Traditional systems lack to present the issues and risks associated with those issues due to data distribution.
Traditional systems hold back the root cause identification as teams don’t have the data lineage over the distributed data layer.
Non-Availability of profiling and lineage tends to lose business Revenue, and the existing systems start building data quality issues.
Data profiling supports correcting the ETL pipelines by helping in data quality management.
Better data profiling uncovers the data lineage challenges faced during the early stages of data platform development.
Data lineage targets identifying the root cause analysis of the missing link in the data.
Data quality makes the system more reliable in terms of delivering the best of the business requirements from data.
ElixirData Observability intelligently bundles the automatic data issues and PII solutions.
Cardinality, relationships, and key integrity help in fixing the problematic data issues that bring reliability to the ETL processing.
Distribution: ElixirData Observability help identify the data accuracy and consistency.
Volume: Validation is quick to understand if all the tables have all data.
Schema: Data quality can be managed from the data schema information tab for correctness in data.
Lineage: Where the data landed and what sources have the data access or lineage, managed by ElixirData.