How To
Dec 27, 2023

How to Effortlessly Filter Large Datasets Using Gigasheet

Despite being industry-leading spreadsheet platforms, MS Excel and Google Sheets can’t handle large datasets. This means, you can’t use these platforms to filter big data.

Processing and filtering big data requires a robust platform built for handling complex functions at scale. This platform should be able to handle millions of data points without crashing your system or causing performance glitches. 

Don’t worry, though; you don’t have to struggle to find the best tool to filter large datasets. Gigasheet is purpose-built for all the heavy lifting to filter large datasets. Let’s see how. 

5 ways to filter large datasets and navigate your data

I’ve worked extensively on Gigasheet to handle massive data files and extract meaningful insights. From my experience of using this tool rigorously, I can give you three big benefits right away:

  • Unlike Excel and Sheets, Gigasheet is designed with a powerful backend infrastructure to handle big data files like a piece of cake.
  • Working on Gigasheet is a breeze because instead of writing (and memorizing) complex formulas, you’re working with a more user-friendly interface. 
  • Premium users are not limited by the number of rows and columns; Gigasheet can easily handle more than 1 billion rows whereas MS Excel allows just over 1 million rows and Sheets allows 10 million cells.

Now, let’s get to business and break down five crucial functions to make life easy for you when filtering big data files. 

I used an eCommerce business’s order records with over 4,000,000 rows as sample data to perform all actions and better contextualize the steps for you. This dataset had details like customer ID, invoice date and number, order description, customer country, quantity, customer cohort, and more. 

eCommerce dataset

Case #1: Use the filter option

The easiest way to filter a large dataset is by using the Filter feature in Gigasheet. You can create conditions to filter all the data in your workbook and display only those data points that meet your specified conditions. 

For starters, I applied a condition to display all records from Belgium and France. To set this condition, I had to define the row I wanted to filter, the operator (equals/matches), and the value. 

filter big data using Gigasheet

Gigasheet filtered this massive dataset in the blink of an eye. 

Here are the filtered results:

filter large datasets

Then, I took a step further to add a few more conditions and filter this data even more. I just clicked on the yellow box showing ‘Filtered by’ and clicked the “Add Condition” button. 

 filter datasets with Gigasheet

Next, I added two new conditions to filter the data by quantity and customer cohort. 

You can set conditions using “and” to display only those records that meet all rules. You can also use “or” to create an either-or filter that will display data meeting any of the specified rules. 

apply multiple filters to big data

Here are the results I found—all 4,000,000 rows checked and filtered for these three conditions within nanoseconds. 

filtered dataset

Case #2: Filter by individual rows

Besides adding filters to your overall dataset, you can also apply filters to specific rows. This is great when you know exactly how you want to filter a large dataset and can set your condition for a specific request. 

For example, I decided to filter results by quantity. So, I clicked on the row titled ‘quantity’ and found the option to apply filters. Then added my condition and hit Apply

Filter by individual rows

Gigasheet showed me all the results that met my specified condition for quantity. 

filter a large dataset file

Case #3: Create groups, then apply filters

Besides adding filters to raw data, you can also filter a big data file by first categorizing the data points into groups. Gigasheet can group any dataset into different categories depending on the parameter you choose for grouping. 

In my sample data, I chose ‘country’ as the primary grouping parameter and found the categorized data in less than a second. 

Now, you can filter data within each broader group to find relevant information. Here, I filtered the information by Customer Cohort and set this condition.

create filters using Gigasheet

When I opened the group for France, I could only see records for customers from Group 1 and Group 2. The same was visible for all other groups for different countries. 

filter data by group

Case #4: Use IF/THEN function 

Another creative way to use Gigasheet for filtering big data is with the IF/THEN function. You can use this capability to set certain conditions and decide the outcome if the data matches or doesn’t match these conditions. 

I created this condition to explain this function: if the country is France and the customer cohort is Group 6, then categorize them as “Valid” and the rest as “Invalid”. I named this column “Test”. 

 filter with IF/WHEN function

Once I inserted this condition, Gigasheet created a new column named Test. It also marked each row as either valid or invalid based on whether they fulfilled the specified condition. 

Filtered dataset

Case #5: Work with the Sheet Assistant

Lastly, you can use Gigasheet’s built-in AI Sheet Assistant to filter your data. 

It’s as simple as writing a prompt instructing AI how you want to filter the sheet. Then Sheet Assistant will perform the necessary steps to implement your request. It’ll also share a rundown of these steps, so you can do them yourself. 

filter using Gigasheet AI assistant

Filter large sets of data without breaking a sweat!

If you’re still stuck on Excel or Google Sheets to manage a massive data file, you’re leaving money on the table. You don’t have to spend hours struggling with slow processing time and constant crashes. 

Gigasheet combines convenience with performance to filter large datasets effortlessly. It’s so easy that you have five different options to navigate your data. Sign up for free to experience the power of big data and take your spreadsheet game to the next level. 

How to Filter Large Datasets

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