A Step-wise Guide to the Process of Data Cleaning
Manual sorting is a cumbersome affair and takes a lot of time so, it is important to shift to data automation
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Data cleaning is a service which is an intricate task, it is complicated to maintain and most importantly complex to decide where to start from. The chances of formatting errors always lie when it comes to data curation and management. The complexities enter when the job comes to cleaning the data and maintaining a verified list of data, whether it is fetched from varied vendors or accumulated by the hard working employees or conjoined efforts of both. A teeny weeny mistake in feeding the data, or a typing mistake can screw your entire database and in turn your decision-making process. If you can arrive at the errors in the database, you would be saved from taking wrong decisions, but it would increase an entire bunch of workload for you. Ample hours would just be wasted in manually cleaning the data and rectifying the errors which could have been avoided. So, what is the way out of this time consuming and frustrating problem?
You just need to hire a data cleansing service and get your data brushed up. This will assist you in focusing on the areas where you are weak at and save your time and energy. If you are faffing about what is to be done in the data cleansing process, check out the step-wise method for the same.
Set Your Goals
The intuitive thing to be dealt with in the process is identifying the field in which you want to step in to get the data. Bifurcate between the high priority data and low priority data for your business and how you are going to utilize it. Prepare a list of information you are looking for: email address of the potential business clients, contact details of the potential clients, revenue generation of specific industries, and so on. If you have pre accumulated data, set the norms of the data reliability and get your veterans of the job to start verifying it.
Clean Your Data Closet
Once you have set your priorities which data is actually relevant and important to you and you have a bunch of related things, you need to sort it out. You remember cleaning your closet? Getting the useless things out, keeping the fresh clothes one side and casual on the other. Just consider your data accumulation as your closet stuff, throw the old data out of your data closet. Also, go through the existing data and sort out which data is fresh and can be used and which data cannot be relied on. If you think, the entire data closet cleaning task is very cumbersome and you don't intend to do it on your own, you can hire the services of a data cleaning company like IBCConnect and hand over your entire closet. What you get is an organized and up to date data closet.
Manual sorting can take a lot of time so, it is important to shift to data automation. Along with managing the old data, keep a track on the flow of new data entering the system. Create a workflow to manage the newly coming data. The workflow can be monthly, weekly or daily depending on the amount of data you are dealing with. Apply the same strategy for the new data as well as the previously accumulated data.
This step is to be undertaken when the data is incomplete or missing from the record. Such missing information cannot be auto-corrected. You can take the example of phone numbers, emails, company size or industry in which company is functioning. It's essential to fill up the missing information from whichever source you deem fit. You can either contact data appending services or try various contacts or try the traditional way of search via Google.