Dalberg Data Insights analyzes anonymous mobile and satellite data, helping communities better direct resources where they are most needed. Its tools are used to fight the spread of infectious disease, strengthen food security and build more sustainable cities. Meet the cofounder Rositsa Zaimova, a 29-year old data innovator.

Rositsa Zaimova made this year’s Forbes 30 under 30 list of the brightest young business leaders. The 29 year-old innovator has co-founded Dalberg Data Insights, the Big Data entity of the strategic advisory firm Dalberg.

Rositsa’s startup leverages disruptive technologies such as AI and Blockchain to tackle important social problems. The Bulgarian-born entrepreneur says building trust with providers, funders and users is key in the new field of Big Data for Development.

Ralitsa Vassileva: How would you describe your venture?

Rositsa Zaimova: Dalberg Data Insights is the Big Data entity of Dalberg Group, active in building data products that inform policy makers and development actors worldwide. Throughout the world and particularly in developing countries, policymakers, NGOs and other institutions often lack the right data to tackle important social challenges – how to most efficiently direct resources after an earthquake, for example, or how to contain a disease outbreak. Conversely, extensive and rich data sources exist behind the firewalls of private companies, such as mobile phone operators. By partnering with private companies, we access their data sources without compromising the privacy of customers or revealing proprietary information.

RV: How did you make it financially viable and scalable?

RZ: Actionable and real-time insights are key for policy makers and development actors. We are working on the topics of food security, disease surveillance, urban planning with UN Agencies, Inter-American Development Bank, USAID, etc. It’s usually on a project by project basis. However, we have also developed a few algorithms which are easily replicable, such as the epidemiological models for disease surveillance.

RV: Which obstacles did you have to overcome, and how did you go about that?

RZ: Good quality data that is real-time is usually in the hands of private companies and it is very challenging to access. It takes time to build relationships and make the case for data-for-development. Once we get access to the data, anonymise, aggregate, analyze it and turn it into insights, many public actors we are working with do not trust the insights unless they are correlated with their own data, which is often in the form of surveys. Again, it takes time to build relationships and trust.

Our ambition is to capture the social value of private data worldwide

It is a new field and advocating about it, showcasing the success stories and being open about the biases are critical to building the ecosystem for data-for-development. To be able to access data in a secure and sustainable manner, we are working on Data-as-a-Service model (DaaS), which we are piloting in Uganda and plan to scale geographically.

The ecosystem in data-for-development in emerging markets is very complex. It usually involves a data provider (e.g. a telecom operator), a funder (like USAID), an end user (like the Ministry of Transport) and a data innovator (Dalberg Data Insights). Aligning with the various actors on requirements, budgets, data privacy and security aspects is very time consuming. To manage the complex ecosystems, we are spending time with the end users on-site to really understand the problems and co-design the right data tools with the users.  

RV: What has its social impact been so far?

RZ: Our data tools have been used by 15+ different public and development actors across East and West Africa, Brazil, Bangladesh and Haiti. They have been used to predict the spread of infectious diseases in Brazil and West Africa, estimate food production in Northern Uganda and design more sustainable cities in Uganda and Haiti.

RV: What is your next goal?

RZ: Our ambition is to capture the social value of private data worldwide. Two next steps for us are – 

  • Piloting the DaaS model mentioned above, learning from it and scaling it geographically.                
  • We are working towards productization/standardization of the existing solutions to ensure replicability and scalability.


This interview is part of the series “Meet the New Digital Leaders.”