When doing data cleaning, it is important to make sure you follow a few simple rules to make sure you not only minimize the risk of data cleansing but also maximize the effort. Here are the top ten rules to remember for your data cleansing project:

  1. Create a data cleaning plan – Before you start data cleaning establish what is your main issue and what your objective is. It could be that it is too many duplicates, your data is outdated, you are missing necessary data, or your data is in a format that you cannot use for your marketing, analysis and sales. Your data cleaning plan should consists of timelines, objections and priorities. At StrategicDB a data cleansing company, a free data audit is given so you can establish your data cleaning priority and identify key issues with your data.
  2. Back Up Your Data – This is probably the most important rule in any data manipulation but especially true for data cleaning. As no process is 100% accurate, you may need to revert back to your original data. Prior to beginning to make live system changes it is a good idea to back up your data.
  3. Identify root cause of your data issue – prior to cleaning it is ideal to identify the source of bad data, duplicates and so on. If you clean before you identify the issue, you will be cleaning on a yearly basis and never be done! This is where a good data quality analyst will come in handy. If you are missing information that can help identify the source of your bad data, implement a strategy to capture this data so you can monitor it in the future. Otherwise, fix the issue so it does not happen in the future. Common sources of bad data includes: form submits, 3rd party data purchases that are not standardized prior to uploading it to the system, sales reps who do not input complete information and historical data which no one has touched in ages.
  4. Communicate with all teams involved – Prior to beginning your data cleansing, notify all the people involved with the data so they are aware of the project. This is key, as you maybe not be aware of key business rules that may impact your data cleaning rules.
  5. Come up with business rules – Business rules are key when doing data cleansing. For de-duping, each company defines duplicates differently so make sure everyone is on the same page. For data standardization/normalization make sure that the hierarchies, categories or formats are discussed in advanced to avoid having to redo it in the future.

Once you have created a plan, come up with your business rules, communicated your plans with everyone involved, backed up your data and identified root causes of your bad data you can begin your data cleaning project. Remember, that good planning in the beginning of the data cleaning initiative can save you time and money down the line.

If you are looking for data cleaning services, StrategicDB offers a free data audit report.