Data Quality Assessments (data & processes)
The Data Quality Assessment consists of five major steps:
- Initiation;
- Data Quality Analysis: Identify data issues and improvement areas;
- Data Quality process analyses: Identify where data is impacting the process and where processes are impacting the data. Identify process issues and improvement areas;
- Data quality report: Findings and conclusion of the analyses. Definition of Data Quality solutions and approach;
- Workshop.
During the Data Quality Assessment Human Inference will analyze the quality of the customer data and the data quality processes that have impact on the analyzed data.
The assessment of procedures and (business) rules will be done by organizing a workshop with employees of the customer. In this workshop we will discuss all manual and automatic procedures and rules to check if improvements can be made. This workshop will be lead by a senoir consultant of Human Inference.
The results of all analyses will be written down in a data quality report, which will be the input for defining the solution direction and improvement opportunities within three months (Quick wins) and long term goals.
With this information and analysis a workshop will be organized between the customer and Human Inference. In the workshop we will present, explore and discuss the quality of the customer data and processes and the solution direction, and potential improvement opportunities. Solutions and approaches will be proposed, explored and discussed to improve the data quality continuously.
The final goal of the Data Quality Assessment will be:
- To have updated procedures in place to avoid polution;
- To have defined next steps for implementation within the RBI infrastructure;
- To have an approach how to use as much as possible functionality of the current licensed Human Inference software (configure new parametres);
- To have an approach how to improve the data quality with 'quick wins' and define them;
- An agreement on the steps in which Human Inference consultancy support the new procedures;
- To come to a mutual understanding and agreement on the solution to be chosen and the next steps to be taken to improve the data quality continuously.
This deliverables of the Data Quality Assessment will be:
- A detailed report which outlines the analyzed data, including our conclusions and recommendations;
- A detailed report with the outcome of the workshop, including solutions on the discovered problem areas;
- A plan of approach (action plan) on the quick wins for Data Quality Approval;
- An action plan on the steps necessary to be taken to guarantee high level of Data Quality.
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