Data Discovery Platform Solutions and Services

Challenges Faced

Data Quality Validation

Customers lack an understanding of the usefulness and completeness of data while maintaining its uniqueness at the same time.

Educating on Data

Accurate data checks and validity for exploring the quality of data stops organizations to educate their people and customers on data.

Cloud-Native

Most customers had the hybrid infrastructure which requires data from on-premise and cloud-based systems visualized together.

Data Management Solutions

By adding the provision of being able to connect to on-premise and cloud-based data management systems together, XenonStack brings in the reliability of managing the data platform.

For Hindcasting and Forecasting validation, users mostly require the ability to query metadata and data from multiple sources. XenonStack solves this problem with Data Mesh solution.

When data stewards have access to all data sources under a common roof, they deliver the data completeness and usefulness to deliver the unique data and people become more educated on the data.

Understanding of the global state of data fulfills the needs of Business Context Analytics as well as helping in deriving better decisions on Business with the presence of fact data only.

Data Mesh as a Service For Enterprise

Data Mesh will bring scalability to upcoming and new Data sources.

People can be educated more on data hence reducing the data stewards interventions.

Data issues can be identified from a source of the data to a consumer of the data.

Onboarding of On-premise and Cloud-based systems together relieve the customer from Data Migration costs.

Better Visualization tools to bring in better insights to represent the customer market and needs.

Cleaning of data at the edge reduces the efforts of Data Scientists later.

Data Discovery Implementation Strategy

Configure Data Source: Configure the data with Data Discovery Solutions.
Govern the Data: Define or select predefined data governance rules on newly configured data source.
Data Access Control: Secure the data by managing the data access patterns and assigning roles of access to data.
Information: Validate the data lineage and Metadata.