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Data Quality Platform

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Monitor your company’s data to know its quality, avoid errors, omissions, duplications and disconnections that lead you to be inefficient and lose business opportunities.

Reliable and high quality data is essential to deliver business value. It always has been, but now, in the digital age, it is more necessary than ever to have a holistic view of our customers’ data. Without this vision it will not be possible to create personalised experiences, increase sales and move forward.

Ensuring the quality of critical data is essential to optimise all operations within a company. This proper data management eliminates costly inefficiencies caused by errors. It is not possible to achieve solid digital transformation goals, accelerate new initiatives or react quickly to challenges without having a solid picture of the business based on the reliability of available data.

Delonia’s Data Quality system allows to detect deviations in the company’s data according to the set business rules and thus, to manage, centralise, organise, classify, locate, correct, and synchronise. With this solution, the three main challenges of data management can be overcome: having multiple versions of data, having data errors as a result of manual data entry and manual data maintenance, and having unreliable stale data. There are many things that can be done by monitoring this data and asking the system to return a result.

Advantages

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Operational efficiency

The quality of an organisation’s data is directly related to the agility of operations and the possibilities for evolution and change. Many of the improvement initiatives that are launched fail because of this initial error.

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Traceability

In systems where different people are involved, it is essential to leave a detailed trace of who, what, how and when an action was done and the effect on the data. This also makes it possible to detect the source of errors and correct them.

Auditability

The system allows all information to be monitored so that it is accessible for data quality audits and certifications, which speeds up these processes and improves the overall outcome of inspections.

Digital transformation

Technological solutions that rely on artificial intelligence need to handle a lot of data and get it right. Without certifying the quality of the data, it is not possible to undertake robust digitization processes.

Business agility

Decision-making in today’s business environment requires agility. This decision making is largely based on the information available, and for decisions to be correct, the information must be supported by valuable and reliable data.

Customer service

Customer service is the main beneficiary of working with systems that guarantee the quality of their data, in order to avoid errors, encourage self-management and personalise services that guarantee customer loyalty.

Applications

Any organization that handles large volumes of data and needs it to be reliable for the management of its business.

Companies that need to detect errors in their data in order to implement control and automation measures to minimise them.

Features

Kpis configurator panel

The solution is based on the prior configuration of the kpis to be measured and the threshold to be considered significant, warning the user of any deviations detected.

Kpis classification system

The system allows to classify the kpis in order to be able to monitor them with different criteria and thus code the deviations according to the origin of the deviations: poorly resolved business criteria. debugging problems in data entry, etc.

Alarm monitoring

The system will warn through the control panel of the status of each of the indicators. When the set thresholds are exceeded, the system will alarm and the percentage deviation will be displayed.

Evolution of indicators

Each of the kpi described above will have a record of progress and it will be possible to measure the degree of improvement as action is taken. This will make it possible to clean up previous data and not replicate errors that have already been detected.