Essential guide to managing, preparing, and analyzing data in Excel using AI. From data imports and cleaning to analysis, tasks that take hours to complete can be done in minutes using natural language AI prompts. This reference is about taking action and gives you the need-to-know steps in the process of analysis including example prompts for each step. Succinct, colorful, and in an outline-style format for finding answers fast, this 6 page laminated guide covers more per page than any other reference. Easily stored and accessed, find any step in the process you need to review at any time without continually searching for answers. Author Andrew McLeod, a writer, and statistics and computer science expert working in AI since 2022 uses his Excel and AI knowledge to help you with the best notes an expert can give for a great price. Add this desktop reference for you, your team, department or entire company and save time and resources.
6 page laminated reference guide includes:
- Importing Data with Copilot
- Primary Data Import Methods
- How Copoilot Handles Imported Data
- Constraints & System Boundaries
- Data Preparation & Workflow Analysis
- Data Cleaning
- Data profiling
- Error Classification
- Remove or eliminate invalid data
- Handling missing or null data
- Fix error inconsistencies
- Text Cleaning
- Detect & handle outliers & anomalies
- Data-type error fixing
- Fuzzy matching & deduplication
- Data harmonizing
- Cross-referencing& data enrichment
- Pattern violation detection
- Constraint or rule-based cleaning
- Data Structuring
- Table formatting
- Header structure
- Table layout cleanup
- Convert nontabular layouts
- Column or schema design
- Data organization
- Reshaping data
- Relational structuring (multitable design)
- Data modeling preparation
- Indexing & keys
- Data input structuring (upstream design)
- Schema consistency
- Data Formatting & Standardization
- Data-type consistency
- Data-type standardization
- Date, time, & number formats
- Cell formatting
- Conditional formatting
- Text standardization
- Quantitative standardization
- Category & label standardization
- Readability
- Cross-dataset standardization
- Data encoding standardization
- Locale & language standardization
- Data Transformation & Preparation
- Sorting & selection
- Combining data (multi-source structuring)
- Column-level transformations
- Row-level transformations
- Data aggregation & grouping
- Reshaping data
- Hierarchical or nested data handling
- Derived metrics & calculations
- Time-based transformations
- Data enrichment
- Scenario & business logic transformations
- Custom logic & advanced calculations
- Performance optimization
- Data Validation & QA
- Validation rule setup
- Validity & type checks
- Required & unique fields
- Logical & relationship checks
- Completeness & reconciliation checks
- Error reporting
- Data Analysis
- Exploratory data analysis
- Descriptive statistics
- Aggregation & summarization
- Pivot table analysis (nonvisual)
- Statistical analysis
- Advanced statistical analysis
- Predictive & modeling analysis (basic)
- Multivariant analysis
- Segmentation & cohort analysis (basic)
- Drill-down & drill-through analysis
- Anomaly detection
- Insight generation
- Sensitivity analysis (basic)
- Business logic analysis
- M365 Copilot Ecosystem
- Beyond Copilot
- Julius.AI
