Data Culture in the Tech Era

This content originally appeared on DEV Community and was authored by Julian

Working in data and technology is highly sought after these days, especially with the massive implementation of tech tools and the vast amount of information generated. In this post, I’ll share relevant aspects that I believe should be taken into account before starting deliverables and requesting projects with internal teams.

Data Culture

It is the foundation of all data implementation. Beyond releasing new features every day or implementing new technologies, we must be able to understand and assist the organization in a general way. Primarily, we need to foster a healthy data culture in which the entire team of a company is involved, not just executive levels, but also managerial and collaborative ones. This will make it clear who the users involved in the structure of data project definition will be, as well as the processes that will be improved and the technology that will be necessary, from which we can gradually dispense.

Business Alignment

Added to the executive sponsor, having business alignment is what will give us the opportunity to know how everything we do is solving real problems, contributing to a better work area, facilitating problem-solving, and optimizing time and resources. This business alignment should be focused on understanding from the business side what they are currently doing, using, what hurts them, what they lack, and why they use what they currently have. This last point must be primordial to improve current processes and not work redundantly in the future.

Content Management

Now, the relevance of understanding what strategy works for us in the business is where everything will take shape. Where do we start? What works for us? How do we divide and assign tasks and jobs? Right here, we analyze everything obtained from the three topics previously raised. According to Microsoft (https://learn.microsoft.com/en-us/power-bi/guidance/fabric-adoption-roadmap-content-ownership-and-management), we can have three ways to handle this content: Business-led self-service BI, managed self-service BI, and Enterprise BI. Depending on the strategy we choose, it will influence our operational model, our CoE, etc.

Delivery Scope

Now that we know how the team will be managed and what strategy benefits us, we’ll review how we’ll deliver the reports. For this, we have possible four levels of scope, starting from fewer to more users: (Personal, Team, Departmental, and Enterprise).

Conversely, for creating content at each stage, it is expected that the greater the number of consumers, the fewer creators per level. This is to have greater control and governance over the reports.

Center of Excellence

To clearly manage the delivery of reports, we must create a CoE that allows us to evangelize the company’s people with our data-driven culture, train them, guide them, and educate them so that they have good practices when creating their reports and the risks of incorrect use of data or visualizations are minimized.

Governance

It is a very open topic; however, it can be summarized that its objective is to govern what users do with the data, ensuring that the company’s data is well managed. For this, we must promote users to be able to work with certain internal measures that align with the organization, have consistency in documentation, deploying, and standardization of processes, and added to this, have a reduction in possible data leaks beyond the limits set by the organization and the BI team.

What do you think about these aspects? Share your thoughts in the comments and let’s have a productive discussion!