What Is Structured Data Analysis?

Structured data is simply a database. It is easier to understand in combination with typical scenarios, such as enterprise ERP and financial systems; medical HIS database; education card; government administrative approval; other core databases.

Structured data, also called row data, is data that is logically expressed and implemented by a two-dimensional table structure. It strictly follows data format and length specifications, and is mainly stored and managed through relational databases. In contrast to structured data, it is unstructured data that is not suitable for representation by two-dimensional tables in the database, including office documents in all formats, XML, HTML, various reports, pictures and audio, and video information. Databases that support unstructured data use multi-valued field, field, and variable-length field mechanisms to create and manage data items, and are widely used in full-text retrieval and various multimedia information processing areas ^[1]

Structured data markup is a way for websites to appear better in search results. With structured data markup, your website can display rich snippets well in search results.

Search engines support standard structured data markup to provide users with a better Internet experience. The microdata markup on the webpage can help the search engine understand the information on the webpage, and it can be more convenient for the search engine to identify the classification and judge the relevance.

At the same time, structured microdata can allow search engines to provide a richer summary of search results, that is, detailed information that helps users with specific queries, and allows users to see important information about your products directly in the search results. For example: the price, name, inventory status (whether the product is available), reviewer ratings, and reviews of the product can all be seen directly in the search result summary.

These rich snippets help users see if a site is relevant to their search and can get more clicks on the page.

For example, in the search results, there are more factors such as star ratings, number of reviews, and prices, which will undoubtedly increase the professionalism of the website and increase the trust of customers in the website. The good exposure of the website is virtually invisible. This increases the click-through rate and conversion rate of the website.

1.Use HTML code tags

There are three main ways to mark up HTML code: microdata, microformats, and RDFa. However, for some foreign trade stations, the mark is mainly microdata, and in some cases the microformat is also used, depending on the type of page that is not used.

Using microdata markup

With microdata markup, there are two code formats: http://data-vocabulary.org/ and http://schema.org/. Since the data-vocabulary tag only supports Google search, and the schema also supports Google, Yahoo, Bing and other searches, we might as well call the data-vocabulary as the old version of the tag and the schema as the new version.

The current mainstream is markup using a schema. However, due to some items on the page (such as breadcrumb navigation), the schema does not introduce the corresponding markup code, so it must still be marked with data-vocabulary. In this case, the new and old code will coexist on the page code, but Does not prevent search engine spiders from crawling the page content.

With data annotation tools, simple content tagging is possible. Nine tag types are currently supported: articles, book reviews, events, local businesses, movies, products, restaurants, software applications, and TV sequels. During the operation, you can create a page set yourself, mark the type of page, and then Google will grab the content of the relevant type of page, you review and modify, if there is no problem after the modification, click OK to create and OK .