... with customers to evaluate whether data conforms to data governance approved mappings or standards. ... help the business improve their data allowing for better communications and ... how business needs translate to data and technology needs Strong analytical ...
... standards and continuous improvement of data delivery practices.Significant experience in data design and architecture, data modeling in complex enterprise data warehouse and lake environments. Experience ...
... standards and continuous improvement of data delivery practices. Significant experience in data design and architecture, data modeling inplex enterprise data warehouse and lake environments. Experience ...
... Partnership Investigation Team as a Data Mining Specialist at the John Lewis Partnership. ... detect malicious activity.As a Data Mining Specialist, you will be known for your technical expertise, delivering actionable data mining insight based on your ...
... to build a career in data engineering, gaining hands-on experience ... with large datasets and identify data-related issues.Team Player: Excellent ... be working closely with senior data engineers and other team members. ...
... in the areas of advanced data techniques, including data access, data integration, data visualization, data discovery, data layer design and implementation to ...
... (e.g. data fabric, data mesh, data warehouse, data lake or data hub);Data Structures (e.g. structured, semi-structured and unstructured data);Data and analytics governance (e.g. Master Data Management, data quality and data stewardship practices ...
... to and can understand the data Bupa holds; reducing barriers to entry and make the complex simple for people who want to leverage our data assets Support for Access - Help ...
... ), Information data architectures (eg. data fabric, data mesh, data warehouse, data lake or data hub) Data Structures (eg. structured, semi-structured and unstructured data). Data and analytics governance (eg. Master Data Management, data quality and data ...
... not limited to identification of data sources, extraction and transformation of data, data mapping, data reconciliation, data cleansing, data aggregation, data deduplication, data quality assessment, and root cause ...