Automated vs Manual Data cleansing services for big data

Data cleansing services is unavoidable for businesses. It is a meticulous process that requires expertise and experience in the particular domain. Whether they get it done manually or use automated tools, data cleansing is a must if the business wants to make use of the valuable information it has generated and extracted from reliable sources. Big data is helping businesses with critical information on customer usage and market conditions. But cleansing Big Data is also a challenge. Businesses typically spend 60% to 70% effort on cleansing the data they collect for analysis. This can be managed effectively by a competent Data cleansing services provider, saving your business precious time, effort and money. Here are some ways in which Manual and Automated data cleansing services are used for businesses:

Standardize Data

The very first step towards data cleansing is to standardize information. Form guidelines and standards for business information and train your data experts on ensuring data quality. An accomplished Data cleansing service provider India will first categorize the information to be sorted and stored. With bulk data and big data, this categorization will resolve a lot of redundancy and validation issues automatically. The database offers many in-built data validation routines that takes care of data cleansing to a great extent. Further, this information can be further scrutinized with manual checking.

Integrate Diligently

When there’s bulk information, it becomes necessary to integrate information diligently. Every business will rely upon multiple processing software tools for different processing purposes. There’ll be inventory management tool, payroll processing tool, accounting tool and budgeting tool all of which will need cleansed information. As the MIS will extract information from all of these, data integration across various systems become essential. Big data cleansing services offer seamless data integration across multiple system with data conversion as required. They make sure that the information that’s converted from various tools offers integrity and reliability.

Plan for Automation

Automation is essential in data cleansing to make the process more efficient and quick. Since many businesses have process automation already in place, data that flows through these systems automatically should also be automated to ensure seamless data flow. Automated data cleansing using advanced tools make sure that the information flow is not interrupted while the data is of utmost high quality. Data cleansing automation should be planned and executed diligently to ensure end to end data integrity across the various tools used.

Machine Learning for Cleaner Data

When it comes to Big Data, one of the major challenges faced is natural language processing. How do you verify and cleanse the data in images, videos and audio files? This is done using advanced Machine Learning tools. Database cleansing and building services for Big Data make use of Machine Learning and Natural Language Processing tools that analyze the raw data closely to extract what’s relevant and exclude the noise. This makes data cleansing much faster and more efficient.


Big Data cleansing requires special tools and expertise. There’s quite some automation involved which comes quite expensive for small and medium enterprises. But if they want to leverage quality Big Data, they can still do that with the help of outsourcing data management services, especially for data cleansing.