Configuración Inicial
Configurar Looker Studio y Conectar la Primera Fuente de Datos
Crear Gráficos en Looker Studio y Analizar Ventas
Conectar una Fuente de Datos desde Google Sheets en Looker Studio
Agregar Filtros y Controles Interactivos en Looker Studio
Diseñar un Dashboard Accesible con Looker Studio
Quiz: Configuración Inicial
Análisis, Optimización y Seguridad
Integrar Datos de Inventario y Analizar la Disponibilidad de Productos en Looker Studio
Optimizar el Stock en Looker Studio
Parámetros para optimización en Looker Studio
Combinar Datos de Ventas y Clientes en Looker Studio
Segmentación de Clientes con Campos Calculados en Looker Studio
Manejo de Seguridad del Dashboard en Looker Studio
Optimizar la Carga y el Rendimiento del Dashboard en Looker Studio
Quiz: Análisis, Optimización y Seguridad
Técnicas Avanzadas
Conectar Múltiples Fuentes de Datos en Looker Studio
Expresiones Regulares y Transformación de Datos en Looker Studio
Optimización del Dashboard para Dispositivos Móviles en Looker Studio
Visualizaciones Comunitarias y Navegación en Looker Studio
Storytelling con Datos: Cómo Contar una Historia en Looker Studio
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Implementing filters in dashboards is a powerful tool to customize data visualization according to the specific needs of each user. In the case of Freshmark, with its three branches and managers who need access to information relevant to their area, filtering controls become essential elements for efficient and accurate decision making.
Dashboards are fundamental tools for data visualization and analysis, but their true potential is unlocked when we can filter the information according to our specific needs. In the case of Freshmark, a multi-branch company, each manager needs to see only the data relevant to his or her area of responsibility.
To implement filters in our dashboard, we need to go to the "add a control" section. This functionality allows us to create different types of filters that will instantly transform all our visualizations without the need to modify each chart individually.
There are several types of controls that we can implement depending on the type of data we want to filter:
The choice of control type will depend on the nature of the data to be filtered. For example, to filter by branch, the drop-down list is very intuitive as it allows you to select one or more options visually.
To create a filter by branch using a drop-down list:
Once implemented, we can select a specific branch (e.g. branch 2) and all visualizations will be automatically updated to show only the data corresponding to that branch. It is also possible to select multiple branches simultaneously for comparisons.
Filtering by time period is especially useful for analyzing time trends:
This type of filter displays a complete calendar, similar to the date selectors used in booking systems. By applying this filter, the sales trend graph will display only the selected months, allowing for a more focused analysis.
In addition, this control offers predefined options such as "last 7 days" or "last 30 days", facilitating quick analysis of recent periods.
To filter by products, we have two main options:
This type of control allows you to search for specific products by typing their name:
However, this control has important limitations: it does not offer suggestions and does not show the available categories, which makes it difficult to use when we do not know exactly the names of the products.
A more effective alternative is to use a drop-down list:
This option displays all the categories available in the dataset, making the selection easier even when we do not remember the exact name of the product.
Buttons are versatile controls that can perform various actions:
To implement a PDF download button:
This functionality allows you to easily export the entire dashboard for sharing with other team members or for presentations.
Implementing filters and controls on dashboards transforms the way we interact with data, allowing for more accurate and personalized analysis. For Freshmark, this means that each manager can now focus exclusively on the information relevant to their branch, improving efficiency in decision making. We invite you to experiment with the different types of filters and share in the comments which ones you find most useful for your own data visualization projects.
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