How can you use cloud-based BI platforms for data storytelling?

Recentemente, mergulhei na explora??o dos recursos avan?ados das plataformas de Business Intelligence (BI) em nuvem para storytelling de dados. Destaco a utiliza??o de técnicas de visualiza??o interativa, integra??o de dashboards personalizados e ferramentas de análise preditiva para criar narrativas robustas. A capacidade de alavancar APIs e integra??es para acessar dados em tempo real também se mostrou crucial para a constru??o de histórias de dados dinamicas e em camadas. Estou ansioso para compartilhar mais insights sobre essa abordagem e continuar explorando como maximizar o potencial das plataformas de BI em nuvem para storytelling de dados.

Participei recentemente da cria??o de narrativas de dados utilizando recursos avan?ados de storytelling em plataformas de Business Intelligence (BI) em nuvem. Destaco a importancia de explorar técnicas como a narrativa guiada por dados, a constru??o de sequências de eventos e a visualiza??o de histórias em múltiplas camadas. Além disso, a aplica??o de algoritmos de análise textual e de minera??o de dados enriqueceu as narrativas com insights adicionais. Estou entusiasmado para compartilhar mais sobre essa prática e continuar a explorar o potencial das plataformas de BI em nuvem para storytelling de dados.

Select a cloud-based BI platform that offers robust data visualization and storytelling features. Popular options include Tableau Online, Microsoft Power BI, Google Data Studio, and Looker.

The abundance of options in cloud BI causes indecision. Although platforms advertise self-service visualizations, their governance, scalability, and tooling differ greatly. Give more importance to practical testing centered around your real use cases than to reading brochures. Take stock of the technological infrastructure, analytics users, and data sources that are currently in place. Describe the kinds of analyses now being conducted that could be improved with improved BI. Project future data quantities and the amount of accessibility needed. Make a shortlist of two or three platforms that suit your demands both now and in the future. Provide complimentary trials and allow both experienced and novice users to test the system.

Before creating your data story, ensure your data is clean, organized, and relevant to your narrative. Use the BI platform's data preparation tools to clean, transform, and integrate your data sources.

Na minha opini?o,a ênfase na sele??o da plataforma certa, levando em considera??o fatores como fontes de dados, visualiza??es desejadas e facilidade de uso, é crucial para garantir que os recursos atendam às necessidades específicas do usuário. Além disso, a importancia de preparar e limpar os dados antes de contar uma história com eles é destacada, ressaltando a relevancia da precis?o e consistência dos dados na tomada de decis?es informadas. Por fim, a necessidade de definir claramente o público-alvo e os objetivos da narrativa de dados é abordada, reconhecendo a importancia da abordagem.

Soiled data undermines even the most sophisticated analytics. Learn what's going into your data lakes and warehouses before beginning any cloud data analysis. A profile that considers governance, correctness, consistency, and quality. To create a virtual data team, gather cross-functional data stewards. assemble in the cloud DBAs, analysts, data engineers, and leaders from the line of business. Discuss definitions, guidelines, and corporate policies. Fill in the gaps with data mapping, tagging, ETL, and glossaries. Avoid over-engineering metadata at first. High-value metrics that are in line with decisions and culture should be used first. By using ratings, descriptions, and sharing, assist users in curating and enriching certain data sets.

Not the data, but the audience is where the art of data storytelling begins. Prior to creating engaging stories, ascertain who would be the recipient of the insights. Which choices do they affect? Which metrics direct their efforts? Where is their lack of visibility? Interview target users from various business areas and roles. Examine their present methods for obtaining, evaluating, and using data. Determine both quantifiable and unquantifiable blind spots that affect performance. Take note of the feelings associated with particular numbers. Next, make clear what the main goal of narrative is. Does it reveal any trends? enhancing the quality of the data? Motivating action?

Understand who your audience is and what you aim to communicate with your data story. Tailor your narrative and visuals to resonate with your audience's interests and goals.

Data visualizations should not only demonstrate technical proficiency but also educate and motivate viewers. Where to begin, though, when there are so many methods to show data? Steer clear of complex charts that improve "cool" factor but not understanding. When it comes to leadership, clarity usually triumphs over inventiveness. Key messages should be emphasized and the audience should be served by design decisions. Use basic graphs like bar, line, pie, and scatter plots that are related to business indicators for wide-ranging communication. To highlight patterns, use tree maps and heat maps. Encourage user-controlled involvement using drill downs and filters.

Choose appropriate visualizations that effectively convey your data insights. Utilize the BI platform's visualization tools to create compelling charts, graphs, and dashboards. Pay attention to design principles such as clarity, simplicity, and consistency.

Develop a coherent storyline that guides your audience through the data insights. Use annotations, text boxes, and storytelling features provided by the BI platform to provide context, highlight key findings, and explain trends or patterns in the data.

Share your data story with stakeholders using the collaboration features of the BI platform. Distribute interactive dashboards or reports via email, embedded links, or scheduled updates. Encourage feedback and collaboration to refine your narrative and insights further.