What are the most effective ways to handle large datasets in Excel?

Filters allow you to quickly narrow down large datasets based on specific criteria, while PivotTables summarize and analyze data in a dynamic and interactive way, making it easier to glean insights.

Data cleaning is the most crucial step in data analysis process and before data cleansing understanding the data is most important. Without understanding the data, we cannot clean it effectively. For underatanding the data dig deeper the dataset and recognize all the potential information that can support data analysis and remove all the worthless points from data. Once the data is cleaned correctly, most of the data analaysis is done as its very time consuming process. Excel provides us various built-in functions and formulas which help us the clean our data. And one of its most usefull tool for data cleansing is Power query.

Large data sets are not recommended in Excel. This has many limitations that could cause data to be misreported. Large datasets should be managed in SQL server.

Power query is the most effective tool of excel that can transform the data and answer all the questions without much interpretation. Power query provides us various GUI options for cleansing and transforming the data. We can also use its M language to transform the data. Through power query we can remove duplicates, combine data, add and delete new calculated columns. Basically power query is the ETL Tool of Execl where we can extract data from varoious data sources, transform it into the useful form and the load back with the suitable data models.

Power Query is to big data as Comté is to a mousetrap - it works, but it might not be the tool you need. However, it's the best tool Excel has. If you're not skilled on it, it's not hard to pick up and the logging of your actions on the right hand side bar of the screen will be a lifesaver in working out how to correct a mis-step if you make one!

Just as a child making their first PowerPoint overuses animations and transitions, you need to rein yourself in here. Don't try and colour your whole sheet or add icons and trend lines everywhere. Think - what is the story you need to tell, how can you summarise it in a single table or dashboard, and then use effective colours and icon sets or sparklines to explain what people see. Just remember, if you add pretty pictures, people will ignore the details - so use the formats sparingly or to highlight anomalies.

Opportunity and annoyance live on equal measure in tables. Their automatic assumptions at filling often make life a breeze, but their incompatability with several formulae (dynamic arrays can't spill inside them, for example) and different naming conventions (say goodbye to fixing references with a dollar sign) will need you to pause and think about what techniques will be needed to get what you want done on occasion. That said, these minor quibbles are just that, minor, and the speed and usability of tables - particularly in conjunction with live data streaming in from MS Forms (for example) can be utterly transformative. Give tables a go, you'll be pleased you did.

If you're about to make a pivot table, stop and ask why! Too often source data is dynamic, particularly on a share sheet, and a static pivot that needs a decision maker to hit recalculate on every time is a risk. Dynamic tables using formulae are easy to build, particularly with the new PIVOTBY family of equations rolling out in 2024, if you must pivot. Think about using SUMIFS, COUNTIFS, SUMPRODUCT and XLOOKUP instead of pivots - dynamic results will save you time and money from bad decisions made when someone forgot to hit F9.