directory
What is data visualization?
2. What are the large screen analysis software for data visualization?
3. Do you need to write code to achieve data visualization?
Four, data visualization needs to pay attention to the problem
Tech companies aren’t the only ones that need to focus on data analytics — any type of business should. Analyzing business information to facilitate data-driven decision making requires what we call business intelligence software or BI tools. In simple terms, BI is a set of tools and methods for extracting raw data from its source, transforming it, loading it into a unified storage system, and presenting it to users.
Everything that happens before the actual data is presented in visual form can be thought of as the underlying infrastructure, known as the data pipeline. The main part of the pipeline is the extract, Transform, load (ETL) process and its tools. You can think of it as the back end of any BI system. Then the front end of the system is the user interface, and the data is finally presented to the user in visual form, which can be directly used as data visualization Kanban or data visualization large screen for enterprises or individual users with data analysis requirements.
What is data visualization?
Data visualization is the practice of converting raw information (text, numbers, or symbols) into a graphical format. Data visualization has a clear purpose: to show logical correlations between units and to define tendencies, trends, and patterns. Depending on the type of logical connection and the data itself, the visualization can be done in a suitable format. Therefore, it is very simple, and any analysis report contains examples of data interpretation, such as pie charts, comparison bars, demographic charts, and so on.
In most cases, visuals are created manually with the appropriate visual software, be it PowerPoint or Photoshop. However, the core use of large screen analysis tools for data visualization is still in the analytical world. For this reason, data visualization has become the standard way to introduce information to users through BI interfaces (data analysis tools).
2. What are the large screen analysis software for data visualization?
There aren’t many completely free options on the market. But most of the data visualization large screen analysis software can be free trial, the following small series to introduce a few domestic and foreign use rate is relatively high data visualization large screen software tools:
1. Yixinhua Chen Cool screen
Cool screen is a new generation of data visualization products independently developed by Yixinhuachen, which can flexibly and quickly produce various kinds of interactive conventional screen and large screen visualization, built-in more than 100 cool components and 3D effects, so that the data “leap on the screen”, get a more vivid and intuitive visual presentation. Yixinhuachen cool screen function:
1) Rich visual components
2) Cool 3D effects
3) Visual components and templates that can be combined arbitrarily
4) Dynamic interaction
5) Low code, without complex code writing can realize data visualization
2. Microsoft Power BI
It’s not uncommon for Microsoft to give away its software for free, but there are minor pitfalls. You don’t have to pay a dollar to get all the features, but all generated reports will be published to Microsoft Gallery. So basically, all of your reports will be publicly available. Power BI functions:
1) Drag and drop interface
2) Desktop applications
3) Extensive list of local integration with data sources
4) Customizable reports
5) Incremental data update
6) Complete BI ecosystem as a service in Power BI Pro
3.Tableau Public
Tableau Public is also similar to Microsoft Power BI — full functionality for sharing all the data you publish on Public services.
4.Google Analytics
This is perhaps the most accessible option for any user who wants to create visual reports. Google Analytics features:
1)Web applications
2) Drag and drop interface
3) Built-in integration with Google Analytics and other products from the Google Marketing Platform
4) Customizable reports
6) Shared access to analysis
3. Do you need to write code to achieve data visualization?
At present, most large-screen data visualization software on the market do not need to write code, and many analysis and visualization processes use existing tools and large-screen template components. The four data visualization analysis software mentioned above do not need to write code to achieve data analysis and data visualization requirements.
Four, data visualization needs to pay attention to the problem
If you decide to include visuals in your analysis, it’s important to understand some of the potential challenges that need to be overcome. If you are a manager or are responsible for implementing BI in your organization, understand some of the issues you may encounter before the actual data is available for visualization. Here are some key points you can’t ignore during data preparation.
In any process of software development, defining the required data and available sources is based on assumptions. The same goes for deciding whether to need a data warehouse and whether to convert data into multiple formats.
A simple solution can be found by testing at all stages of data processing. In data visualization, we must test assumptions that may directly affect the results of data visualization. These projects are:
1) Initial data type
2) The source of choice
3) Type of data source (query, continuous update, interim report)
4) Database/data warehouse architecture
All of these structural elements can be tested by a domain expert (ETL developer) in the domain, while assumptions can be discussed with a data engineer/data analyst.