What do you do if you need to convey complex data insights to non-technical stakeholders in Data Management?

First and foremost action is to understand the level of the audience and accordingly use the language to explain. Present most important insights using visualization (graphs, charts etc), frame the data to illustrate the significance of business and project.

Communicating complex data insights requires simplification and translation of findings from the data analytics language to the business language. This can be accomplished effectively through data story telling which focuses on narrating outcomes from the past and the present by keeping it interactive with the target audience. With the use of appropriate graphic visualizations, story boards, and analogies, it becomes easier for non-technical audience to understand trends, patterns, and other observations from the underlying data enabling them to take decisions in the future. Most importantly, arrange the order of insights in a manner where it is easy for the audience to comprehend, compare, correlate, categorize and take meaningful actions.

One thing I found helpful when doing data analysis was the intuitive way Jupyter Notebooks simplified data problems and provided a guided way for story telling. Using PySpark to query and presenting the results with proper narrative helps enormously.

To convey complex data insights to non-technical stakeholders in data management, focus on simplification and clarity. Use layman's terms to explain concepts, employ visual aids like charts and infographics to illustrate key points, and tell a compelling story that links the data to real-world impacts and decisions. Highlight actionable insights and facilitate an open dialogue for questions and feedback. This approach ensures that stakeholders can grasp the significance of the data insights and how they can be applied to drive business decisions.

Acredito que um fator essencial para transmitir insights valiosos é conhecer as partes interessadas e as expectativas que estes possuem sobre o projeto, elaborar um bom storytelling voltado aos dados para transmitir com clareza e transparência os principais insights levantados, sem dúvidas irá colaborar para o seu sucesso.

In implementing filtering ensure various data points and data elements ie age, date, region, quantity, gender etc can be used with ease by the audience. The interactive dashboard helps to avoid cognitive overload hence making data meaningful. Dashboard filtering used on powerful platforms/tools such as Power BI allow visualization of filtered data.

When presenting findings to non-technical audiences, it's crucial to simplify the data presentation as much as possible. Rather than delving into the intricate methodologies or analytical approaches employed, focus on clearly communicating the core results and actionable recommendations derived from the analysis. Non-technical stakeholders are primarily interested in the key takeaways and practical implications, not the technical work behind the scenes.

Simplificar a visualiza??o dos dados usando painéis é algo que sem dúvidas agrega muito, seguir boas práticas como por exemplo: n?o incluir textos longos, n?o exagerar na diversidade de cores, excesso de imagens, etc. Irá fazer com que seus dados transmitam insights nos primeiros segundos da apresenta??o. Outra forma de simplificar é fazer uma limpeza de dados assertiva, manter somente o que realmente importa para os stakeholders.

Apresentar painéis ou planilhas de forma clara e de fácil entendimento, sem dúvidas é uma das partes mais importantes. Quando falamos de um projeto para trazer insights envolvendo dados, lembrar sempre de utilizar técnicas para uma boa apresenta??o como: evitar textos grandes, excesso de cores e imagens, técnicas de visualiza??o, etc.

Use different chart types ie bar, pie, line to visualize. Bar chart for comparison, pie chart to show distribution and line chart to show trends.

Consider using the Rate of Revelation as a framework to narrate your data findings. Use foreshadowing and paced reveals to make the narrative more digestible. This is particularly useful to improve stakeholder retention and engagement when working with complex data findings (eg counterintuitive analysis results).

The Drill Through feature for Power BI visuals is a great way to facilitate mini-narratives and promote user engagement with data. From experience, guidance and user-centric design of visuals that use this feature provides value to users sooner than leaving them to figure-out an otherwise poor UI.

Enhance how audiences interact with data through use of filtering based on different criteria ie time, age, location, price, quantity etc. These should be relevant to their search preferences, requirements and analysis of data.