An organization may have large volumes of data that needs to be accessed at all times. Proper handling of the organizational data and maintaining data quality levels is of utmost importance in order to obtain better results in the company’s performance and decision making. From time to time, a data quality audit must be executed to understand if the quality of data is maintained above the permissible limit. This is why it is important to deploy data quality audit tools in a company.
What Is The Actual Need Of A Data Quality Tool?
Organizations are collecting ever increasing volumes of data, and without a defined data strategy and quality level, this deluge of data can be overwhelming and harmful. Unless your organizational data really helps you in decision making, and maintaining and developing the business, it is completely useless to collect it. A regular data audit is necessary to understand the actual status of the data quality and integrity in the organization, and to face data quality challenges bravely.
If you are looking to improve the quality of data in your organization, along with data enhancement,the first thing you need to do is to deploy a good tool that is capable of analyzing the quality of data in the organization. Here are features and qualities of a reliable data quality audit tool that should be present in order to help an organization maintain quality data standards.
Features And Qualities Of A Good Data Quality Audit Tool
A good data quality audit tool must be able to analyze the organizational data properly and help in detecting all data quality issues. In addition, the tool must:
1. Help in verifying the quality of the data used in the organization
2. Help in accessing the underlying data management and reporting
3. Assist in assessing the system’s ability to collect and report quality data
4. Check that appropriate data management systems and data quality management tools are in place and being used throughout the system.
5. Conduct periodic assessment and verification of the data, and performs monitoring and evaluation of the data quality and other aspects in the organization.
6. Provide findings that are used to identify the needs for adopting data quality management systems and strengthening data management by taking further actions.
7. Present a complete report of data quality and integrity in the organization to the managers of the business, and with a full and detailed analytical report, it suggests recommendations and necessary actions for data quality improvement which is completely based on the audit findings.
If you’re not sure where to find such a tool to start your data quality journey, check out RingLead’s DMS Scanner. DMS Scanner will scan your entire Salesforce and identify all duplicate records, as well as all empty fields that are currently inside your database. Scan your entire org in minutes, and receive a comprehensive health scorecard right after the scan for a better understanding of the current state of your data quality.
Once you’ve determined the pain points of your database, use a data management tool, like RingLead Data Management Solutions, to dedupe, protect, normalize and enrich your CRM or Marketing Automation System quickly and easily. RingLead DMS is the only cloud-based, fully scalable data management platform that can handle all of your data quality needs efficiently, saving you time, money and energy.
Try our DMS Scanner today, by clicking the box below!