Important things to consider when looking for a data quality solution
A data quality solution must be accompanied by real support and offer a number of guarantees to put your data quality project on the right track for the long term.
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Real-time data entry control, database cleansing, deduplication: regardless of the objectives of your data quality project, it’s important that you check what the software developer has put in place to ensure easy integration, and use that is secure and user-friendly, with uncomplicated configuration.
Upstream of the Data Quality project: identify and measure
The business lines that work on the data know whether their database needs to be upgraded and unified to get a 360-degree view of their customers. Finding unsatisfactory deliverability rates in email campaigns, dealing with perpetual undelivered mail, or juggling with duplicate or triplicate customer records, for example, are problems that speak for themselves. On the other hand it can be more difficult to evaluate the extent to which the client data in the database needs to be adjusted and the benefit of investing in a Data Quality Management (DQM) solution.
Since it is not possible to correct Data Quality problems without having identified and evaluated them, the vendor of a Data Quality solution must be able to enlighten you and propose to work on a sample of data from your database to make a concrete diagnosis. An audit of the database allows you to have a precise idea of its quality, according to the criteria dictated by your company. For example, what proportion of email addresses needs to be corrected to increase the reachability of the database. Regarding postal addresses, what types of errors occur – for example, missing street numbers, incorrect postal codes, misspelled street names, etc.? This audit should give a clear picture of the areas of remediation. This information is essential to put a Data Quality project on the right track.
Anticipate the integration in your Data Quality project
The integration of a technological solution remains a critical step that must be anticipated and a Data Quality solution is no exception to the rule. Simplicity and speed are among the priorities, so it is important to check the integration methods and the timeframe to be anticipated – should you anticipate an implementation of a few days or several weeks? When will your IT staff be able to take over? The most efficient data quality solutions are designed for easy integration, thanks to a set of connectors and web services that operate with the main enterprise systems (CRM, ERP, cash register software, etc.). Above all, they do not require additional development, which is costly and difficult to upgrade later on.
Another major issue is the possibility of customizing the quality of your customer data. On this subject, the advice of the vendor or integrator is strategic in order to apply a Data Quality tailored to your company. You need to be guided in the definition of the quality rules, but also beyond, for example on how to process the data via the solution to meet local regulations. Also, the expertise in customer data in the broadest sense of the word of your vendor or integrator is a criterion of choice for the success of your project. You must be able to ask the questions related to Data Quality that emerge, and get usable answers.
Security, a sensitive issue in a Data Quality project
Customer data means highly sensitive data. DQM solutions naturally address these issues and offer several data protection options. The first requirement is of course to choose a vendor that has a proven track record in terms of the security of its own infrastructure – data centers, resistance to intrusion tests, security audits, and equipment redundancy.
The other security issue in Data Quality Management is the treatment of customer data – your company’s data. Where are the operations for quality improvement of an existing database, for example? In the cloud? In the editor’s data center for temporary processing? In your company’s customer base? A comprehensive DQM solution that addresses both the cleaning of existing databases and the real-time qualification of incoming flows is likely to combine several of these methods. A review of the practices and security standards applied is therefore necessary with your service provider to clarify everything.
Coaching and training on DataQuality Management
If implementation support and solution training are a must in any software project, it remains to be seen how much autonomy the customer can get from it.
In terms of data quality management, bear in mind that the solution is configured on a case-by-case basis, according to the needs of each company. For example, in terms of deduplication and unification of customer data, many parameters will be unique to the company, such as the criteria according to which to identify a duplicate or the threshold beyond which to stop merging to avoid losing customer data. Expert support is therefore imperative and your editor or integrator must be able to provide it. Also consider whether the solution operates in “black box” mode, or whether your vendor can really hand things over to you. This is an essential question if you want to control your customer data, without being permanently dependent on your service provider.
Training, or even certification in the solution’s technology, must also be considered, since they allow for becoming autonomous. A single training course may not be enough on a matter as complex as Data Quality Management. The ideal solution is a comprehensive program that caters to different levels of expertise – novices and experts alike must be able to increase their competencies. The training and certification program of the vendor is therefore another criterion to be checked.
About DQE
Because data quality is essential to customer knowledge and the construction of a lasting relationship, since 2008, DQE has provided its clients with innovative and comprehensive solutions that facilitate the collection of reliable data.
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