This section describes the main areas of consulting regarding the data management process in the organization.
Scope of service
We have summarized our experience of post-project management and data governance in the largest banks in the CIS and Europe. At this phase, we provide the following services:
— End-user training;
— Creation of documentation for production;
— Implementing a data governance process.
Consulting is provided to executives, as well as to head of MIS division though organizing knowledge shearing courses and building a healthy data quality and data governance processes within an organization.
At the post-project stage, we focus on the implementation of data governance, which includes:
— Organizational structure, policies and procedures for data governance;
— Responsibilities, functions and organizational structure of the SIM department;
— Creation of new functions and networking: from data stewards to data owners.
Key consulting areas of data governance include:
— Data stewards and data owners;
— Data architecture and technology;
— Archiving and data retention policies;
— Data security;
— Metadata management;
— Data quality management;
— Management of master data.
New main roles and functions within organization:
— Chief Data Officer;
— Operational Committee on data quality;
— Data stewards;
— Data owners;
— Business intelligence;
— Data analytics;
— Data modeler;
— Data Quality Manager;
— Data manager;
— Organizational structure for data governance.
Policies and Procedures:
— Data Management Policy;
— Data Quality Management Policy;
— Data Modeling Policy.
Business owners and managers will receive gap analysis and recommendations for building of sound data governance processes in an organization, including identifying data owners and securing their responsibility, as well as creating a date stewards network and building a data governance function under the control of the Chief Data Officer.
As a result, we help an organization in creating:
— End-user manuals for the information system;
— Regulation on the data warehouse production and BI;
— Descriptions of logical data flows and IT-architecture of MIS;
— Policies and procedures for data governance;
— Organizational structures and functions of MIS unit;
— New functions of data stewards and data owners.