As an open-source tool, it needs to have a large community behind it so it keeps evolving. If the framework allows us to do it in a more transparent and easy way, the adoption within the company will grow faster This is one of the most important features, in the end, as we will need to share the dashboards both internally and externally. If we want the framework to take root within the company, it needs to be user-friendly, personalizable, easy to use, easy to admin, … In order to better understand the data we are analyzing, a large variety of charts will allow us to get and share insights in a more efficient way It’s important to be able to connect to as many sources as possible, such as databases, upload CSVs, … In order to understand which visualization platform better fit our needs, we defined the following proxies as evaluation metrics: This even allows us to incorporate external information and use it along with our data. The dashboard layer is last layer and is independent and focused only on visualizations, without storing any complex logic, this allows us to switch between visualization frameworks more easily.Įven if we need to access the raw data or create long-term visualizations on dashboards from processed data, this dataflow covers all our needs so far. All the complex rules and calculations will be done by our ETL and loaded into our data warehouse in a format that is easy to read by the top layer. Regardless of the source of the data, our goal is that the Dashboard creation process is equivalent for all of them, and in order to achieve that we have designed a dataflow focused on visualizations. In this post we will try to cover the most important aspects to consider, such as connections support, chart diversity, sharing features,…Īt Jobandtalent we have different data needs depending on the team, these needs have defined our dataflow. One important step in this process is choosing the right data visualization tool.
You need to create processes that control huge and complex data flows, as well as finding resources to give it structure and meaning, as we mentioned in other posts. As a company like Jobandtalent grows, the data that it generates grows with it exponentially.
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