You’re an Information Systems professional. How can you take your data visualization to the next level? (2024)

I've found that data can be very helpful, but I would add that simplicity matters. One well thought-out chart with a good explanation can be much better than three charts that might overwhelm. Control the conversation and use the chart as a starting point, not the end.

Adding filter to data and keep the perspective near to available audience. Data can be filler to predict the accuracy based on depth and genuinely of available data. Subsequently data is not just few characters in the shape of information but it is small signage board to lead towards greater height to keept the ask under control before it become crisis.

1º and most important is data quality. for visualization efectiveness build simple and autómated dashboard on excell or PBI. know your audience and know the desired information output to be able to guarantee the desired impact on the audience.

Color coding might seem simple, but it can significantly transform reporting and boost its effectiveness. For example, at one of the AI companies, we measured various team metrics to improve their productivity, such as average velocity, say/do ratio, total features released, and total bugs found. To make these metrics more impactful, I suggested introducing color coding. Any deviation from the average by less than 20% would be highlighted in yellow, while deviations above 20% would be in red. These visual cues increased collaboration with the executive team, making them more interested in a detailed analysis of teams that needed support. And hence, Eng Ops review adopted this color coding approach across all teams.

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Os rótulos numéricos nas visualizações de dados são uma maneira fácil para os visualizadores entenderem rapidamente seus dados.Cores específicas adicionam clareza ao que os dados apresentam e podem tornar a análise de dados mais rápida. Ao criar um painel com vários gráficos, use a mesma cor nos gráficos quando eles representarem o mesmo grupo ou métrica.Duas abordagens para implementar consistência de cores em seus painéis:Modo fácil: Comece a implementar a escolha intencional de cores em painéis individuais.Modo difícil: Atribua cores específicas a métricas comuns em sua organização e use essas cores de forma consistente em todos os painéis e visualizações de dados.

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Building interactivity into a visualization can allow for self-service for your audience, and can impress. Instead of needing to tailor a set of visualizations for different purposes (or for different target audiences) you can elegantly display the information, and allow the user to explore the information. A well-designed tool can reduce the need for many additional tools. And will also leave a user more impressed than a static graph or chart.

A visualização interativa de dados não é apenas mais uma palavra da moda; é a arte de transformar dados brutos em visuais bonitos e dinâmicos. Com os projetos de visualização corretos, o que antes era uma mera imagem em uma planilha Excel pode ser transformado em uma representação animada e perspicaz, tornando a interpretação mais intuitiva e envolvente.Mas por que isso importa? Em um mundo onde o tempo é essencial, essas técnicas de visualização criativa oferecem uma compreensão rápida de análises complexas. Não se trata apenas de criar um design bonito; trata-se de criar uma narrativa que impulsione os insights de negócios e a tomada de decisões.

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Certifique-se de que o software possa se conectar a várias fontes de dados, incluindo bancos de dados, planilhas e serviços em nuvem. A capacidade de importar e integrar dados de diferentes fontes é crucial para uma análise abrangente de dados.Liveboards permitem reunir dados de várias fontes em um único painel. Isso fornece uma visão holística de seus dados conectando-se a bancos de dados, planilhas, fontes de dados em nuvem e até mesmo bancos de dados de terceiros.

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- In my experience I believe cross-collaboration & an efficient cloud data sharing method can allow various benefits. Especially to inter-linked systems which are inter-dependant on “Risk analysis” - the advantage of having visualised and far more in-depth micro-level data access, can enable a potential for great innovation niches to often sprout. - cross platform syncing and multi-platform embedding, helps data to be easily presented throughout various devices and upcoming technologies. - team growth, allowing teams to gain access to cross-cloud data sharing, analytics & collaboration. Enables greater oversight in team clusters whom manage specific projects and scales of these projects.

Data science is gaining importance these days. Data visualization tools are all about gathering raw data and converting the same into visuals. Being visual creatures, viewers can find colorful graphics to be quite appealing. Businesses can also convey messages quite easily and more effectively unlike plain numbers.Visuals also provide valuable information that can be absorbed effortlessly. It also helps specific datasets to become more appealing to users. Incorporating the same into business does not require any expertise. You just need to use the right tools and develop attractive charts, maps, diagrams along other visuals.

data visualization that assists clients capture key items from, proper use of design elements leveraging on AI can be helpful. All the listed options (using right charts, colours, interactive elements, collab software in line with practices) work in unison to enhance proper visualization. breaking the rules can sometimes create memorable visualization.

Top 10 Data Visualization Tools1. Tableau Public & Gallery2. HockeyStack3. Google Charts4. Google Data Studio5. Infogram6. Datawrapper7. D3.js8. Flourish Public9. RAWGraphs10. Dygraphs

As an Information Systems professional, there are several ways to take your data visualization to the next level, but I assume there is one above others to consider.Focus on user experience: Ensure that your visualizations are easy to understand and navigate. Pay attention to the design, layout, and color schemes to make the data more accessible and visually appealing.