is easy to install and operate, and you don't have to be a programmer to use it. The software provides you with simple examples to get started. Additionally, it can help you transform information downloaded from the internet about currency exchange rates, debtor lists, sports results, order lists, website visitor lists, and more.
One of the key advantages of using DB Maker
is its ability to structure information. The software can convert unstructured data into structured data that is suitable for use in databases. Structured data can help you analyze and manage information more effectively, which can lead to better decision-making and more efficient operations.
Another significant benefit of using DB Maker
is its time-saving feature. If you were to manually copy and paste information into a database, it would be a time-consuming process that could take hours or even days. With DB Maker, you can extract the same information within seconds.DB Maker
can also help you avoid errors that may arise from manual data entry. When copying and pasting data, you may accidentally omit or add information, which could lead to inaccurate data. DB Maker eliminates this risk by automatically extracting the information according to the defined parameters.
Furthermore, DB Maker
provides users with the option to convert multiple HTML files into a CSV or Excel file format for further processing in spreadsheet applications like Microsoft Excel. This flexibility enables users to analyze and manipulate the extracted data according to their specific needs and requirements, enhancing the usability and versatility of the tool.
When navigating the immense volume of information available online, it can be challenging to differentiate structured databases from ordinary text documents. However, two core elements— "Records"
—serve as distinguishing features that give structure to databases, facilitating efficient data storage and retrieval.
In the framework of DB Maker, a "Record"
signifies a unique set of data within a database, containing multiple attributes or data points. For example, in an e-commerce database, each record might represent an individual product, complete with various fields like product name, cost, description, and availability status. A single database could house numerous such records, each imparting unique information. "Fields"
, in contrast, are the discrete compartments within a record that store specific data points or attributes. In the context of a product record, these fields could include attributes such as SKU, brand, color, dimensions, and weight. Through fields, a database achieves an organized and structured format for data, simplifying the processes of categorization and retrieval. DB Maker
provides a range of settings for pinpointing records and fields during the data extraction phase. Let's delve into these settings,Options for Identifying Records:
- "Begin" - This feature enables users to designate a symbol or sequence of symbols that mark the commencement of a record. If you recognize that a specific string like "<TR" signifies the initiation of a new record in your source data, this option can be used to identify it. This is particularly beneficial for structured documents such as HTML, where distinct tags often indicate the beginning of individual records.
- "End" - DB Maker also allows users to define a symbol that represents the termination of a record. By doing so, you can precisely demarcate the limits of each record within the database, ensuring accurate data extraction.