How do you find and fix data gaps with tools?

1 Data Auditing Tools

The first step to find and fix data gaps is to audit your data sources and data sets. Data auditing tools can help you examine the structure, content, quality, and consistency of your data. They can also help you detect and report any errors, anomalies, or inconsistencies in your data. Some examples of data auditing tools are Data Quality Analyzer, DataCleaner, and OpenRefine. These tools can help you perform various tasks, such as data profiling, data validation, data cleansing, and data transformation.

2 Data Visualization Tools

The next step to find and fix data gaps is to visualize your data and identify any patterns, trends, or outliers. Data visualization tools can help you create charts, graphs, dashboards, and reports that can help you understand and communicate your data. They can also help you compare and contrast different data sets and sources, and spot any gaps or discrepancies. Some examples of data visualization tools are Tableau, Power BI, and Google Data Studio. These tools can help you perform various tasks, such as data exploration, data analysis, data storytelling, and data presentation.

3 Data Integration Tools

The third step to find and fix data gaps is to integrate your data from different sources and formats. Data integration tools can help you combine, merge, or consolidate your data into a unified and consistent data set. They can also help you align, map, or transform your data according to your needs and standards. Some examples of data integration tools are Talend, Informatica, and Stitch. These tools can help you perform various tasks, such as data extraction, data loading, data transformation, and data synchronization.

4 Data Governance Tools

The fourth step to find and fix data gaps is to govern your data and ensure its quality, security, and compliance. Data governance tools can help you define, implement, and monitor the rules, policies, and standards for your data. They can also help you manage the roles, responsibilities, and access rights of your data stakeholders. Some examples of data governance tools are Collibra, Alation, and Data Catalog. These tools can help you perform various tasks, such as data lineage, data cataloging, data stewardship, and data quality management.

5 Data Testing Tools

The fifth step to find and fix data gaps is to test your data and verify its accuracy, completeness, and validity. Data testing tools can help you design, execute, and automate the tests for your data. They can also help you measure and report the results and performance of your data. Some examples of data testing tools are QuerySurge, Databricks, and DataGrip. These tools can help you perform various tasks, such as data verification, data validation, data comparison, and data benchmarking.

6 Data Monitoring Tools

The sixth and final step to find and fix data gaps is to monitor your data and track its changes, issues, and impacts. Data monitoring tools can help you collect, analyze, and alert the data metrics, events, and anomalies. They can also help you troubleshoot and resolve any data problems or incidents. Some examples of data monitoring tools are Splunk, Datadog, and Grafana. These tools can help you perform various tasks, such as data logging, data alerting, data debugging, and data optimization.

7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?