There are 10 ways to keep your student data accurately clean and updated especially when it is your dream to intimate them with data management and data analytics. To communicate correctly with prospective students and make the right decisions out of all your data, it’s essential for you to have clean data.
Dirty data not only causes a storage headache, but it can also lead to inaccurate results and unwanted mistakes in your automated marketing strategy. Over time, businesses amass a significant amount of unnecessary data that must be updated to ensure its relevance and verified for accuracy and completeness.
Detecting any deficiencies can be accomplished using various reporting tools or spreadsheet software. Addressing these gaps will inevitably require human involvement, although artificial intelligence may offer some assistance to a certain extent.
Hence, data cleaning is the process of identifying and correcting errors, inconsistencies, and missing values in your data. This can improve accuracy, reliability, and usability of your data, making it easier to analyze and visualize. Moreover, data cleaning can help you avoid misleading or inaccurate conclusions, and ensure that your data meets ethical and legal standards.
Keeping Your Student Data Accurate, Clean, and Updated
So, back to the question, what are the 10 ways to keep your student data accurately clean and updated as a teacher in modern day academics? Here are some of the ways you can help your student create clean and accurate data:
Make Standards Out of Your Student Data
Be careful with automation and personalized messages. Be sure to standardize and set up properly your automated workflows to make sure your prospective student gets a unique application experience. Great personalization shows your students and prospects that you understand them, appreciate them and can talk to them as an individual and not as a number.
Many times than not, dirty data is caused by basic formatting issues. As the formats differ and run through a series of imports and exports, the data issues exponentially grow. Moreover, make sure to determine standards in the way you enter data.
Organize Your Student Data
If you choose to save data digitally, a district-level data-management application can assist you in collecting and organizing various types of learning and assessment data. Otherwise, look at the Google Classroom tools. Working with hard copies, printouts, and file folders are also decent options. Whatever method you use, try to use an identifier so you can find what you’re looking for later.
Secure Your Student Data By Digital Means
Millennials expect more from institutes than ever. Technology is dominating their world, and this is why institutes must adapt and embrace new technology that will help them stand out from the crowd in a highly competitive environment.
It’s no longer acceptable to ask a student to fill out a paper form, or for them to wait for weeks after an inquiry to get back to them, they expect everything to be digital, well presented, and instantaneous.
Scouting and Removing Errors
It probably goes without saying that you’ll need to carefully remove any errors from your data. Errors as avoidable as typos could lead to you missing out on key findings from your data. Some of these can be avoided with something as simple as a quick spell-check.
Spelling mistakes or extra punctuation in data like an email address could mean you miss out on communicating with your customers. It could also lead to you sending unwanted emails to people who didn’t sign up for them.
Add Context, Build Value for Your Student Data
Ensure that you have added context to your information. They can be as plain as where you met, demographics, family (relationships), or opinions, etc. In short, you need to feed your student data system as much information as you can get. This will help you deliver the right message to the right student at the right time through the right channel.
Get Rid of Duplicates from Your Student Data
When you collect your data from a range of different places, or scrape your data, it’s likely that you will have duplicated entries. These duplicates could originate from human error where the person inputting the data or filling out a form made a mistake.
Duplicates will inevitably skew your data and/or confuse your results. They can also just make the data hard to read when you want to visualize it, so it’s best to remove them right away.
Prioritize Your Student Data
Use data to incorporate a variety of ideas. Figuring out what you’re aiming for can help you choose the most helpful group of facts. Consider interim assessment results when creating teaching groups, for example. Examine your classroom tests and insights if you feel you may need to revisit a concept with your students.
Throw Open Your Questions on Your Student Data
Engage in honest discussions about student data with colleagues so that everyone can benefit from shared knowledge. “What leaps out to you in this data?” is an example of a question that can lead to a helpful discussion. Discuss methods for meeting students where they are. Or, if you’re feeling stuck, ask others for advice that has worked for them.
Maintain Mono-Language Translation
To have consistent data, you’ll want everything in the same language. The Natural Language Processing (NLP) models behind software used to analyze data are also predominantly monolingual, meaning they are not capable of processing multiple languages. So, you’ll need to translate everything into one language.
Convert Data Types
Numbers are the most common data type that you will need to convert when cleaning your data. Often numbers are imputed as text, however, in order to be processed, they need to appear as numerals. If they are appearing as text, they are classed as a string and your analysis algorithms cannot perform mathematical equations on them.
Benefits of Cleaning and Updating Your Student Data
Below are some of the few tips of importance which your student data cleaning and updating have:
Accuracy and Reliability
At the heart of any analysis or decision-making process lies data. Ensuring this data is accurate and reliable is paramount. Data cleaning techniques ensure that the information you’re working with is both trustworthy and actionable.
Efficiency
Clean data translates to efficient operations. Whether you’re running analytics, machine learning algorithms, or simple database queries, clean data ensures faster processing times and more accurate results.
Enhanced Decision-making
With clean data at your fingertips, decision-making becomes a more streamlined process. You can trust the insights derived from your data, leading to better and more informed decisions.
