Quarterly data governance roadmap with secondary data

Description:

The image is a PowerPoint slide titled "Quarterly Data Governance Roadmap with Secondary Data." It is structured as a matrix to outline the evolution of an organization's data governance strategy across four quarters of 2019. Each quarter focuses on a specific theme in data governance, with elements listed down the left side to address different aspects of the strategy.

For Q1 2019, the theme is "Fragment," emphasizing a segmented approach with several point solutions. Q2 2019 shifts to an "Enterprise Perspective," focusing on central infrastructure and KPIs. Q3 2019 is about "Advanced Analytics," including setting up ETL for secondary data sources and predictive data analysis. Finally, Q4 2019 centers on "Big Data," with aims for data optimization and governance implementation.

The elements down the left are categories of data governance, including BI Architecture, Data Sources/Data Currency, Type of Analysis/use of analytics, Data Models, Data Governance, Tools, Skills, and Cultures/enterprise data literacy. Each category has corresponding entries for each quarter, indicating the progress and initiatives planned or accomplished.

Use Cases:

Here are seven industries where this slide could be effectively used:

1. Financial Services:

Use: Outlining data strategy for risk analysis and customer insights

Presenter: Chief Data Officer

Audience: Data scientists, risk managers

2. Healthcare:

Use: Managing patient data and compliance with regulations

Presenter: Health Informatics Director

Audience: Clinical analysts, IT professionals

3. Retail:

Use: Enhancing customer data management for personalized marketing

Presenter: Marketing Intelligence Lead

Audience: Marketing team, data analysts

4. Telecommunications:

Use: Developing infrastructure for managing large data sets from users

Presenter: Network Data Strategist

Audience: Network engineers, business analysts

5. E-Commerce:

Use: Streamlining data processes for customer behavior analysis

Presenter: E-Commerce Analyst

Audience: Product managers, data teams

6. Manufacturing:

Use: Integrating data from IoT devices for predictive maintenance

Presenter: Operations Manager

Audience: Maintenance teams, data engineers

7. Education:

Use: Implementing data systems for student performance tracking

Presenter: Institutional Researcher

Audience: Administrators, educational data specialists