Salesforce Tableau Consultant

Good design works with how the eye and mind behave. You learn which visual cues people read quickly and accurately, and which ones mislead, so that every choice of mark, size and position has a reason.

• Position, length, color and size as encodings
• Which comparisons the eye makes best
• Pre-attentive cues and focus
• Gestalt principles in layout
• Limits of memory and attention
• Why a simple chart often beats a clever one

You build A before-and-after redesign of a cluttered view, with the reason for each change.

The question decides the chart. You match comparisons, trends, distributions, relationships, parts of a whole and places to the forms that show them best, and learn when to avoid a chart that looks impressive but hides the answer.

• Comparing categories
• Showing change over time
• Distributions and spread
• Relationships between measures
• Parts of a whole and their limits
• Maps: when geography earns its place

You build A chart choice guide with a worked example for each kind of question.

Small decisions decide whether a view is readable. You use color with purpose, label what needs labeling, annotate the point of a view, and remove decoration that competes with the data.

• Color for meaning, not decoration
• Palettes and colorblind-safe choices
• Titles, labels and legends
• Annotating the key point
• Removing clutter and unnecessary ink
• Consistent formatting across a set of views

You build A style guide of color, text and annotation rules for one client’s dashboards.

A dashboard is a path through the data. You arrange views so the eye follows the story, add interactivity that helps rather than distracts, and design for the devices and settings where it will actually be used.

• Layout and visual hierarchy
• How much to put on one dashboard
• Interactivity that serves the question
• Designing for different screens
• Performance as a design concern
• Accessibility in dashboards

You build A dashboard design with wireframe, layout rules and interaction plan.

A well-made chart can still mislead. You spot truncated axes, misleading aggregation, dual-axis traps and false precision, and learn to show uncertainty and context so that readers do not draw the wrong conclusion.

• Axes and baselines
• Aggregation that hides the story
• Dual axes and when they deceive
• Showing uncertainty and sample size
• Context, comparisons and benchmarks
• Reviewing a view for honesty

You build A critique of five flawed charts, each with an honest redesign.

Clients rarely need every product. You learn what each part of Tableau does for authors and for consumers, and how they combine, so you can explain the family in terms of jobs people need to do.

• Authoring tools: Desktop and Prep
• Sharing platforms: Server and Cloud
• Public sharing and when it applies
• Mobile and embedded use
• Connecting to data that stays in place
• How the products fit in a client’s stack

You build A product map showing which Tableau part serves each role in a client’s analytics process.

Design depends on data, and data choices affect speed and freshness. You compare live connections with extracts, decide when preparation belongs in Tableau Prep or upstream, and weigh the cost of each path.

• Live and extract connections compared
• When to prepare data in Tableau Prep
• When preparation belongs upstream
• Data freshness and refresh planning
• Performance effects of data choices

You build A data connection and preparation recommendation for one client’s data sources.

Good content has to be found, trusted and kept up. You advise on publishing, permissions, ownership and certified sources, so that a client’s analytics stay tidy as the number of authors grows.

• Publishing and where content lives
• Permissions and ownership
• Certified and trusted data sources
• Naming and organizing content
• Retiring stale content
• Roles for authors and consumers

You build A content governance plan with naming, ownership and permissions for one client.

Recommending a path is the heart of the work. You weigh the client’s goals, skills, data and budget against what each product does best, and say plainly what you would choose and what you would not.

• Reading goals, skills and constraints together
• Weighing product options
• Phasing a rollout of capability
• Saying what you would not recommend
• Planning for growth in users and data
• Writing the recommendation

You build A product recommendation with options, trade-offs and a phased plan.

A design the client does not understand will be changed. You explain choices in terms of clarity, accuracy and use, run a design review, and respond to feedback without giving up what makes the work sound.

• Explaining a choice in the client’s terms
• Running a design review
• Responding to feedback and taste
• When to hold a position and when to give way
• Documenting rationale for later

You build A design rationale document for one dashboard, ready to present to a client.

Close with a full piece of advisory work. You review a client’s existing dashboards, redesign the weakest, recommend the product path, and present both together with clear reasons.

• Reviewing existing work
• Redesigning with a reason for each change
• Recommending a product path
• Preparing the presentation
• Handling the client’s questions

You build A review pack: critique, redesign and product recommendation for one client.