The expansion in business application and integration complexity is making it more difficult for organizations to sustain data quality at high levels. Datability Ninety X is built on innovative concepts like user accountability, automatic transformation and loading, and integrated manual cleansing, among other unique abilities to help organizations keep data clean all the time.

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Rules Management Engine

The Rules Management Engine is responsible on the administration of Datability Ninety X quality rule books, in which cleansing routines and parameters reside. The quality rules books have hundreds of rules ready out-of-the-box. These books contain general rules that are applicable on general customer and product data, like age and birthday rules, gender, names, contacts, … etc. Additionally, they contain country specific quality rules such as National ID verification, occupation category, ... etc. Moreover, the rule books also contain industry-specific rules including those imposed by the regulator. Customer-specific data are added on installation.

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Task Management (Manual Cleansing Engine)

MACE is cornerstone component in the solution as it is responsible for genuine integration of manual cleansing into the whole process, sharing the same rules, user access rights, and parameters. MACE manages with data cleansing tasks that need human intervention and cannot be automatically cleaned. MACE manages the full cycle of bulk cleansing, distributing data to agents in controlled excel sheet that are not modifiable and that have clear marking of fields that have issues and notes showing the issue description. MACE also, using interfaces to the organization content management system, facilitates evidence-based cleansing. Finally, MACE automates manual record survivorship based on record and field matching.


Performance Management

DNX Platform leverages a set of activities that ensure organization goals are met in an effective and efficient manner. DNX performance management dashboard records & exhibits pending tasks, workload, AVG time per task and jobs achievements percentage ..etc,

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Quality Monitor

What doesn’t get measured, doesn’t get done. This is the main purpose of the Quality Monitor, it tracks a comprehensive list of metrics that indicate trends in data quality in your organization, and provides dashboards to track individual and group performance in terms of quality upkeep. It also provides notifications through integration with email and SMS services, to send alerts and produce data quality mismatch reports. This serves as an immediate warning to users aiming for ongoing behaviour correction.



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