## Step 1: Define the symbolic representation of the variables
The variables are 'intrusion analysts', 'security engineers', and 'honeypots', which can be represented symbolically as $x_0$, $x_1$, and $x_2$ respectively.

## Step 2: Convert the natural language objects into symbolic notation
The symbolic representation of the variables is:
- $x_0$ : intrusion analysts
- $x_1$ : security engineers
- $x_2$ : honeypots

## Step 3: Define the objective function in symbolic notation
The objective function to minimize is $2.15x_0 + 9.26x_1 + 8.44x_2$.

## 4: List the constraints in symbolic notation
The constraints are:
- $3x_0 + 12x_1 + 7x_2 \geq 14$ (total combined data integrity impact from intrusion analysts, security engineers, and honeypots must be 18 at minimum, but one constraint is 14 and another is 18, we will consider both)
- $3x_0 + 12x_1 \geq 22$ (total combined data integrity impact from intrusion analysts and security engineers)
- $3x_0 + 7x_2 \geq 14$ (total combined data integrity impact from intrusion analysts and honeypots)
- $14x_0 + 13x_1 + 8x_2 \geq 22$ (minimum power consumption from intrusion analysts, security engineers, and honeypots)
- $14x_0 + 13x_1 \leq 52$ and $14x_0 + 8x_2 \geq 22$ are considered but $14x_0 + 13x_1 + 8x_2 \geq 22$ will be used for power consumption
- $9x_0 + 14x_1 + 13x_2 \geq 30$ (total combined data accessibility impact from intrusion analysts, security engineers, and honeypots)
- $9x_0 + 14x_1 \geq 30$ (total combined data accessibility impact from intrusion analysts and security engineers)
- $9x_0 + 13x_2 \geq 34$ is not needed as $9x_0 + 14x_1 + 13x_2 \geq 30$ and $9x_0 + 14x_1 \geq 30$ will suffice for data accessibility
- $2x_1 - x_2 \geq 0$

## 5: Correct and Refine Constraints Based on Problem Description
Correcting and refining based on the problem statement:
- Data integrity impact constraints: $3x_0 + 12x_1 + 7x_2 \geq 18$
- $3x_0 + 12x_1 \geq 22$
- $3x_0 + 7x_2 \geq 14$
- Power consumption constraints: $14x_0 + 13x_1 + 8x_2 \geq 22$
- $14x_0 + 13x_1 \leq 52$
- $14x_0 + 8x_2 \geq 22$
- Data accessibility impact: $9x_0 + 14x_1 + 13x_2 \geq 30$
- $9x_0 + 14x_1 \geq 30$
- Other: $2x_1 - x_2 \geq 0$

## 6: Write down the symbolic representation of the problem
```json
{
'sym_variables': [('x0', 'intrusion analysts'), ('x1', 'security engineers'), ('x2', 'honeypots')],
'objective_function': '2.15x0 + 9.26x1 + 8.44x2',
'constraints': [
    '3x0 + 12x1 + 7x2 >= 18',
    '3x0 + 12x1 >= 22',
    '3x0 + 7x2 >= 14',
    '14x0 + 13x1 + 8x2 >= 22',
    '14x0 + 13x1 <= 52',
    '14x0 + 8x2 >= 22',
    '9x0 + 14x1 + 13x2 >= 30',
    '9x0 + 14x1 >= 30',
    '2x1 - x2 >= 0'
]
}
```

## 7: Implement the optimization problem using Gurobi
```python
import gurobi

def solve_optimization_problem():
    model = gurobi.Model()
    
    # Define variables
    x0 = model.addVar(name="intrusion_analysts", vtype=gurobi.GRB.INTEGER)
    x1 = model.addVar(name="security_engineers", vtype=gurobi.GRB.INTEGER)
    x2 = model.addVar(name="honeypots", vtype=gurobi.GRB.INTEGER)
    
    # Objective function
    model.setObjective(2.15 * x0 + 9.26 * x1 + 8.44 * x2, gurobi.GRB.MINIMIZE)
    
    # Constraints
    model.addConstr(3 * x0 + 12 * x1 + 7 * x2 >= 18)
    model.addConstr(3 * x0 + 12 * x1 >= 22)
    model.addConstr(3 * x0 + 7 * x2 >= 14)
    model.addConstr(14 * x0 + 13 * x1 + 8 * x2 >= 22)
    model.addConstr(14 * x0 + 13 * x1 <= 52)
    model.addConstr(14 * x0 + 8 * x2 >= 22)
    model.addConstr(9 * x0 + 14 * x1 + 13 * x2 >= 30)
    model.addConstr(9 * x0 + 14 * x1 >= 30)
    model.addConstr(2 * x1 - x2 >= 0)
    
    # Optimize
    model.optimize()
    
    if model.status == gurobi.GRB.OPTIMAL:
        print("Optimal solution found.")
        print(f"Intrusion Analysts: {x0.varValue}")
        print(f"Security Engineers: {x1.varValue}")
        print(f"Honeypots: {x2.varValue}")
        print(f"Objective: {model.objVal}")
    else:
        print("No optimal solution found.")

solve_optimization_problem()
```