The first thing you should do is make sure your data is in a format that's easy to work with. If it's not, you should probably try to clean it up before you dive into using any of these tools.
When it comes to exploring data, there are two main barriers:
- Difficulties in exploring huge amounts of data (think terabytes and petabytes)
- Lack of time to get insights from the data
When you're trying to get a sense of your data, it can be hard to know where to start. There are a lot of ways to explore data. You can use Excel or Google Sheets, or you can use a more robust program like Python. But what if you don't know any programming languages? Or what if you want to explore data in a new way that isn't available to you with your current tools?
Some of the most common approaches to data exploration include:
- Spreadsheet-like tool (no-code)
- Visualization tool (low-code)
- Programming languages based exploration (coding-based)
- Off-the-shelf analytics tools like PowerBI.
So what are some good rapid data exploration tools?
Tableau: Tableau Public is an interactive visualization tool that allows you to create beautiful visualizations without needing advanced programming skills or expensive software licenses. It supports SQL queries and other advanced features, so if you need something more than just basic charts and graphs, this is a great option!
Pros
- Ease of use
- Thriving community forum
Cons
- If you want something that offers a little more flexibility and control over your visualizations than Tableau Public does, then using Plotly or Jupyter Notebooks makes more sense. Both of these tools allow you to create custom charts and graphs for analyzing your data or creating presentations about it.
Google / Excel Sheets: Google Sheets and excel sheets have always been the default go-to for exploring any kind of data. While the sheets do allow you to analyze unstructured data, the required skill level needed for using Excel/Sheets for such data exploration is high.
Pros
- Great for exploring small-size data and sharing information with others.
Cons
- Has row and column limitation [10 million cells for sheets, around 1M rows for Excel]
- Becomes slow when data is huge
- Operations such as Pivot table can get complicated for massive data
- The user interface is not easy to use when managing big data
Gigasheet: Gigasheet is a big data analytics tool that provides an excel sheet interface while removing the complexity of handling big data on excel sheets. Typically you need a basic infrastructure of having a database to be able to analyze and explore your data. And a certain kind of visualization capability to display the analytics. Gigasheet removes all this need and allows you to export your data from any of your apps or private sources to the platform and start exploring the data. For example, looking into 90 Million rows of JSON data from Aetna health insurance, I could identify the top 10 maximum price procedures - all because of the flexibility and power of Gigasheet!
Pros
- Since the interface is similar to an excel sheet, you don’t have the initial learning curve trying to understand how to explore the data.
- The tool is free for analyzing any number of rows
Cons
- You need to pay for more than 3 GB storage space, or to export a full file. But still, pricing is reasonable, especially when you take into account the benefits of using it, and data exploration is free.
P.S - I work at Gigasheet and the big data analytic tools that convert your massive-unused data to impactful insights.
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