Imagine a weekend where your mom decides it's time to organize the entire house. The house, with items scattered in every room, is like an organization filled with data across multiple systems. In this story, your mom takes on the role of the Chief Data Officer (CDO), making the high-level decisions and setting policies for managing the household items (data). You, as the management level, are responsible for implementing these policies, assigning responsibilities, and overseeing the entire process. Here's how the adventure unfolds:

Discovery

It’s Saturday morning, and your mom gathers the family in the living room. "We need to get this house organized," she announces. You glance around, seeing toys under the couch, old magazines on the coffee table, and kitchen gadgets spilling out of drawers. Your mom, the CDO, has identified the problem and sets the goal: a well-organized home.

You start by exploring every nook and cranny of the house to discover all the stuff that needs to be organized. You find forgotten board games in the basement, mismatched socks in the bedroom, and dusty kitchen gadgets in the pantry. This is the Discovery phase, similar to discovering data within an organization. Just as you need to identify and locate all items in your home, companies need to know what data they have and where it resides.

Classification

With everything laid out before you, it’s time to sort. You and your siblings start classifying items: kitchen stuff like utensils, bedroom items like toys, and basement finds like old sports equipment. Your mom watches, nodding approvingly, as you label each pile with sticky notes.

This step mirrors Classification in data governance, where data is categorized based on type, sensitivity, and importance. Just as labeling items in your home helps manage them better, organizations label their data to improve organization and access.

Policy

Next, your mom introduces some Policies. "Broken utensils go to the trash, old toys get donated, and anything useful gets organized properly," she says. She outlines rules for what to keep, what to discard, and how to organize the rest.

In data governance, policies are similar. They define how data should be handled, what data should be retained, and what can be deleted. These policies ensure data is managed consistently and efficiently.

Rules

Now comes the tough part—Rules. Your mom hires a professional team to help implement these policies. The team meticulously follows the rules: throwing away broken items, organizing kitchen utensils in labeled bins, and sorting toys into donation boxes.

In an organization, data stewards and data owners are like this professional team. They are responsible for enforcing data policies and rules, ensuring data is stored, accessed, and maintained according to the established guidelines.

Metadata

As the professionals work, they label each box with its contents and the number of items inside. This labeling is like creating Metadata—data about data. It helps you quickly find what you need without opening every box.

In an organization, metadata serves a similar purpose. It makes data management and retrieval more efficient, providing context and meaning to the stored data.

Profit

Finally, you look at the fruits of your labor. The house is organized, clutter-free, and you even have some items ready for a garage sale. Your mom beams with pride. “We can make some extra money by selling or renting out these items,” she says.

This step represents Monetizing data in an organization. Well-managed data can provide valuable insights, improve decision-making, and drive revenue. Just as renting out unused items can bring in extra income, leveraging well-governed data can fuel business growth and profitability.

Scaling Up

Your mom is thrilled with the results and has a new idea. “Why don’t we offer our organizing skills to the entire neighborhood?” she suggests. You create policies for organizing other homes, sometimes incorporating local community guidelines to ensure consistency.

Similarly, organizations often scale their data governance efforts beyond individual departments to the entire enterprise, incorporating external regulations and standards to ensure comprehensive and effective data management.

Conclusion

In this story, your mom, the CDO, sets the vision and policies for managing household items (data). You, in the management role, oversee the implementation by hiring a team and ensuring the rules are followed. This journey of organizing your home mirrors the steps of data governance: discovering, classifying, creating policies, enforcing rules, managing metadata, and finally monetizing the organized data. By following these steps, both your home and any organization can achieve greater efficiency, consistency, and value from their data assets.