How Brainly’s Data & Analytics Department Uses Data for Decision-Making

Dare IT x Brainly
2022-05-13

The modern student looks to various sources for knowledge - but one of the best ways to learn is through a conversation with an educator. That’s what Brainly is about - connecting those who are learning with those who teach.

At Brainly, data is the key to decision-making, for both internal matters and determining how to best help their users. Understanding the roles related to Data Analysis, Data Science, Data Engineering, or Data Governance helps us to better understand how Brainly uses data and why it’s crucial. We interviewed three Brainly data experts from the Data & Analytics Department: Ewa Bugajska, Senior Lead Data Analyst in the Analytics Center of Excellence, Katarzyna Bodzioch-Marczewska, Solutions Architect in Data Governance, and Tomasz Sienkiewicz, the Director of the Data & Analytics Department.

What can you tell me about your Data organization - what makes it so unique?

[TS] We see that companies have different approaches to how the Data or Analytics teams operate - quite often it’s either a centralized or a decentralized model. In a centralized model there’s one Data team that receives requests from the whole organization; in the decentralized model all Data experts are embedded in the business units they’re supporting and they don’t work together.

What makes Brainly unique is our hybrid organizational model in terms of how we use data and how Data Analysts work. On one hand, they’re embedded in teams, working with products, marketing, and more. At the same time, we have a central team to ensure that all Data Analysts are able to cooperate and share knowledge with each other, work according to similar standards, and are hired and onboarded using a standardized process.

How are Data teams set up at Brainly?

[TS] Basically, our data teams are divided into 3 main areas. The Data Analytics team helps stakeholders make data-driven decisions. Data Analysts analyze data, draw conclusions, find opportunities, and based on these, stakeholders make decisions.

Our AI/ML team uses data to build ML-based products, mostly focusing on how to use data to build solutions for end-users. And Brainly’s Data Engineers make sure that data is collected, transformed, and stored properly.

Can you tell us a bit more about how the central Data Analytics Department is divided?

[TS] There are 2 areas - the Analytics “Center of Excellence” and Data Governance.

[EB] My area is the Analytics Center of Excellence, where we make sure to hire the best data analytics talent, in cooperation with our Talent Acquisition team, and provide them with an onboarding experience that prepares them for working with our data and systems. I support Data Analysts’ professional growth, define career paths, organize opportunities for the analysts to share and acquire knowledge, as well as lead initiatives, focused on standardizing some of the work that all analysts do, regardless of the team they work in.

[KB] My area, Data Governance, is about controlling some aspects of our data management system. I build policies and processes to make sure our data quality meets our standards and our data is safe but accessible for everyone who needs it. Right now, my main focus is the data catalog that we’re building with Data Analysts and Data Engineers.

Why is data so important to Brainly and how do users benefit from it? 

[TS] The way I see it, when you run a business, you make decisions. The higher in the company hierarchy, the more important the decisions - they’re made in different ways, based on your gut, past experiences, and biases. Most importantly, you make decisions based on insights and data.

Generally speaking, companies that use data to make decisions tend to be more successful. This is how we act at Brainly - we use data to make big decisions so we can grow and build quality products as quickly as possible.

What does Brainly do to support their “Data Culture”?

[TS] We support access to and the understanding of data. For example, Kasia’s project increases accessibility, and Ewa’s A/B testing project helps us understand that data.

[KB] We support the growth of the Data Community. One way of doing that is gathering tribal knowledge about data and building a data catalog. The data catalog tool that we’re currently onboarding will help everybody discover data faster, understand it and collaborate around it. It will be a trustworthy and easily accessible source of information about the data for everyone in Brainly.

[EB] One of the projects that we’re currently running in partnership with the Product division is focused on improving our approach to running A/B tests within the whole company through building a common framework, proper education, organization, and a standardized approach to reporting. Thanks to that, our Analysts can be more efficient when summarizing the A/B test results, and business stakeholders understand the outcomes so they can make data-driven decisions faster.

Can you describe Brainly’s company culture and how you work?

[EB] Brainly is a company with a great mission and amazing people who help to realize it. You rarely have the privilege to work with people who care about each other and the company’s mission and who are so open to learning and sharing knowledge. 

Since we’re an education company, it may sound obvious that learning is a big deal for us, but any initiative that is focused on sharing knowledge is well received. We learn and grow together, in more than just our own area of expertise.

Do you feel the Brainly value “Stay Curious: Always wonder. Always explore” represents your work at Brainly?

[TS] Absolutely. I like to say, “Win or learn” instead of “Win or Lose”!

[EB] Even though we aren’t a product team, we still have regular retrospective meetings to identify if there are issues we should address right away, and we also actively ask for feedback within the processes we participate in.

[KB] We talk about technical problems and review our solutions. Nothing gets swept under the rug. Our team members are open to doing it because they feel they are in a safe space. It’s always a great opportunity to share experiences and learn from each other.

Subskrybuj newsletter