 Do I know the data subjects(audience) ?
 Do I understand the requirements and the value it must add ?
 Did I choose an appropriate graph that can convey the right intent ?
 Do I have to add any interactiveness to the graph ?
 Can I layer or separate the information ?
 Can I maximize the data density ?
 Is the graph telling the truth ?
 Are colors used appropriately in graph ?
 Do I need to remove any chart junk ?
 Is any scale distorted or missed ?
 Did the visualization, maximize the data to ink ratio ?
 Is pixel quality of the graph good enough ?

Reference: https://stephanieevergreen.com/updated-data-visualization-checklist/

Short descriptive title is left-justified in upper left corner
Short titles enable readers to comprehend takeaway messages even while quickly skimming the graph.

Titles are in a larger size than subtitles or annotations, which are larger than labels, which are larger than axis labels, which are larger than source information. The smallest text - axis labels - are at least 9-point font size on paper, at least 20 on screen.

Titles, subtitles, annotations, and data labels are horizontal (not vertical or diagonal). Line labels and axis labels can deviate from this rule and still receive full points. Consider switching graph orientation (e.g., from column to bar chart) to make text horizontal.

Position data labels near the data rather than in a separate legend (e.g., on top of or next to bars and next to lines). Eliminate/embed legends when possible because eye movement back and forth between the legend and the data can interrupt the brain’s attempts to interpret the graph.

Focus attention by removing the redundancy. For example, in line charts, label every other year on an axis. Do not add numeric labels and use a y-axis scale, since this is redundant.

A viewer should be able measure the length or area of the graph with a ruler and find that it matches the relationship in the underlying data. Y-axis scales should be appropriate. Bar charts start axes at 0. Other graphs can have a minimum and maximum scale that reflects what should be an accurate interpretation of the data (e.g., the stock market ticker should not start at 0 or we won’t see a meaningful pattern).

Data should be displayed in an order that makes logical sense to the viewer. Data may be ordered by frequency counts (e.g., from greatest to least for nominal categories), by groupings or bins (e.g., histograms), by time period (e.g., line charts), alphabetically, etc. Use an order that supports interpretation of the data.

Avoid three-dimensional displays, bevels, and other distortions.

Colors should represent brand or other intentional choice, not default color schemes. Use your organization’s colors or your client’s colors. Work with online tools to identify brand colors and others that are compatible.

Action colors should guide the viewer to key parts of the display. Less important, supporting, or comparison data should be a muted color, like gray.

When printed or photocopied in black and white, the viewer should still be able to see patterns in the data.
Color is legible for people with colorblindness
Avoid red-green and yellow-blue combinations when those colors touch one another. Avoid using red to mean bad and green to mean good in the same chart.

Black/very dark text against a white/transparent background is easiest to read.
Excessive lines— gridlines, borders, tick marks, and axes can add clutter or noise to a graph, so eliminate them whenever they aren’t useful for interpreting the data.

Color should be faint gray, not black. Full points if no gridlines are used. Gridlines, even muted, should not be used when the graph includes numeric labels on each data point. Graph does not have border line

Axes do not have unnecessary tick marks or axis lines Tick marks can be useful in line graphs (to demarcate each point in time along the y-axis) but are unnecessary in most other graph types. Remove axes lines whenever possible.

Viewers can best interpret one x- and one y-axis. Don’t add a second y-axis. Try a connected scatter plot or two graphs, side by side, instead. (A secondary axis used to hack new graph types is ok, so long as viewers aren’t being asked to interpret a second y-axis.)

Graphs should have a "so what?" – either a practical or statistical significance (or both) to warrant their presence. For example, contextualized or comparison data help the viewer understand the significance of the data and give the graph more interpretive power.

Data are displayed using a graph type appropriate for the relationship within the data. For example, change over time is displayed as a line graph, area chart, slope graph, or dot plot.

Use a level of precision that meets your audiences’ needs. Few numeric labels need decimal places, unless you are speaking with academic peers. Charts intended for public consumption rarely need p values listed.

Choices about graph type, text, arrangement, color, and lines should reinforce the same takeaway message.