Alteryx Designer Core study plan

Build three separate workflows that each ingest a different source type (delimited CSV, Excel workbook, and a flat file needing a custom delimiter and start line) and land the records in a Browse tool for inspection.

Configure field types manually on at least six fields across those workflows, then verify with a Select tool that numeric, date, and string fields report the intended type.

Produce two output files per source workflow: one .yxdb for downstream reuse and one delimited file with a specified delimiter, quoting style, and header option.

Attach a Dynamic Input or Directory-based input pattern that reads every file in a folder instead of a single hard-coded filename.

Write a one-page reference listing twelve Input Data and Output Data configuration options you actually changed, with the effect each had.

Clean up field metadata in each week-1 workflow using Select and Auto Field, explicitly renaming at least four fields and reordering them into a documented target order.

Insert Data Cleansing to strip whitespace, remove null rows, and standardize casing on at least two text fields, then confirm row counts before and after.

Write five Formula expressions using string, numeric, and conditional (IF/ELSEIF/ENDIF) logic, and check each result in a Browse tool.

Apply Filter and Sort tools to split one stream into two documented branches and order the output by two keys.

Score at least 80% on a self-written 20-question quiz covering Input/Output and basic Select/Formula behavior.

Aggregate one dataset with Summarize using at least three grouping fields and four aggregation actions (Sum, Count, Count Non-Null, Max).

Convert a wide dataset to a tall one with Transpose and back to wide with Cross Tab, then compare the round-tripped output against the original to prove the schema matches.

Deduplicate records with Unique (both the unique and duplicate outputs) and cap rows per group with Sample, documenting the exact configuration used.

Generate sequential identifiers with Record ID and totals with Count Records, then join those results back for reporting.

Bucket numeric values into at least four tiles using Tile and validate the distribution with a Summarize count per tile.

Build running totals and prior-row comparisons with Multi-Row Formula across at least three grouped categories, restarting correctly at each group boundary.

Apply Multi-Field Formula to transform every numeric field at once and verify no field was skipped.

Combine a running-total stream with an aggregate stream using Append Fields and confirm row counts multiply as expected.

Reorder and select fields for final delivery with Select, including dropping helper fields created during calculation.

Complete a timed 30-question mixed practice set on Domains 1 and 3 and log every missed item with the tool behavior it tested.

Split a single concatenated field into at least four parseable fields using Text to Columns, testing both delimiter and split-to-rows behavior.

Extract structured values with RegEx in both Replace and Parse modes on at least five distinct patterns, including one malformed-record case.

Parse and reformat date strings in three different incoming formats into one consistent date type, using DateTime tools and DateTimeParse-style formulas.

Standardize messy categorical text with Data Cleansing, Trim, and Replace, then prove the reduction in distinct values with a Summarize distinct count.

Handle nulls and blanks explicitly: replace, impute, filter, or flag at least three null-handling cases and document which choice you made and why.

Join two datasets with Join across all four join types (Inner, Left, Right, Full Outer) and record the resulting row count for each.

Assemble three or more inputs with Union, resolving schema differences by name and by position and noting the output schema each produced.

Use Join Multiple on three inputs to build one combined record set, and compare its output row count against sequential two-way joins.

Match records with Find Replace in both Append and Replace modes, and cluster near-duplicate values with Fuzzy Match followed by Make Group.

Diagnose and fix at least three deliberate join problems: mismatched field names, mismatched data types, and duplicate keys inflating row counts.

Refactor a multi-tool workflow into labeled Tool Containers with annotations on every non-obvious tool, keeping the logic identical.

Control execution order explicitly where the engine does not infer it, and disable and re-enable a branch to demonstrate the effect on downstream tools.

Add Browse tools and caching at chosen checkpoints so you can inspect intermediate data without rerunning the whole workflow.

Re-run your three weakest tools from Domains 2 and 4 without notes, then rewrite the configuration steps in your own words from memory.

Document a workflow end to end so another analyst could rebuild it from the written spec alone.

Take two full-length timed practice exams in a single sitting each, and score them by domain rather than overall.

Re-derive every tool behavior behind a missed question by rebuilding a minimal workflow that reproduces the correct result.

Re-read only your own miss logs and cheat sheets rather than starting new material, closing every open question flagged during weeks 1-7.

Verify tool-specific details you are least sure of (default behaviors, output anchor differences, field-type handling) and write them into a one-page final reference.