Business Intelligence, also BI, refers to any set of processes that seeks to transform raw data into actionable insights. Although, most schools are reluctant to engage in BI procedures, citing a lack of relevance.
Decision-makers, these days, are starting to have a change of heart. It’s getting progressively clearer that classic approaches to teaching are no longer adequate, and a more Data-Driven solution is now necessary. Rather than engaging a brute force approach, a quick, effective dive into available data can reveal useful information that maximizes teaching effectiveness.
Business Intelligence tools and procedures come in handy for everything from admissions to optimizing classroom scheduling to even improving student success.
What is Business Intelligence?
Business intelligence refers to well-defined procedures that extend over data collection, analysis of the collected raw data, and ultimate transformation into consumable insights for appropriate shareholders.
Simply, BI seeks to optimize operational flows and improve on the existing models in place. In addition to newly-emerging concepts like artificial intelligence in education, BI is arguably one of the foremost methodologies that seek to enhance the educational landscape. A BI and analytics initiative enables administrators to access constant reporting, and meet reporting requirements.
Contrary to popular opinion, BI reports do not predict an activity’s outcomes or provide definite information about what might happen. Instead, analytics experts affirm that they allow shareholders and other information consumers to easily dig into data to extract information about past trends. BI banks heavily on Software tools to render the information-digging process seamless and smooth.
Using Data Warehouses
Though many seem unaware, educational systems typically store a huge amount of relevant data. Score tables like test scores and overall grades are all useful raw data that could be banked on to develop a relevant model. Such procedures enable educational institutions to foster a broad culture of data-driven decision-making.
More often than not, the aggregate of all that raw information can match up to the warehouses of even a Fortune 500 company.
“However, improper storage, curation, or data processing can lead to all the raw information being under-utilized or inexpertly used. Not only do most key shareholders in an educational system fail to understand the significance of such metrics they’ve stored, but they are also almost always unsuccessful at utilizing them,” affirms Richard Loch, a Business Intelligence expert at PapersOwl. A bit of this failure can be attributed to the non-organized and indeliberate data collection. Nothing renders analysis processes ineffective quicker than the decentralization of potentially usable data.
It’s not unusual to find useful raw information such as school enrollment stats stored in warehouses well removed from the systems that house other relevant metrics such as examination records, typically stored by teachers or other staff members on a needed retention basis to enhance curriculum delivery and identify trends.
Major shareholders and end users usually fail to connect the dots between disparate data. Most Analytics experts typically recommend the adoption of data warehouses at this stage. Data warehouses provide mediums to store data in a way that enhances the quick and efficient processing of complex datasets.
However, safeguards should be placed appropriately to prevent the insights gathered from being employed in nefarious capacities. Such safeguards are adequately detailed in a range of business ethics essay that may come in handy. For an educational institution, that would mean that crucial shareholders would have accessibility to all the metrics they’ve gathered over the years in one spot as opposed to its physical storage in several. That would mean they could obtain the enrollment records, examination scores, and the likes in a matter of seconds and ultimately educate young minds and reduce management complexity.
Better Reporting and Data Visibility
Raw data on its own is insufficient in getting the key shareholders to do a valuable dive into their gathered data, which is exactly what necessitated the introduction of analysis principles in the first place. Gleaned insights should be presented to decision-makers to boost the analytics process’s success and enhance their understanding of the query made.
It’s quite easy to decide when information is presented visually appealing. To deliver helpful insights in a way that encompasses and banks on available data, it’s always essential to advance the level of data visibility. Nevertheless, the volume of raw info gathered on a district level, such as budgets and the specific annual report, further adds an extra difficulty to carrying this out.
As such, a viable and powerful solution still remains in the implementation of data warehouses. Gathering all pertinent raw info in a central spot enhances the effectiveness of BI procedures and produces clearer and more accurate dashboards. Those can be banked on to generate insights into education systems, like universities and high schools, and ultimately progress the atypical student performance in such institutions.
Data-Driven Decision Making
Should business analytics processes be run on an institution’s data set, a typical educational organization could get more efficient at maximizing its available resources – typically time and workforce. Such measures usually enhance academic performance to a small extent.
For example, exploratory analysis carried out on data gathered in a warehouse can provide valuable insights into which teachers are most effective at maximizing the grades of groups of students in a particular subject. Such processes aid in increasing the results and benefits colleges gain from their data. BI also allows school administrators to make data-driven decisions based on objective evidence.
To enhance data visibility and develop good insights from collected data, it’s vital that any organization, not excluding educational institutions, leverage on the concept of data warehouses. Such storage facilities allow for the centralization of collected data in one spot leading to preferable models developed and even more accurate insights gleaned. To deploy such successfully, the key is to start small.
Another important consideration is improving the User Interface medium employed to deliver insights to decision-makers. As humans are more visual beings, a great way to enhance the processing of provided insights best by untrained shareholders would be to provide them in such a way that they’re pretty easy to catch up on.