Data Cleansing – Eliminating Dirty data

Sales, Technology | 3 minutes to read

05th Mar, 2020


Not to be confused with Data screening!

Identifying errors at input stage

Many synonyms:

  • Data Scrubbing
  • Data Appending
  • Data Hygiene Management

Fixing errors post data capture

Data scientists spend 60% of the time organizing and cleansing data!

The goal is to ensure integrity, relevancy, consistency & uniformity of database post-cleansing process entailing completion, correction, deletion, filtration, deduplication 


Data is the new oil – yes oft-repeated but the truth!

Discover whitespace

Moving away from the stagnant market pie, leverage the dynamic ecosystem and bring into the net, the whitespaces yet unexplored

Net New Customer acquisition

Good quality b2b database ensures targeted prospecting, aligned communications, meaningful engagement and thus, an accelerated conversion of MQLs to SQLs

Improve the decision-making process

A high-quality data translates into accurate analytics and which in turn propels better decision-making.

Personalised services and optimisation of customer experience

Getting real-time insights to fine-tune the communication for making it personalised is a major advantage offered by intelligent analytics. Also, leveraging its power for better operational management at the back-end ensures a superior customer experience at the front-end.

Increase employee productivity

Good quality data also allows the staff to be more productive since they’d be spending less time in validating the data or digging for the right information to fill-in the gaps

Better compliance management

Businesses also stand to save a significant sum of money since quality data adhering to geographical regulations mean a better compliance management and saving of hefty fines.


To assess how often data cleansing is required, following parameters can be considered.

  • Nature of business
  • Volume of data inflow
  • Frequency of data inflow


Evaluate database

Understand data in its entirety. Assess data thorough data discovery sessions to identify redundant data. Evaluate the b2b database basis its unique goals and objectives before proceeding.

Activate safety net

Have contingency plan ready – create back-ups to ensure a fall-back option. Since >1 person may be involved in the cleansing process, imperative to keep a log of all changes and develop a common progress sheet for holistic view.

Invest intelligently

Manual process of data cleansing is both time-consuming and error prone. Hence, invest into a robust database cleansing software but only after through research. Map your expectations with tools’ features to ensure goal achievement.

Leverage automation & database experts

If data cleansing is to be done in-house, leverage automation for repetitive jobs. Take help from b2b database providers to zero down on the right tools and their usage in the best manner possible.

Regular assessment of the performance

It is important to keep a regular check on the quality score of the database. This helps in keeping an eye on allied functions like the impact on decision-making, eventual time and monetary saving and also in-time evaluation if course-correction is required.

Data cleansing has become an important part of every organisation. Analysing the data has now become more than just garbage-in and garbage-out process. In order to get more clarity on the process, Click Here to know about B2B database cleansing services by Denave.

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