If you are running a small business, then you might be finding data management to be an easy process that requires you to handle a few Excel sheets. However, as your business continues to grow, you would not be able to use this simplistic method to keep track of your business data any more. What used to be a single-page Excel sheet now gets transformed into a warehouse containing tons of data. Growing businesses that need to capitalize on information in order to boost their operational efficiency and revenue growth and improve their products or services should consider investing in data science services. This would allow them to keep their data organized, to understand how they should search for important data, and to interpret available data in an accurate manner. With this approach, businesses are able to perform accurate data analysis. A vital part of being effective and efficient in this activity is to ensure that you are using clean data sets that would give you clarity. No wonder why today’s businesses are investing in data cleansing operations. In this article, we have explored the concept of data cleansing, data cleaning steps and techniques, and significance of data cleaning in data mining so that businesses take data cleaning seriously and are able to harness the power of data to drive results.

Why do Individuals Need Data Cleansing?

Personal information, including tax information, credit card data, banking and mortgage details, legal names, and birth dates, may get accumulated in an individual’s computer over a period of time. Soon, it might become difficult for individuals to manage all these information and to find documents that they need urgently. People may need to check several old documents in order to find the documents that they are looking for. Documents that are not stored in an organized manner may never be retrieved. With data cleansing, individuals can ensure that they are able to easily find the recent and important documents. By keeping your documents organized, you can prevent data security issues as well.

Why data cleaning is important?

With timely and structured data cleaning, companies can get a lot of benefits including:

  1. Prevention of costly mistakes

    When businesses invest in data cleaning, they can easily avoid the costs that are associated with identifying errors and rectifying them and performing troubleshooting. For instance, businesses need to ensure that products are delivered to the right addresses and this would save them from incurring additional costs for redeliveries.

  2. Data usability across diverse channels

    Cleaning facilitates professional management of customer information across multiple channels. For example, by maintaining an accurate record of customer details such as phone number, email addresses, and postal codes, businesses can successfully implement contact strategies on different channels.

  3. Easier client acquisition

    Companies that maintain their customer data in a systematic manner are able to easily set up a prospect list by making use of updated and accurate data. By using these details, they can make their customer acquisition operations more efficient.

  4. Ease of decision-making

    Clean data supports the process of decision-making. With accurate information in hand, businesses are able to perform analytics better and handle MI in an efficient manner. This, in turn, facilitates better decision-making.

  5. Boost in team productivity

    Data cleaning promotes data quality and this contributes to greater productivity. By eliminating unwanted data and retaining quality data, companies are able to make a holistic use of high-quality data and ensure that their teams remain engaged in productive work.

  6. Data cleansing for data quality

    Quality information aids in undertaking processes efficiently, to gain an edge over competitors, to deliver high level of customer experience, and to advance to the next levels.

How to evaluate if you need data cleaning?

You should hire a service provider to get the accuracy of your data assessed. They would be able to let you know if it needs to be cleansed.

Why Data Cleaning is Important for Businesses?

Businesses need to manage loads of information such as business details, employee details, and client data. With data cleansing, businesses can ensure that they keep their important data safeguarded for future use. Data cleansing ensures on-time availability of data and accuracy. Businesses should have accurate employee information as well as customer information that would allow them to make critical business decisions. This would generate the desired marketing results as well. Cleansing allows businesses to improve data quality by allowing them to get rid of outdated and unwanted data and helping businesses to categorize quality data in the most appropriate manner. With cleansing, businesses can avoid costly mistakes.

Stages of Data Cleansing

The data cleansing process includes a number of stages including:

  1. Dealing with the missing details

    Quality data management calls for identification of missing data. For example, when you find postal codes to be missing, you may infer that the goods remained undelivered. External support may be needed to attach missing elements in order to build a complete data set.

  2. External Data Validation

    External details need to be validated to ensure accuracy and uniformity. This would enable businesses to maintain communication channels, facilitate the payment process for the customers, and address legal liabilities as well.

  3. Elimination of Duplicate Details

    By eliminating duplicate data, businesses are able to keep their databases up-to-date and accurate.

  4. Management of Structural Errors

    Addressing mistakes that result during the measurement and transfer process emphasizes the value of data cleaning. Among the diverse issues that need to be addressed are mis-categorized classes and typos.

What should be the ideal frequency of data cleansing?

The cleansing process is performed at one-go and it may demand a lot of time if your data has been accumulating for years. That’s why you should opt for cleansing at regular intervals of time. The frequency of cleaning depends on several factors including the volume of data that needs to be reviewed. You may not choose to opt for data cleaning within short intervals as this would lead to resource wastage on account of unnecessary efforts.

Data Cleansing Tips & Techniques

The cleansing process is quite elaborate; however, the processes may differ from one organization to the other. However, we have listed some general tips that you may consider trying out:

  • Assessment

    Data cleaning typically includes elimination of data from a single database, for example, a spreadsheet. If you are maintaining data in an organized form in a spreadsheet or a database, then it would become easier for you to assess your data faster and to understand what needs to be updated. On the other hand, if your information is stored in separate files in different locations in your computer, you may want to compile data in a single file to facilitate the assessment process. You should ask these questions as part of your data assessment activity:

    Is my data making any sense?

    Is data duplication present?

    Is numerical data adding up to create a meaning?

    Is there is any error?

    With this primary assessment, you will be able to get a fair idea about how much effort you may need to put. You would need to allot more time if you have to clean up records from the past 10 years in comparison to the time that you may need to spend in rectifying spelling mistakes and out-of-date numbers.

  • Use A Separate Spreadsheet for Cleansing.

    It is a good idea to generate a copy of the original spreadsheet and to implement all the changes in the new document. This is necessary to safeguard your original document against mistakes. Once you are sure that your new document is error-free and once you are done with cleansing, you may get the information in the new sheet copied to the original spreadsheet. This would demand additional effort, but it would pay you back in terms of peace of mind.

  • Use Functions.

    It would be quite difficult for you to clean up errors manually.If you are working on a spreadsheet, use software features. Microsoft Excel comes equipped with a lot of functions that would allow you to cleanse data in a much easier way. For example, Excel has a feature called ‘remove duplicates’, which would make your job quite easy. So if you have entered a customer’s information twice, this feature would correct your mistake automatically.

  • Use Data Cleansing Software.

    If you find the task of cleansing to be too much tiring, you may consider deploying data cleaning software to accomplish this task. These software may be pricey, but these may be a solution for you if you can’t perform cleaning yourself.

A Final Word About Data Cleansing

Businesses and individuals find data cleaning to be a hard task because they allow information to accumulate over time. Records may get transformed into a real mess in terms of duplication, spelling mistakes, confusion, and obsoleteness. With cleansing, the process of data management becomes quite simpler. Data management includes the creation and implementation of processes, policies, architectures, and procedures for managing an organization’s information. Data management includes database management, record management, data security, document sharing, and data storage. And all these processes get systematically implemented if you implement cleansing.

Outsourcing Data Cleaning

Growing companies don’t have much time in cleaning their databases and the large volumes of information pile up year after year and finally become a mess to handle. Data cleaning is an important factor in generating superior-quality algorithms that are needed in domains such as machine learning.  Clean information can help businesses to derive meaningful insights and take appropriate actions. When you choose to outsource your data cleansing requirements to a reputed service provider, you can save on time and efforts that you might otherwise spend on this tedious task. With outsourcing, you can get access to the best data scientists in the world and they would ensure that you get the most accurate outcomes at a fraction of a cost that you might otherwise end up spending if you do this yourself. Outsourcing is a low-risk, low-cost option that would allow you to get the best outcomes at the best rates.