1. A robust data Infrastructure
Hi! In this video, we'll go through the role of data infrastructure in enabling data fluency across the organization.
2. Ecosystem enabling data products
Data infrastructure is one of the core pillars of the data ecosystem. Combined with the right tools and processes, data infrastructure enables the creation and sharing of data products. Data products make it easy for users to get what they need without having to dive into a very complex set of unprocessed data. They are defined as the resulting products from data processing, modeling, or analysis that are made available to users. These include curated or KPI datasets, dashboards, reports, and prediction models.
3. The meaning of data infrastructure
Data infrastructure makes these data products available and enables data-fluent individuals to use data effectively. In simple terms, data infrastructure refers to the hardware, software, databases, standards, and policies that collectively ensure data is available, reliable, and secure. Imagine data as water, and data infrastructure as the pipes and reservoirs that store and transport this water. It ensures data flows from where it's generated to where it's needed with the right quality and compliance.
4. Implementing a data strategy
Data-fluent organizations have a clear data strategy in place. This makes sure all the required data is collected and made available to users across the organization in the best way possible. This data strategy is clearly communicated to all data teams that are working towards delivering this strategy. Besides making the data available to users, the outcome of delivering the data strategy is to ensure a single source of truth of the data, and that the data is discoverable, compliant, actionable, and understood. Let’s delve into these components in more detail.
5. Enabling a single source of truth
A data-fluent organization ensures a single source of truth by creating one central place where all important data is stored, organized, and managed. Such as a centralized data warehouse. When users in the company need for example sales data or customer information, they go to this data warehouse. This prevents confusion and mistakes that can happen when different users use different versions of the same data from various sources.
6. Data standards and governance
To ensure data is reliable, consistent, and accessible data-fluent organizations focus on setting the right standards and governance. Let’s picture a bustling city where car traffic flows seamlessly. This seamless flow is thanks to the rules of the road, the traffic lights, the signs, and the well-defined lanes. In the same way, data standards and governance sets the rules of the road for data within an organization. Data Standards, are like the road signs and traffic rules. They provide the specific guidelines and formats that data should adhere to. Data governance is like the traffic management authority. It's responsible for overseeing and enforcing the rules and policies related to data.
7. Enabling discoverability
Data loses its value when people can't access it, lack an understanding of its context, or struggle to find the information they require. As the number of data products grows, data-fluent organizations typically use data discovery tools where users can effortlessly identify the data products they need. Through the discovery tools, users can also read about the meaning of the datasets, the meaning of each column, and the source of data, learn who owns the data product, and essentially understand the data before using it.
8. Operationalization of data products
Lastly, an important element of a strong data infrastructure is enabling a clear path to operationalization. The operationalization of data products is about turning an idea or a model into something practical that the organization can use every day. It's the process of making sure the data experts can deploy their data products and make them available to users that ensures monitoring, refining, scaling, and improving quality.
9. Let's practice!
Great! Now, let's reinforce what you've learned with some hands-on exercises to deepen your understanding of these data infrastructure concepts.