If you are worrying that a database isn’t big enough to handle all of your data, the good news is that data isn’t usually stored in one giant table, as it is actually made up of multiple tables.
There are multiple tools that exist to link those tables of data and read the information contained in them fairly efficiently. Some of these tools include Oracle and MySQL, and both of them are able to handle massive amounts of data pretty easily. Since these tools don’t actually read the content of data, they would just need the reference points that are called pointers so that they can quickly retrieve the data.
In the scenario where the database is scrambling to look for the information that the user needs, it would often rely on fast switching pointers. This process is how you get the needed data out of billions found in a table. For example, the software doesn’t exactly need to know that the person’s first name is John, it just needs to know that that user’s pointer that says “John” is in the database, and it automatically points to the table containing the information. Then, that table would point to the next connected bit of data, etc. In simple terms, the database is using pointers to find data in a chain of tables. Again, most of the retrieval aspects of the data gathering aren’t about getting all of the data because it is just trying to find the pointer. That pointer often leads to the next pointer, and so on. The database is typically just fast swapping pointers and moving to another display of data.
Big data, as it is termed, is a huge industry that is made specifically for the challenge of gathering and finding data. The industry isn’t perfect, but it exists simply to find better and faster ways to store data in order for the pointer chain to be processed easier.
How do you store data in a database?
In a database, the data is stored by the computer into tables. These tables help the database organize the data within a specific field while also making it easier for the user to retrieve the data. Every data is organized using a field, which is a column found inside the database that organizes where each data should belong. For example, data that are related to the names of a company’s employees will be placed below the “employee name” field, while the occupation of each employee will be stored in the “occupation” field. A single table may have 30 or more fields in the database, so it is not exactly unlimited.
Besides the column, the tables of the database also have a row, which determines the data that should be placed first, and the data that should be placed last. An example that could better explain what a row means to a database is the organization in the names of the employees arranged in alphabetical order. Of course, the employee with a name that starts with the letter A would be the first one on the table, while the employee with a name that starts with M would be placed somewhere in the middle. The arrangement on which data goes first is usually set by the user or data handler, but he or she may also program the database to arrange the order of data using tools.
There would be instances where the database will have insufficient data, and this situation is where the NULL value comes in. The null value is supposed to act as “filler” for data that are not found within the database. For example, there is the name of the employee in the table, but he or she has no indicated occupation. Because his or her occupation is not specified, the database would inset a NULL value on it to fill the blank space or the gap in the table. Furthermore, if there is an “age” field in the table, and an employee didn’t provide information about how old he or she is, then the database would also place a NULL value on it. It would be wrong to place a “zero” or “0” value on the “age” field because the database would assume that the employee is zero years old. In the database, the number zero is considered to still have value, while NULL is automatically read to have no value.
Storing data is not as easy as placing names, words, and numbers on a table, as you would also need to know where to place the data and what to do if the data is insufficient. One wrong placement of data in a table would often lead to a corrupted file, so it is important for data handlers to have advanced knowledge in data storing and gathering.