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What are the key steps for effective data discovery and inventory?

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Data discovery and inventory are essential processes for data governance, as they enable you to understand what data you have, where it is, how it is used, and how it is managed. Data discovery and inventory can help you improve data quality, security, compliance, and value. However, data discovery and inventory can also be challenging, especially if you have a large, complex, and dynamic data environment. Here are some key steps for effective data discovery and inventory that can help you overcome these challenges and achieve your data governance goals.

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Christopher Hockey, IGP, CIPP/US

Guiding Enterprise Leaders in Information & AI Governance | Expert in Risk-Based Strategy, Data Privacy, Compliance…

1 Define your scope and objectives

Before you start your data discovery and inventory project, you need to define your scope and objectives. What are the business drivers and use cases for your data discovery and inventory? What are the data domains, sources, and types that you want to discover and inventory? What are the data attributes, metadata, and relationships that you want to capture and document? What are the data governance policies, standards, and rules that you want to apply and enforce? How will you measure and report on your data discovery and inventory outcomes and benefits?

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Christopher Hockey, IGP, CIPP/US

Guiding Enterprise Leaders in Information & AI Governance | Expert in Risk-Based Strategy, Data Privacy, Compliance, Data Protection & Regulatory Compliance | Transforming Data Strategy with Future-Ready Solutions
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Target is really an expert in this. They wanted to improve their marketing so they embarked on a data discovery project. The goal? To predict if a customer was expecting a baby and tailor ads accordingly. Before starting, they clearly defined their scope. They needed data points like purchase history, especially items expectant mothers might buy. They detailed specifics: which products, from which departments, and the timeframes of purchases. With privacy guidelines, they began analyzing. Target was able to adapt marketing. But, a lesson learned: always consider customer comfort. Some felt the ads were intrusive, showing the importance of defining project boundaries and understanding the implications of data use.

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2 Choose your tools and methods

The next step is to choose the tools and methods that you will use for your data discovery and inventory. Depending on your scope and objectives, you may need different types of tools and methods, such as manual, automated, or hybrid. Manual tools and methods rely on human input and documentation, such as surveys, interviews, spreadsheets, or diagrams. Automated tools and methods use software or algorithms to scan, analyze, classify, and catalog your data, such as data profiling, data lineage, data cataloging, or data quality tools. Hybrid tools and methods combine both manual and automated approaches, such as data stewardship, data validation, or data annotation tools.

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3 Execute your data discovery and inventory

The third step is to execute your data discovery and inventory according to your scope, objectives, tools, and methods. This may involve identifying and accessing data sources and systems, extracting and collecting data samples and metadata, analyzing and assessing data quality, structure, meaning, and usage, classifying and tagging data based on domains, types, attributes, and relationships, cataloging and documenting the data in a central repository or platform, applying and enforcing data governance policies, standards, and rules. Finally, report and communicate the results and insights of the data discovery and inventory.

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4 Review and refine your data discovery and inventory

The final step is to review and refine your data discovery and inventory on a regular basis. This is not a one-time activity, but an ongoing process that needs to remain up-to-date with changes in your data environment and business needs. You should assess the accuracy, completeness, consistency, and currency of your data discovery and inventory information, as well as how well it supports your data governance objectives. Additionally, gauge the satisfaction of data stakeholders and users with the outcomes and benefits of your data discovery and inventory. Finally, consider ways to improve your data discovery and inventory scope, objectives, tools, methods, and processes. By following these key steps, you can achieve effective data discovery and inventory that can enhance your data governance capabilities and results.

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5 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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What are the key steps for effective data discovery and inventory?

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2

3

4

5

1 Define your scope and objectives

2 Choose your tools and methods

3 Execute your data discovery and inventory

4 Review and refine your data discovery and inventory

5 Here’s what else to consider

Data Governance

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What are the key steps for effective data discovery and inventory?

1

2

3

4

5

1 Define your scope and objectives

2 Choose your tools and methods

3 Execute your data discovery and inventory

4 Review and refine your data discovery and inventory

5 Here’s what else to consider

Data Governance

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