Answer: Data and Insights
Explanation:
Data and Insights in an enterprise platform is very important as it helps users better understand their customers so that they may be able to offer them the best services.
Data allows the platform to capture the data of the customer and insights then curates and consumes the data for analysis. The result of this analysis will enable the company to better understand the customer so that they might be able to offer preferable products.
Answer: Between Layers 2 and 3
Explanation:
In between Layer 2 and Layer 3 the MPLS header is present and is known as Shim header. It is also said to be in 2.5.
Answer:
d. broad needs and few customers.
Explanation:
This strategy is based on creation of unique and valuable persons.
Broad needs and few customers (Wealth Management )
Wealth management is a service that combines to address the needs of clients. Wealth Management utilizes financial discipline such as financial and investment , accounting and tax.This service is appropriate for individuals with broad array of diverse needs.
Return them they are probably defective or turn ur media volume all the way down.
Solution :
class Employee:
#Define the
#constructor.
def __
__(
, ID_number, 
, email):
#Set the values of
#the data members of the class.
= name
_number = ID_number
= salary
self.email_address = email
#Define the function
#make_employee_dict().
def make_employee_dict(list_names, list_ID, list_salary, list_email):
#Define the dictionary
#to store the results.
employee_dict = {}
#Store the length
#of the list.
list_len = len(list_ID)
#Run the loop to
#traverse the list.
for i in range(list_len):
#Access the lists to
#get the required details.
name = list_names[i]
id_num = list_ID[i]
salary = list_salary[i]
email = list_email[i]
#Define the employee
#object and store
#it in the dictionary.
employee_dict[id_num] = Employee(name, id_num, salary, email)
#Return the
#resultant dictionary.
return employee_dict
