Why embedding charts is so important?
Most businesses must analyze a plethora of information to understand what actions need to be taken. This is often done with the help of charts and other data forms.
While useful, the vast amount of statistics and visuals can sometimes make it difficult to comprehend what’s happening. It could also overwhelm your analytics platform. This not only will make your job more arduous but could slow down the analytics tool.
Because of this, it might be ideal to embed them, especially if you use a team analytics platform. This post will explore why embedding charts and data is important. You’ll also find some tips you can follow when doing so.
Embedded data takes intricate statistics and sorts them to put into an analytics platform. This way, when you need to address a certain aspect, you can add the data portion to it. The platform will automatically take this embedded data and blend it into the metric it’s placed in. Unlike similar data, embedded portions stay on the software rather than a hard drive.
Embedding might seem unnecessary, but it provides great benefits.
One benefit to using analytics platforms is that they assist them with interpreting figures. You’ll notice that thanks to this, you can easily understand your company’s data.
Embedding charts and data can do this simply by making the statistics more transparent. You can view various metrics that might otherwise go unnoticed or misunderstood. It puts them in an easy-to-read manner that can be clarified in seconds.
Another intriguing perk of embedded data is that it can boost your productivity. With it, you can get a detailed look at various aspects without having to make major changes. This allows you to test different components to see where you can improve. By doing so, you’ll notice that your company’s productivity will increase because you can fix weak areas.
You’ll also find that this feature could encourage your company to increase its revenue. Thanks to its visualization settings, you can understand where areas of concern might be. This is especially so around your customer’s experience. With embedded analytics, you can discern where to increase your outreach. You’ll also see where you’re popular with your clients, so you can boost these aspects.
Before setting out to embed data, you’ll want to consider a few things.
One of the most critical components to look at is the size of the chart or data units. If these pieces are too big, they could overwhelm the platform. This could cause it to crash. Before you begin the process, make sure to locate how big the file is. You can do this by clicking on it and selecting the detail tab. This will inform you of the piece’s size.
You might also want to look at the security details of the chart or data. For instance, when you transfer the piece, can you add protections? This includes passwords and encryption keys. If not, you might risk it being accessible to others.
Besides this, consider whether you can set permissions. Otherwise, some users might be able to adjust the pieces without your knowledge.
For those who plan to allow team members to access the embedded figures, ensure they are scalable. This allows them to monitor the data fluctuations. The platform should provide easy access to these settings so you can scale the figures as needed. Scalability will also tweak the algorithm so that the platform can quickly monitor the new measures.
While analytics platforms are built to quickly refresh information, sometimes it could take time. This is especially so if you plan to add or export large quantities of embedded data.
Loading times will vary depending on the platform, but many will provide a progressive loading feature. This will put the figure on the dashboard as soon as it has been embedded. This way, you don’t have to wait for the entire batch to load.
While linking and embedding might seem similar, there is a major contrast. A link only refers to a separate URL. On the other hand, embedding lets you take the same link but keep it on your platform.
On analytics platforms, embedding is ideal because it keeps you on the dashboard. If you click on a chart or data figure, you’ll stay on it. However, if there was a link in the chart, a new tab would open. By embedding charts and data, you keep things organized and in one place.
One characteristic that might make some hesitant to embed their charts and graphs is that they’ll be reconfigured.
The good news about embedding is that it will keep their aesthetics. It won’t remove certain components. It also won’t shrink the graph making it blurry. When you embed the figure, it will simply just make it easier to access.
Embedding charts and data from analytics platforms is easier than it might seem. Because these platforms tend to automatically embed the data placed on the dashboard, you can simply export the figures.
Before it’s sent out, it will go through an ETL (Extract, Transform, Load) configuration. This will prepare the data and create an output file. You can then submit it to a data storage folder where you can later refer to it.
To ensure that the conversion went well, do a quick test. This can usually be done by clicking on the piece and opening it. You should see it within the dashboard and uploaded properly. If not, you’ll need to redo the process.
Embedded analytical platforms are very useful. You’ll find that with them the embedding process time is significantly lowered.
However, there is a downside. Some embedded analytics platforms will only work with pre-embedded data. In other words, you’ll need to configure data before adding it to the platform. While this might take some time, it will ensure that everything syncs.
Keep in mind though this isn’t always the case. Many platforms, like Toucan Toco, help with embedding data instantly. You simply connect and add the figures and the platform will do the rest.
Embedding charts and data is essential if you want to better process your figures. It will also keep your analytics platform running efficiently. By keeping the information above in mind, you can easily embed and understand any data on the platform.
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