Over the past five years, we have used Visual ETL platforms such as Data360 Analyze to transform data for our customers in the UK, Europe and the US. Once a data transformation process has been developed, it can be automated so that you can have the right data available to you at the right time. Our consulting experience spans all the way from initial requirement gathering and solution design, right through to development and deployment, and finally onto training and knowledge transfer. Pomerol can truly provide you with an end-to-end offering.
In the current age of ‘Big Data’, having poor data quality leads to poor information. Poor information means a lack of actionable knowledge in business operations resulting in an inability to apply that knowledge to produce better business outcomes.
Being able to check and maintain the quality of your data held in any system is vital in order to help produce these actionable insights.
Data quality includes
Data completeness — Is there a value entered for this field?
Data Validity — Is the data valid? Eg.postcode format and content, telephone number length and format, salutation one of Mr/Mrs/Miss/Dr/etc?)
Data Consistency — Is the data consistent across all data stores. e.g. customer DOB is the same on all systems.
Data quality becomes even more important when considering the use of Machine Learning (ML) and Artificial Intelligence (AI) initiatives. Without a solid data foundation, how can you trust the forecast results?
With Data360 Analyze we leverage its ability to highlight these inconsistencies in the data, reporting these back to data stewards to remedial action if necessary or applying business rules to clean the data on the fly producing consistent output for reporting purposes to enable better business outcomes.