilot to give you three different responses to help inform your analysis and select the best response.

Power BI is a powerful business analytics tool that enables the creation of interactive visualisations of your data. However, it’s important to know when you would use PowerBI over Excel. Also please be aware that gaining access to PowerBI can incur additional licence fee costs and requires specialised skills to use effectively, as such if you have a project or idea to improve team efficiency by using PowerBI submit your idea to the Digital Services Ideas Portal for review and prioritisation: University of Lincoln Digital Services Ideas Portal (internal link).

PowerBI is suitable for:

Handling and cross-referencing – Power BI is able to manage, group and form relationships between several sets of data as well as analyse millions of rows of data efficiently. This enables it to find relationships in multiple data sets at once.

Advanced visualisations – PowerBI offers a variety of ways to visualize data and customize that output to include multiple data sets, filtering of data and interactive dashboard creations to make data a live experience.

Real-time data: PowerBI is designed to work directly with data directly from the source which can provide real-time updates rather than working with a fixed data set, this can be useful to ensure all outputs are up to date and reflect current data. PowerBI can also work with fixed data that doesn’t change. It’s important to note that not all data systems can connect with PowerBI.

Cloud-based sharing: Power bi enables you to share and publish dashboards and report which can be seen by others in the environment.

Enhanced interactivity: PowerBI enables you to interact with your data in much more intense ways by looking at filters, drill down features, bookmarking to help you explore data quicker.

AI capabilities: Some licenses of PowerBI can use AI features to help with data analysis.

Although PowerBI can be a useful piece of software, it’s important to be aware of some of the caveats or challenges that come with using it.

Challenges of Power BI:

Although Power BI can be a useful piece of software, it’s important to be aware of some of the caveats or challenges that come with using it.

Data integration – Different data sources use different formatting, which means merging and managing multiple data sources can be challenging to ensure they all work together.

Data quality – The accuracy and reliability of Power BI depends heavily on the quality of the data that’s gathered.

Licensing costs– The software costs the university based on the amount of licences that it has. This can be a significant financial challenge for each area and an identified need and understanding of the software should be thought about in advance of asking for a licence.

Learning curve – Even for the experience data analyst there is a steep learning curve for mastering the wider toolsets built into the software. This needs to be heavily considered if you are looking at a license.