involves examining datasets to draw conclusions about the information they contain, using specialized systems and software. It is a crucial process in business decision-making, helping to identify patterns, correlations, and trends
DATA ANALYTICS
is a powerful tool for data manipulation, analysis, and visualization. It is widely accessible and
contains built-in tools that make it ideal for both beginners and advanced users to perform analytics
MS Excel
Searches for a value in the leftmost column and returns a value in the same
row from a specified column.
VLOOKUP:
summarize large datasets, allowing users to reorganize and extract meaningful information without altering the original dataset.
PivotTables
o Identify and remove duplicates using Data > Remove Duplicates.
o Use Conditional Formatting to highlight duplicate or inconsistent data.
Removing Inconsistencies and Duplicates:
: Horizontal lookup to find data in rows.
HLOOKUP
Cleaning data ensures accurate analysis.
Remove duplicates using Data > Remove Duplicates.
Use text functions like LEFT(), RIGHT(), and TRIM() to clean textual data.
Convert data types and deal with errors such as missing values.
Data Cleaning Techniques
Error Checking
Handling Large Datasets
Best for comparing quantities across different categories.
o Bar Charts:
Effective for showing trends over time.
o Line Charts:
Visualize the proportion of different categories.
o Pie Charts:
Use =—– to add interactive buttons to filter data dynamically in PivotTables and PivotCharts.
Slicers
Import large datasets from external sources, such as CSV files or databases using Data > Get External Data.
Export cleaned or analyzed data to formats like CSV for use in other applications
Data Import and Export