Refresh Your Data This Spring
As the seasons change, many of us instinctively feel the urge to refresh our surroundings, decluttering and reorganising to bring a sense of order and renewal. This tradition of spring cleaning shouldn't just be limited to our homes - it’s a practice that can be equally transformative when applied to the digital environment of our organisations.
Just like a cluttered closet, a cluttered data system can lead to inefficiencies, confusion and missed opportunities. “Dirty” data, which can include outdated, irrelevant, duplicate or incorrect information, not only hampers your team's productivity but can also lead to costly errors and missed organisational opportunities. That’s why a periodic data spring clean is essential.
Just like a cluttered closet, a cluttered data system can lead to inefficiencies, confusion and missed opportunities.
Why Data Cleansing Matters
Imagine trying to make sense of a room filled with boxes of unsorted, mislabeled items. Now imagine trying to make data driven decisions based on inconsistent, duplicated or incomplete data. The frustration is similar. Clean data, however, provides clear insights that can drive better strategies, improve service delivery and support more effective programs.
Without regular data cleansing, social organisations risk making decisions based on flawed data, which can lead to inefficient resource allocation, inaccurate program development and even compliance issues. With growing regulatory scrutiny around data privacy and retention, maintaining clean data isn’t just a good practice - it’s often a legal necessity.
Two parts to the Spring Clean
To extend our analogy further, you can think of the Spring Clean at two levels:
‘Strategic’ Spring Clean - this is refreshing the ‘data system’ you use - and asking if you are collecting the right data and using this data for decisions. Do you have the right data systems? Protocols and data security? The right case management systems? The right Executive Data Lead with data roles and responsibilities?
‘Operational’ Spring Clean - this is the traditional data cleaning which is at the database level - improving quality and reliability of the data inside the databases that you use. You should have an annual process in place to keep your data clean, so you can rely on it when you make decisions.
This article focuses on the Operational Spring Clean, but if you want to explore a Strategic Spring Clean, get in touch with us for a chat.
Steps to Spring Clean Your Databases
You’ll need someone who understands your databases and has access and authority to make changes to do this next step. We find in many cases, the best way to manage this is to create a ‘data warehouse’ where you can integrate data from various sources inside your organisation and then manage and clean it in one place.
1. Eliminate Duplicate Data
Duplicates are more than just annoying - they’re costly. They can cause confusion, lead to erroneous reporting and waste valuable storage space. Start your data spring clean by identifying and removing duplicate records. This not only improves data accuracy but also streamlines your database, making it easier to manage.
2. Repair Incorrect Data
Misspelt names, incorrect contact information and inconsistent data formats can all contribute to a messy database. These small errors might seem trivial, but they can significantly impact client interactions and analytics. Take the time to correct these inaccuracies and standardise your data entry practices to prevent future errors.
3. Handle Missing Data
Missing data can be as problematic as incorrect data. Before filling in gaps or deleting incomplete records, analyse the missing information to understand why it’s missing. Sometimes, the absence of data can reveal important trends, such as client disengagement and referral intakes in certain questions or processes.
4. Remove Irrelevant Data
Not all data is valuable. Information that no longer serves your organisation’s goals or is no longer relevant should be removed. This step is crucial for ensuring that your team isn’t overwhelmed by unnecessary data and can focus on what truly matters.
5. Filter Outlying Data
Outliers - data points that don’t fit within the normal range - can distort analysis and lead to incorrect conclusions. However, before removing these outliers, it’s important to analyse them for potential insights. Sometimes, outliers can indicate emerging trends or new opportunities.
6. Validate and QA Data
The final step in your data spring clean is to validate and quality check your data. Ensure that the cleaned data is consistent, follows standardised formats and is ready for use in reporting and decision making. This step is critical to maintaining database integrity and ensuring that future data remains clean and useful.
Beyond Cleaning - Managing Data Retention and Anonymisation
Data spring cleaning isn’t just about ensuring accurate data - it’s also about how you manage data over time using a Data Retention Policy. With regulations like GDPR (in Europe) and Australia’s Privacy Act, organisations are required to handle personal data responsibly. This means not just cleaning up, but also ensuring that data is stored for appropriate lengths of time and that any unnecessary data is securely deleted or anonymised.
Anonymisation, for example, allows organisations to retain the value of data while removing personal identifiers, reducing the risk of data breaches and ensuring compliance with privacy laws. This is a process we use when we store and analyse data on behalf of our clients.
The Role of Technology in Data Cleaning
As with any spring cleaning task, the right tools can make the job much easier. Data management software can help automate many of the steps involved in a data spring clean, from identifying duplicates to ensuring that data entry follows standardised formats. Investing in these tools not only makes the process more efficient but also ensures that your data remains clean in the future.
Latitude Network’s Commitment to Clean Data
At Latitude Network, we understand and know the critical role that clean, accurate data plays in driving social impact. We are passionate about helping organisations use data to make better decisions, improve outcomes and maximise their impact. By committing to regular data spring cleans, you can ensure that your organisation’s data remains a powerful tool for positive change.
Whether you’re just beginning your data cleaning journey or looking to refine your processes, Latitude Network is here to support you every step of the way. Let’s work together to keep your data clean, accurate and ready to drive the impact your organisation strives to achieve.
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