Data Cleaning | De-duping, Matching & Cleaning | Datamine

BENEFITS OF DATA CLEANING

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Improve analytics and decision-making

Input

Leverage technology investments

Data Mart

Reduce costs for data storage and management

Segmentation

Deliver timely, personalised customer service

Data Cleansing

Maintain data integrity for legal and regulatory compliance

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Minimise wasted time managing inaccurate or duplicate data

MAKE DATA MORE USABLE

Data cleaning validates, reformats, updates and enhances business information to make it more usable and valuable. Some common data-cleaning processes include:

Mail ADDRESS CLEANING

Matching addresses to postal address files lets us account for variations in the way people fill out forms. We can standardise formats, verify information like gender, addresses, phone numbers and more, and flag customers who meet certain criteria.

DE-DUPING

De-duping is essential if you’re merging data from across departments, locations and systems. This intelligent process automatically finds likely matches, not just identical entries to create and maintain a single view of customers.

MATCHING

Matching arranges your data into groups based on set criteria. For example, it will group people who live together by matching on address data or identify likely duplicates before a merge. This process makes use of data more efficient and allows cross-selling and consolidation.

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Clients we have provided data cleaning for

Case Study: INSURANCE

The process

After completing market research, an insurance customer still felt in the dark about who its customers were, how they behaved and how to generate additional sales across its various offerings. Our client had only a general idea of the brand’s market share – it needed to dig deeper into the data to better understand its customers and what products they were interested in.

The result

Datamine experts worked alongside the client to clean data extracted from three different customer systems. This process ensured the data was set up to deliver the insights our customer needed to make better decisions and investments. The project costs were quickly recouped through more effective marketing activities that led to the addition of new policies and higher sales figures.

What's Next?

Data cleaning pricing

Data cleaning pricing depends on the number of data sources you use, how messy your current data is, and how much of the process you can do in-house. We’ll also consider your goals for getting clean data – what will you do with the data once tidy, and how much logic will you need to deliver that?

See costing guidelines for solutions that include data cleaning on our pricing page.

Higher quality in, improved ROI out

Gathering data isn’t enough to improve organisational decision-making, efficiency, productivity and the use of AI and automation. It also needs to be clean, well-structured and usable – that’s where data cleaning comes in. Contact us to kick-start the process now.