​INFOLAERS DATA STRATEGY

Define enterprise data architecture vision, strategy, principles and standards; get buy-in from stake-holders, management, business partners, and propagate throughout the company.
Provide framework, stewardship, governance and decision making for management of data for project development teams, business users and other stake-holders.
Balance short-term versus long-term actions, strategic versus tactical requirements, while continuing to move forward towards the strategic vision.
Deliver a road map to achieve the vision.

Main focus:

logical and physical design, transformations, ETL and reporting architecture
Building bridge between  the business and technology by conducting more formalized business functionality requests, building trust, focusing on delivering business value and providing  technical teams the business needs and, often, the more advanced analysis/design/development techniques needed to meet those needs

Additional functionalities:

STANDARDS/PROCESSES/TOOLS

•Develop enterprise data management methodology and standards, and promote to both technology and business throughout the company.

•Over time, create appropriate standards, processes and tools to promote and facilitate:

◦Mapping of data sources

◦Documenting interfaces and data movement

•Designing the movement of data through the enterprise:

◦Defining integrative views of data especially for analytic purposes

•Focus on data quality:

◦Put in place governance processes around meta-data to ensure an integrated definition of data for enterprise information, and to ensure the accuracy, validity, and reusability of meta-data.

◦Participate in developing consistent definitions for common reference data.

◦Establish measures to chart progress related to completeness and quality of meta-data for enterprise information, to support reduction of data redundancy and fragmentation, elimination of unnecessary movement of data, and improvement of data quality.

◦Provide input on large-scale projects and road maps for compatibility with the vision.

◦Drive selection of data management tools, and the development of standards, usage guidelines and procedures for those tools.

Define the process to resolve cross-organizational data management issues.Type your paragraph here.