Typically, the “INSERT” operations are very slow inside a database and incurs a high load on the database system. So, most database vendors offer specialized tools called "bulk upload" that allow you to do many “INSERT” at very high speed and at a lower processing cost. Typically, these "bulk upload" tools take as input large text files and copy them into the database. There exists two different problems when working with text files:
1.Text file cannot store the “NULL” value (that is represented inside the Anatella-data-preview-window by an empty cell with a *red* background): Text files can only store strings of zero-length (that is represented inside the Anatella-data-preview-window by an empty cell with a *white* background). Thus, you might lose some valuable information here (because, from the point-of-view of predictive modeling, the NULL value might represent a concept fundamentally different than the “” value).
2.Storing floating-point numbers inside a text file is the most common source of many large “rounding errors”: i.e. You’ll get a slight loss of precision or accuracy when storing floating-point numbers inside text files because of the decimal↔binary convertion: See the next paragraph for more details on this subject. When these "rounding errors" accumulate, they can represent a large quantity of Euros/Dollars (There was even a movie about this subject: i.e. A coder that recovered the money losts inside the "rounding errors" (several millions euros) and put them on his own bank account )
Let’s now talk about how the floating-point numbers are stored inside a computer. Typically, the floating-point numbers are stored & manipulated in binary notation: 010011101 (more details about this subject and ). Unfortunately, in text files, these same numbers are stored in decimal notation: e.g. the number Pi is 3.14159265458, 10, and so on. Converting fractional (ie non-integer) numbers from decimal notation to binary notation (and in the other direction: from binary notation to decimal notation) is a (significant) source of rounding error.
The conversion from decimal notation (used by humans to represent numbers inside a text) to binary notations (the way the numbers are manipulated and stored inside a computer) is usually the most common and most important source of "rounding errors" in a computer program. Hopefully for integer numbers, we don't loose any precision during the conversion.
When you are using standard "bulk upload" tools, you'll lose some precision on the floating-point numbers because these tools expect text files as input (and inside the text files, all the floating-point numbers are converted to decimal notation). To reduce to the minimum this loss of precision, you should instruct Anatella to use as many digits as possible to represents floating-point numbers in the text file: This is done using this parameter inside the writeCSV Action: