Data Cleaning Techniques: Fool-Proof Techniques for Cleaning Your Data

Data Cleaning Techniques: Fool-Proof Techniques for Cleaning Your Data

Your marketing campaigns really are only as good as your data. Working with “unclean” data can cause you all sorts of difficulties.

We recently discussed whether or not data cleaning is actually important (quick answer: it’s absolutely essential!) and with that in mind, today we’re going to discuss the fool-proof techniques you need to know for cleaning your data.

Here are the key fool-proof techniques for cleaning your data:

– Perform an initial audit
– Remove irrelevant & incorrect data
– Remove duplicate data
– Standardise data formatting and modify all entries
– Post-cleansing review

Let’s have a look at all 5 techniques in more detail. By the end of this blog post, you’ll have all the knowledge you need to go away and clean up your data!

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    Data Cleaning Techniques #1: Perform an Initial Audit

    Before anything else, you must perform an audit. The initial audit is arguably the most important step in the data cleansing process, because it helps you to put a plan in place.

    In this stage, you will assess what type of data you’ll be keeping and what you’ll be getting rid of. Furthermore, you’ll decide on how you are going to standardise the formatting. You’ll also set timescales – the scariest part!

    Data Cleaning Techniques #2: Remove Irrelevant and Incorrect Data

    In the initial audit, you should have made a decision on what type of data you’re wanting to keep. At this stage, you will remove the irrelevant data that isn’t of any value to your business anymore.

    Furthermore, you will want to remove any data entries that are simply incorrect. For example, old information that you know isn’t correct, or data that just doesn’t make sense.

    Data Cleaning Techniques #3: Remove Duplicate Data

    If you have irrelevant and incorrect data, it’s likely that you also have duplicate entries. Prior to standardising the data formatting and modifying all the records, it’s a wise idea to remove any duplicates.

    Duplicate data entries just inflate your numbers unnecessarily, which might result in your marketing predictions being wide of the mark. So, remove any duplicate data and then move onto step #4!

    Data Cleaning Techniques #4: Standardise Data Formatting and Modify All Entries

    Now you’ve removed irrelevant, incorrect, and duplicate data records, you can standardise your data formatting and modify all of the remaining entries.

    Data entries should be uniform. For example, if you have a database of names and date of births, they should all be formatted in the same way. For instance, you shouldn’t have one record saying Mr John Doe and another saying Doe, John. Every record should be formatted in exactly the same way.

    Data Cleaning Techniques #5: Post-Cleansing Review

    You’ve reached the end of the data cleansing process! Well done!

    Finally, you must complete a post-cleansing review. Ensure you’re happy with the formatting and double check that all records are relevant and so on. At this point, you should create a schedule for regular data cleaning sessions.

    Now, these 5 steps might make data cleansing sound like an easy process. Unfortunately, it isn’t as easy as it sounds. Data cleaning can be a long, tiring, and time-consuming process. If you can’t commit to performing the data cleansing correctly, please feel free to get in touch. We’d be more than happy to discuss how we can help your business.

    Let us be your business partner, helping you to increase your sales!