Decoding Google’s Software Development Methods: The Cpm Scheduling Debate

Decoding Google’s Software Development Methods: The Cpm Scheduling Debate – TL; dr: Data visualization for complex systems is a two-dimensional coding system. Thus, data visualization readers must go through specific decoding processes to understand and interpret the underlying data and systems. To properly manage data visualization, we as designers, developers or data scientists need to understand the decoding process.

Many of the complex systems we face today, such as production processes or customer life cycles, are invisible. Only by directly collecting and analyzing data can we understand the system so that we can identify and solve problems.

Decoding Google’s Software Development Methods: The Cpm Scheduling Debate

Information graphics can be a friendly way to understand and access this information. They also need to use technology to read and interpret data.

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Visualization of data is the final result of a long and complex process, where many obstacles must be overcome: integration of data from different sources, cleaning, flexibility of use and sometimes, statistical calculations. Then we excitedly watch the colorful and exciting show and think, ‘Yes! For the first time, our data is visible! “We’ve done the hard work and presented the user information on a silver platter. The user is now comfortable and nothing can go wrong, right?

However, the journey is not over. Informational images can be misunderstood or not understood at all. If you’ve seen it before, either as a reader or a video creator, then you should read on.

From my perspective, a lot can go wrong. For more than ten years I have developed web users for information products and I have had the painful experience that my visualizations sometimes miss the mark. Users do not understand the visual language, cannot understand the nature of the information, or cannot understand the meaning of the information presented. In some business intelligence operations, we found that video was rarely used afterwards. But why? How can you improve?

Let’s take a step-by-step look at the process of creating and reading video data, encoding and decoding cycles:

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Creating data visualization does not start with the data, as is often assumed, it starts much faster, with the background system. Behind every information in the world there is a system. It is usually invisible and very difficult.

Take the Internet for example. No one can handle just one stream of visitors. First, we need an idea; The main map of this page, to select the objects, objects and objects that we want to measure. There are many things that can be interesting, visitors, websites, shopping carts and products. But not everything we can measure technically, like the thinking of a website visitor when he decides to buy a product in his cart. It would be nice to know!

Knowing what and what we can and want to measure, we decided to choose the parts of the system that will be represented in our numbers. If our mind map is incomplete, inaccurate, or simply wrong, we cannot ask the right questions and measure the truth.

While we have achieved the first step of information acquisition, we must realize that we cannot capture all the intricacies of the system. The data is not a complete representation of the system, it is a small representation.

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Next, we build a data model. Here, again, a lot is lost, because the information system cannot cover all aspects of the world. Anyone who has done it knows that full data modeling is a dangerous beast. That’s why we choose to keep it as simple as possible and leave out the unimportant information. So in the end, we get a nice and clean model that shows little information about the system. By changing the underlying information in our data structure, the data depth is reduced by a factor of two.

After collecting the data and storing it, we finally make our video. Also, the amount of available data stored in the data table must be filtered, because the table technique can only display a small number of items and attributes. But this is not the only reason why we should reduce the amount of data presented: Graphic design reflects human content. We need to focus on the message we want to convey, the needs of the audience and their specific abilities. So we have to select a small part of the available data for each table: Maybe one or two characteristics, such as the product and its number of sales per day.

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