Business Data Analyst
Posted on Aug 1, 2019 by CV-Library
The Business Data Analyst is accountable for the quality and timeliness of their deliverables, assisting other team members and keeping the Data Architect informed of pertinent information.
Document & diagram business, application and technology views of data "in motion" and its dependencies across systems and manual processes to understand how and where data flows through the business. Including data entering and leaving the business.
Identify the implicit Data Producers, Consumers, Owners and Stewards across the Business.
Build up a business glossary (i.e. Data Dictionary) defining the business terms used throughout the business and how they are defined and differ in terms of the data in the source systems.
Business analysis experience with a data bias, including a knowledge of business mapping and modelling processes as well as the inherent strengths and weaknesses of business analysis methods and implementation approaches
Experience of building and maintaining: Data Dictionaries, Data Models (Conceptual, Logical and Physical), Data Flows
Experience of Reporting and Data Visualisation tools (specifically PowerBI and SSRS) and other OLAP technologies.
Knowledge of Data Management tools or platforms (e.g. Business Glossary, Data Quality, Data Cleansing etc)
Knowledge of the Lloyd's Market (and the US Admitted market), its regulatory requirements and the impact this may have on proposed solutions or business changes
Good understanding of systems and applications of the Insurance Underwriting and Reinsurance industry within the Lloyd's Market e.g. PAS, Claims, Exposure Management systems etc
Experience of some of the following:
Back-office underwriting systems, in particular Subscribe S2000 (NITL)
Claims management systems
Bordereau systems, in particular Watertrace BDX
Exposure management systems
Enterprise or Financial Data WarehousesEssential Knowledge
Understanding of the Lloyd's of London and company (re)insurance markets is Essential.
Understanding of best practices Data Architecture Principles. IT Literacy
SQL Server/T-SQL experience
Experience of SSIS, SSAS and SSRS SQL Server technologies