That's a pretty vague question, but the answer is a cumulative frequency table is exactly the data you'd need for a histogram. A histogram is a chart where for each class or range of data you display a count of how many times you had a sample data point in that range.
Let's say you were measuring heights of seventh graders. We might make our ranges the following:
<60 in
60-63
63-66
66-69
69-72
>72 in
Then we'd measure some seventh graders and get data like:
62.1 67.8 65.5 63.0 69.1 64.2 65.8 63.2 62.8 69.4
We'd make our cumulative frequency table by counting how many in each range. We have to decide about 63.0, on the line; let's put it in 63-66.
range count
<60 in 0
60-63 2
63-66 5
66-69 1
69-72 2
>72 in 0
The frequency is the ratio of the count to n, the total count, here n=10 heights. So we can add the frequency column where we divide the counts by 10 and express the result as a percentage.
range count freq
<60 in 0 0%
60-63 2 20%
63-66 5 50%
66-69 1 10%
69-72 2 20%
>72 in 0 0%
That's how you make a cumulative frequency table where you calculate the frequency of a number of ranges. It can also be used for categorical data; we count each category.