Best Practices for Business Enterprises to Keep Their Data Clean

by | Published on May 18, 2020 | Business Process Outsourcing

Data Clean

Clean data is actionable data, and this helps improve the efficiency and productivity of an organization. As business decisions and activities are data driven, it is important to have clean data to make better organizational decisions. Accurate data helps streamline the business and remove inconsistencies in any record. When the required data is available without any ambiguity, business leaders can focus on key work instead of wasting time correcting data. Businesses can ensure such actionable data by hiring a data entry company that provides data cleansing services.

Data cleansing process removes redundant data, corrects data errors, and modifies data that is improperly formatted. It helps prepare data for analysis. Data cleaning corrects spelling and syntax errors, standardizes data sets, identifies duplicate data points, and corrects mistakes such as missing codes and empty fields. Data needs to be clean for business intelligence and data analytics tools to easily access and find the right data for each query.

The Need for Clean Data

  • To improve sales: A sales representative failing to contact previous customers because of not having their complete, accurate data can lead to loss of customers and sales. So, having accurate and up-to-date data of your customers is vital.
  • Better marketing strategies: An ad campaign with low quality data and reaching out to users with irrelevant offers is not an effective strategy. This not only reduces customer satisfaction but also misses a significant sales opportunity. But with accurate customer data, your marketing team can reach out to the right audience.
  • Improve operations: Configuring robots and other production machines based on poor operational data can lead to major problems for manufacturing companies. Accurate operational data improves productivity and efficiency.

One of the main problems of getting accurate data lies with the inconsistency of corporate database and application in data and data processing. When data is stored across various departments, then the chances of inaccurate, incomplete and inconsistent data is high. Many companies still have siloed systems where departments are not well connected. This means that when you update the data in one system, the update is not reflected in other systems. This inability to communicate with each department can lead to poor data which affects business decision making.

Tips to Keep Your Data Clean

  • Look out for errors: Keeping records of accurate data as well as knowing where these errors are coming from is important for your business to ensure that the data is accurate. Find out the source of inaccurate data to fix the corrupt data and integrate it with other solutions for better productivity.
  • Standardizing the data entry process: Standardizing the entry point of data helps start the business process with accurate data. By standardizing your data process you will ensure a good point of entry and reduce the risk of duplication, bad records and other dirty data issues.
  • Validating and maintaining accuracy of data: After cleaning your existing data, invest your time and resources in data tools that to clean your data in real time. You can even use AI or machine learning technology to ensures accuracy.
  • Remove duplicate data: Look out for duplicate data and removes them and will save time and effort in making business decisions. Duplicate data can be removed by investing in data cleansing services or data cleansing tools that can analyze raw data and automate the process.
  • Verify the results: Once your data is standardized, validated and free of duplicate data, a third-party vendor can be assigned to clean and compile the data to provide a better picture for business intelligence and analytics.
  • Communicate with your team: Make sure to communicate the new standardized cleaning process with your team. This will help you develop and strengthen your customer segmentation and provide targeted information to customers and prospects, so that your team is in line with the new standardized cleansing process.
  • Feedback is important: Every organization should build a process that controls the places from where incorrect information is reported and then updated into the database. This will ensure that your database is accurate and clean.

Businesses use data cleansing tools or set up an in-house data cleansing team to ensure the quality of data. But it comes with its own challenges like:

  • Limited knowledge about what the root cause of data anomalies are
  • Deleting data where a loss of information leads to incomplete data that cannot be accurately filled in
  • Expensive ongoing data maintenance
  • Difficulty in building a data cleansing graph

A practical way for businesses to ensure clean and accurate data is by hiring the services of a good data entry company that provides data cleansing services. An experienced data entry team can convert unstructured data into structured data that can be effectively used.

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