In my previous post, I introduced the concept of a data roadmap and discussed its importance in today’s data-driven world. Now, let’s explore the steps to assess the current state of data in your organization, which is a crucial starting point for building a data roadmap.
A. Data audit
Conducting a data audit involves examining your organization’s existing data sources, assessing their quality, and mapping data flows and dependencies. This helps you identify any gaps or weaknesses in your data infrastructure and sets the stage for designing a comprehensive data roadmap.
Build a Data Roadmap Series
~ Part 2: Assessing the current state of data
in your organization ~
1. Identifying data sources – Start by listing all the data sources your organization uses, including internal systems, external vendors, and third-party applications. This will give you a comprehensive view of where your data comes from and help you understand how different data sources are interconnected.
2. Evaluating data quality – Assess the quality of your data by examining its accuracy, completeness, consistency, timeliness, and relevance. This will help you identify any data quality issues that need to be addressed and ensure that your organization makes decisions based on reliable information.
3. Mapping data flows and dependencies – Create a visual representation of how data flows through your organization and identify any dependencies between data sources, systems, and processes. This will help you understand the complexities of your data ecosystem and pinpoint any bottlenecks or inefficiencies that need to be addressed.
B. Identifying data stakeholders.
Recognizing the key data stakeholders in your organization is essential, as they play a crucial role in shaping your data roadmap and ensuring its success.
1. Internal stakeholders – These are the people within your organization who use, manage, or are otherwise affected by your data. They may include business leaders, data analysts, data engineers, and data stewards.
2. External stakeholders – These are the individuals and organizations outside your company who interact with or rely on your data, such as customers, suppliers, and regulatory authorities.
C. Assessing organizational data maturity.
Data maturity refers to your organization’s ability to effectively manage, use, and derive value from its data. Assessing your data maturity helps you understand your organization’s readiness to implement a data roadmap and highlights areas where improvements are needed.
1. Data literacy – Evaluate your organization’s level of data literacy by examining the skills, knowledge, and understanding of data among employees at all levels. This will help you identify any gaps in data literacy and plan targeted training programs to address them.
2. Data infrastructure – Review your organization’s data infrastructure, including data storage, processing, and management systems. This will help you identify any areas where upgrades or replacements are needed to support your data roadmap.
3. Data governance – Assess the effectiveness of your organization’s data governance practices, including data policies, standards, and procedures. This will help you determine if your data governance framework is robust enough to support your data roadmap and identify any areas that need improvement.
Roles involved: Data Strategist, Data Architect, Data Analyst, Data Engineer, Data Stewards, Business Leaders
Stay tuned for my next blog post, where I’ll discuss how to define your data vision and strategy. Together, we’ll continue exploring the fascinating world of data strategy and building a data roadmap for your organization.
Here are three publicly available links related to assessing the current state of data in an organization:
- “Data Management Maturity (DMM)℠ model” by the Data Management Association International (DAMA): https://dama.org/content/data-management-maturity-model-dmm This website provides an overview of the Data Management Maturity (DMM) model, which is a comprehensive framework for evaluating an organization’s data management practices. The DMM model provides a standard for assessing an organization’s data maturity across various dimensions, such as data governance, data quality, and data integration.
- “The Enterprise Data Management Council (EDMC)” official website: https://edmcouncil.org/ The Enterprise Data Management Council (EDMC) is a non-profit industry association dedicated to advancing data management practices and standards. Their website provides resources and tools for assessing and improving an organization’s data management practices, including whitepapers, research reports, and best practice guides.
- “Data Management Body of Knowledge (DMBOK)” by the Data Management Association (DAMA): https://www.dama.org/content/body-knowledge The Data Management Body of Knowledge (DMBOK) is a comprehensive guide to best practices and principles for managing data. The DMBOK provides a framework for understanding the various components of data management, such as data governance, data quality, and data modeling. The website provides an overview of the DMBOK and its various components, as well as links to related resources and publications.
- Journey to enterprise frameworks