Answer:
Inventory errors can cause mismatches between the real numbers of the company, to avoid this you must use software that allows you to avoid these errors.
Explanation:
There is <u>software that line</u> (in the cloud), which is not necessary to install directly on a laptop or server.
Software examples for optimal inventory management:
1. ERP software in the cloud (it is an enterprise resource planner), it is flexible and low cost.
2. my MANAGEMENT
3. Crol
4. bind ERP (for SMEs)
5. Cloudadmin
6. Multi-commerce (license required).
Answer:
O(N!), O(2N), O(N2), O(N), O(logN)
Explanation:
N! grows faster than any exponential functions, leave alone polynomials and logarithm. so O( N! ) would be slowest.
2^N would be bigger than N². Any exponential functions are slower than polynomial. So O( 2^N ) is next slowest.
Rest of them should be easier.
N² is slower than N and N is slower than logN as you can check in a graphing calculator.
NOTE: It is just nitpick but big-Oh is not necessary about speed / running time ( many programmers treat it like that anyway ) but rather how the time taken for an algorithm increase as the size of the input increases. Subtle difference.
Answer:
The statement is as follows:
print("{0:,.1f}".format(number))
Explanation:
Required
Statement to print 1234567.456 as 1,234,567.5
To do this, we make use of the format keyword, and we set the print format in the process.
To round up number to 1 decimal place, we use the following format:
"{0:,.1f}"
To include comma in the thousand place, we simply include a comma sign before the number of decimal place of the output; i.e. before 1
"{0:,.1f}"
So, the print statement is:
print("{0:,.1f}".format(number))
Answer:
AI, Interests, and marketing
Explanation:
Processing privacy policies is not a real function of a large data set.
The answer is B , Hope this helps , I don’t speak Spanish but a little bit I understand , I’m sure that’s the correct answer answer
