Data as a resource

1. Data as a resource

Welcome back. Data is a precious and powerful resource to individuals and organizations. It enables them to succeed at an unimaginable scale. For a novice data user, realizing the value of data can be daunting.

2. Overwhelming data

One of the main takeaways from working with data should be that it is often too large to work effectively with in its raw form. Even simple analytical tasks can require hundreds or thousands of records. More complex tasks can be millions or even billions of records. To understand a dataset, you must be able to summarize the data into smaller pieces of information to make informed decisions.

3. Summing things up

Aggregations achieve this goal of translating raw data in a way that can be more easily understood. A simple average is a typical aggregation that most people encounter daily. Other common aggregations include totals, also known as sums, minimums, maximums and modes. Aggregations allow you to focus on a specific attribute of the dataset. Distilling large amounts of data into a more usable form is essential for success with data.

4. See the big picture

These simple aggregations are just the beginning of what you can do when summarizing data. Within organizations, aggregations often appear as metrics, benchmarks, or key performance indicators (KPIs). These data measures are just aggregations at their core that aim to distill business processes into something measurable and actionable. It is critical when dealing with aggregations in an organization to understand the business logic behind the metric itself. Both new and experienced data practitioners often overlook this. Knowing how the aggregation is created or what assumptions it makes about the dataset is surprisingly helpful information for many investigations.

5. Curiosity

Being curious about the aggregations around you will help you unlock a better understanding of the value of data that impacts your life. Take a moment to trace a report's origin or uncover the assumptions behind a KPI. Why was a benchmark set the way it was? The data flows around us are genuinely awe-inspiring if you take the time to look.

6. Data flow

The data flow within an organization can be highly complex, coming from many different source systems, processed by other systems, and then displayed in entirely different systems. The field of data management aims to wrangle these complex pipelines and create a unified approach to utilizing data as a resource. Many domains within data management are responsible for different areas of data. These domains vary slightly between industries and organizations, but the most common ones are data governance, data quality, data privacy, and data security.

7. Data domains

Each domain serves a vital purpose in ensuring data is utilized to benefit the organization. Data Governance seeks to ensure that data is consistent, trustworthy, and isn’t misused. Data quality ensures that data is accurate, valid, complete, and consistent. Data Privacy and security go hand in hand to oversee data access, use and protection. Ensuring data is treated as a valuable resource is an essential task for every organization and the responsibility for everyone who relies on data.

8. Let's practice!

As you begin your journey with data, developing an awareness of how data is used and sometimes misused will help guide you toward success. Let's practice with some exercises.

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