The level of importance and the level of accuracy needed necessarily depends on exactly what data you are talking about and what conclusions you are trying to reach.
If you are performing analysis on database and your data is not accurate, you run two main risks, one on a computational level, and the other with your conclusions.
The computational problem is that any calculation done with inaccurate data may have a roll-on effect, causing large errors in the final outcome. This leads to the other problem, that the conclusion reached, or the data output that you end up with may be very inaccurate, far more so than the inaccuracy of your original data.
Why is it important to have an accurate data in a experiment?
The observations and measurements recorded during an experiment are called data. It is important to keep accurate data in order to understand the results of the experiment.
Having accurate data in development and testing is important because it is what helps analysis issues. This is what makes things better.
Accurate data is information that is correct.
for you to be able to het a pertinent and accurate data
They are the same thing. They give you an accurate representation of all the values in a data set
Because good observations ensure accurate data and valid conclusions.
data is not accurate.. where information is so accurate
GIGO stands for "Garbage In, Garbage Out." This concept is important in computing, as it refers to the idea that data that is input into a computer system must be valid and accurate in order to produce accurate results. If bad data is entered, the output will be incorrect. In short, the quality of the output is only as good as the quality of the input. Therefore, it is important to ensure that the data that is being entered into a computer system is valid and accurate in order to produce reliable results.
The most important part of data collection is ensuring the accuracy and quality of the data being collected. This involves following proper protocols, using reliable sources, and validating the data to ensure it is valid and reliable for analysis.
i think ungroup data is more accurate because we count each value. while, in group data there is interval
yes,data should b accurate in database.so that if any time we want to retrive data from database we will be able to see correct data.for example burger king arrange a special menu and pricing for weekends.and if data is not accurate then other branches of burger king will not get this information correctly.and due to this business can flop.