Scraping Web Data
Sometimes there is valuable information available on web sites that do not have a download feature. Appian Analytics can help you get information from a website in a high volume, multi-page and/or in an automated process. Web scraping or "spidering" a web site can be done for you a one time or ongoing basis as needed.
There are a range of applications for this type of approach. Into he occasions when there is valuable data is stored in web pages at one or more web sites automated scraping rather time-consuming and error prone data entry can be a vastly superior alternative. These web pages might contain data that you want to include in an analysis, spreadsheet, or database. Getting the data into a the correctly formatted spreadsheet, database, or flat file can be time consuming and often clients will resort to manually inputting the data.
Appian Analytics can get the database created for you by scraping the web sites and parsing the data into data fields. The type of data that can be scrapped includes tabular and formatted data but also can include non formatted data. Sometimes the data might be stored across a number of web pages or in an irregular format. Regardless, there are ways to access that data and to do that one time or every week, month or at whatever interval your project requires.
Web Scraping Examples:
Keep in mind that not ONLY simple, single web sites can be monitored and scrapped or mined for information but in addition very large, multi-page websites and data from a large variety of websites can be scraped. This process can create a very easy to use spreadsheet or database that you can more easily use for your analysis or information gathering project.
Example Screen Shots of Web Site Data Scrapping:
Web site data that is already formatted in a table on the website is the easiest data to scrape. The tabular structure provides the organization elements needed to effectively categorize the data once its scraped from the site. Even though its important to understand that if the data is contained on multiple pages that it must be "fit" together properly for use in a spreadsheet or database. As a result of this, simply scrapping the data itself is only the first step to making the data useable by analytic applications, reporting, and other decision making.
Additionally, you may require some type of data reformatting, text labeling, data organization, or other types of calculations or analysis on the data. These processes can be performed in addition the web scrape itself and therefore give you a more simple dataset to use in the application of your choice.
A print image is a data file report that is created for presentation and printing. Often, older systems, especially mainframes, will output these types of reports. Generally, they are created using ASCII characters set in the file in such a way that it literally looks exactly how it will print. Again, this was the original way of creating reports for distribution via paper.
The issue is that there may be valuable information stored in these print image files that is not easy to analyze in separate spreadsheets and databases. Often, to accomplish an analysis with this data, the user needs to type the data from the print file into a spreadsheet or database before being able to perform any work.
Unstructured content is a common name for information or data that lacks a consistent and systematic organization. This information may be text comments such as product reviews, service reviews, product ratings, or even blog entries and comments. Additionally, unstructured content could be actual data that is just not organized clearly in table structures that are easy to move into a spreadsheet or database table.
Without consistent and systematic organization, the information or data cannot be analyzed effectively with common data analysis tools such as spreadsheets, databases, and other analytical applications. Therefore, to gain maximum value from unstructured content you either need to use special text mining and analysis tools or extract the content and transform the content into a structure that will facilitate analysis.
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