How AI transforms data cleansing

The Data Business is the latest service provider to have undertaken the step into the future of Artificial Intelligence (AI) support with the development of our Advanced Data Analysis Machine (ADAM).

From its conception four years ago, our Data Scientist, Noman Shafqat supported by our data research team has worked to create a Machine Learning Platform (MLP) which can replicate the performance of our data researchers leading to a considerable reduction in time and cost.

To understand the significance of this development, we must first look at the issue of poor data governance and our methods to cleanse this vital asset.

The data cleansing process


Untreated data cannot be underestimated as a significant factor contributing to the inefficiency of the marketing and sales pipeline.

We serve clients from a variety of sectors who require assistance with appending and updating CRM or marketing datasets and commonly cleanse data that has not been properly managed or benefited from a robust data governance procedure.

Most often, we are tasked with re-categorising contacts such as matching contacts and organisations in a CRM and carrying out email verification procedures so that our clients are presented with clean, replenished datasets that adhere to a logical categorisation strategy.

Essentially, data cleansing is the best way to avoid poor returns to your marketing campaigns and should always be considered as the first point of action.

Until now, this timely and arduous process could either be carried out in-house, which is a drain on time and resources, or by a team of data research analysts who can provide a more efficient return on the process of standardising, appending, and updating key information but are still limited to human capabilities.

The future of AI

machine learning

Artificial Intelligence and its sub-set, Machine Learning, are finding their way into ever-increasing tech and data services sectors. The ability of an MLP to not only duplicate commands input by a developer but to learn and develop at an existential rate has transformed the world of data analytics, increasing the scale and efficiency with which data services can be processed.

AI in data cleansing negates the issue of data coming from multiple sources. There is no standardised process to guarantee an effective categorisation process when matching a client’s data to a stagnant database. ADAM has the intelligence and adaptability to learn when provided with an unknown value.

Meet our friend ADAM


With the Development of ADAM, we are now able to replicate the efforts of a team of researchers in key areas of categorisation, for example, Organisation Types. We have taught ADAM to categorise an organisation, such as Allen & Overy, if given its name. ADAM then utilises open-sourced information online to recognise and categorise Allen & Overy as a ‘Law Firm’.

The real strength of ADAM is that now it has learned our extensive categorisation system, it will be able to implement this when presented with new organisations, cutting the work rate by 75%, which is constantly improving.

In addition, ADAM can also categorise a Job Title’s seniority and its Job Function which is key in delivering targeted marketing campaigns. The success rate at which ADAM can carry out these categorisations sits at an amazing 95%. The mining of an organisation and its contact information can also be completed at the click of a button.

How AI saves you money

This is a major achievement for our cleansing procedures and will improve the efficiency and overall capacity of our services, while at the same time maintaining our high standards. This allows us to pass on time and cost-saving measures to our clients.

We invite prospective clients to gain further insight into ADAM by getting in touch to see how we can help on a case-by-case basis.