Maximizing Results with Data Cleaning: Tasks to Outsource

Data Cleaning
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With the ever-increasing amount of data generated in terms of financial reports, sales reports, customer data, employee records, inventory data, production data, etc., it can be a daunting task for any organization to keep their data clean and up-to-date all the time. 

Data cleaning companies offer a wide range of services from data enrichment to data deputation to help businesses improve the quality of such data. However, it can be challenging to understand which services are best suited for your data needs. That’s why, in this article, we’ll take a closer look at the various data cleaning services that businesses can outsource and how they can benefit from them.

What are the Different Data Cleaning Services to Outsource?

Here are the different services that you can expect when you opt for a data cleaning company:

  • Data Formatting 

Data formatting is the process of structuring the data to ensure consistency and compatibility with the tools and systems used for its analysis. In this process, the service provider makes sure that everything is labeled correctly and is in the same format. For example, if you have a list of dates in different formats (mm/dd/yyyy and dd-mm-yyyy) and you have to merge two different databases for analysis. With the help of data formatting, the service provider will convert all the dates into the same format (e.g., mm/dd/yyyy). This creates a consistent and uniform format of data within a database.

  • Data Enrichment

Data enrichment is the process of enhancing business data sets by adding relevant and useful information to existing data, such as demographic or geographic data, social media profiles, and behavioral insights. The data enrichment process also helps to add any missing values and data like email IDs, phone numbers, or any personal information of your customer or any other businesses. The aim of this process is to keep your database up-to-date and complete. Moreover, this additional information will help you better understand your customers, including their preferences, and behaviors and thus ultimately optimize your marketing strategies and improve customer experiences.

  • Mailing List Cleansing

Mailing list cleaning is the process of identifying and removing inactive, obsolete, and invalid email addresses from a business’s mailing list. It is an important service especially for the marketing team because it helps them avoid sending emails to inactive or invalid email addresses.This results in harming the sender’s reputation and decreases their email deliverability rates. This means that their emails are more likely to be marked as spam and may never reach the intended recipients.  Hence, you can use this service to keep your email list current and updated.

  • Data Standardization

Data standardization involves transforming and structuring data into a common format to ensure consistency and accuracy across different sources. This can involve correcting errors and inconsistencies, verifying data quality, and modifying the data itself to align with predefined rules and standards. For example, ‘Mister’ may be entered as Mr., mr., or mister. The service provider will identify such mistakes and standardize your data in one structured form. This ensures that data is consistent and accurate across different sources, making it easier for businesses to manage and analyze their data. 

  • Data Deduplication

There are many instances when an organization faces issues with duplicate data. For example, in a customer database, duplicate records can occur if the same customer is entered multiple times with slightly different information. This data needs to be removed to keep the database clean. This is where data duplication services come in. It is a process that helps to identify and remove duplicate data from the database. This can be applied to email lists, financial records, and other types of data to improve data quality and streamline data management processes. By cleaning these records, you can avoid sending duplicate communications, ensure accurate customer information, and reduce storage costs. 

  • Data Verification & Validation

A lot of business decisions are taken primarily on the basis of data. This data needs to be collected from a trusted source and validated. Data validation is this process of ensuring that the data entered into a system or database is correct and meets certain criteria or rules. This process involves checking whether the data is within certain ranges or limits, follows a specific format, and meets specific business rules. For example, validating that an email address is correct and in format or that a credit card number is valid. This service helps to improve data quality, reduce errors, and increase efficiency in decision-making processes.

  • Data Profiling

Data profiling is the process of analyzing and understanding the data in a system or database. It helps to identify patterns, relationships, and inconsistencies in the data, which can be useful for improving data quality, making better decisions, and enhancing data management processes. For example, imagine you are a company that has a customer database containing a large amount of data. By using data profiling techniques, you can analyze the data and identify things such as the most common age range of your customers, the most popular products they purchase, and the regions where they are located. These services help you to make better decisions about marketing and sales strategies.

How Can Your Business Benefit from this Clean Data?

Here are some benefits of clean data:

  • Effective Decision-Making Process

When data is clean, accurate, and reliable, it provides a solid foundation for decision-making. For example, imagine a business using inaccurate data to make decisions about its inventory levels. The inaccurate data may lead to overstocking or understocking of products, which can result in lost sales or increased costs. However, with clean data, the business can make informed decisions about inventory levels based on accurate information, leading to better stock management and cost savings.

  • Cost-Effective

Clean data also helps to avoid miscommunication that can arise from inaccurate or incomplete information. For instance, a business performed an analysis of customer data to know customer preferences and choices. The stats and decisions taken from this analysis will be absolutely incorrect if the dataset contains invaluable data. For instance, you might end up increasing the production of that specific product with less demand on the basis of this analysis just because of one minor mistake (number replaced from 09 to 90). Hence, clean data helps to make decisions and saves you from spending on inaccurate business decisions.

  • Better Marketing and Sales Effort

Clean data helps in better marketing and sales efforts in three ways:

  • Targeted marketing campaigns: It allows businesses to segment their customer base and target specific groups with personalized and relevant marketing messages. This leads to better engagement and conversion rates, resulting in increased sales and revenue.
  • Improved lead generation: It identifies and targets the right audience for their marketing campaigns, resulting in more effective lead generation efforts. This leads to a higher quality of leads and increased sales opportunities.
  • Accurate sales forecasting: Clean data provides accurate information on customer behavior and trends, enabling businesses to make more accurate sales forecasts. This helps to improve inventory management and ensure that the business has the right products at the right time.
  • Reputation Management Strategy

Clean data is critical for effective reputation management strategies, as it helps businesses to maintain brand integrity, deliver a better customer experience, and avoid the negative repercussions of unmanaged data. By implementing a data cleaning process, businesses can ensure that they only reach the right people with personalized and relevant messages, leading to increased engagement, loyalty, and revenue. 

  • Reduce Compliance Risk

Inaccurate data can lead to compliance violations, which can result in legal, financial, and reputational consequences for businesses. For example, consider a financial institution that is required to comply with anti-money laundering regulations. If the institution’s customer data is inaccurate or incomplete, they may inadvertently conduct transactions with individuals or entities that are on a government watchlist, leading to compliance violations and severe penalties. To save your business from any such issues, data cleaning keeps your records accurate, complete, and up-to-date, reducing the risk of compliance violations and associated penalties.

Conclusion

Overall, data cleaning is an important process to keep your data up-to-date and useful. Moreover, depending on whether you want a comprehensive suite of services or just a single one, outsourcing data cleaning services can help you keep your data clean and acquire useful insights and a competitive edge in the business on the basis of clean data.

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