This is one of the most used features in Nekt. The Explorer module offers a simple way to learn more about your data and easily extract information.

With it, you can quickly get answers using the AI assistant and have the necessary infrastructure to advance your queries with SQL.

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AI in Action

Curious to see it in action? Watch this video to learn how the AI Assistant works:

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Step by step to successfully explore your data

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1. Know your data

Before deciding which questions to answer, it makes sense to understand what data you have in Nekt, where it comes from, and how they relate to each other.

For this, the first step is to check whether the data source you’re looking for is already registered in Sources and verify in the Catalog which data is being extracted into the tables.

Use the Preview feature within each table in the Catalog to understand the data format, as this can be important for more effective exploration.

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2. Explore your data with SQL

SQL is the most widely used solution for data exploration. In Nekt, it’s the language that allows you to modify and perform operations on the data to answer specific questions.

You can use the AI assistant to generate SQL code from natural language commands, or you can create the SQL code yourself if you’re familiar with the language. Let’s take a closer look at both options:

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3. Save your queries or create a transformation

After creating the SQL query that produces the expected results, you have several options:

3.1 Save to repeat the query later

Use the Save query function to save this query for future use. This will allow you to quickly access this code as many times as you want. Each time you run it, it will be executed on the most up-to-date data. It’s useful when you need an answer frequently.

3.2 Create a transformation and generate a new table

Use the Create transformation function when you want the result of your query to become a new table in your Catalog.

It’s quite common, for example, for a table to come from the data source with more data than necessary for a specific use case or with unformatted data, which makes it harder to use. For this, your SQL code can handle these cases and generate the ideal table - which will only be created and updated in the Catalog (and become available for destinations and visualizations, for example) through a transformation.

3.3 Discard

If you’ve made a query that probably won’t be repeated and whose result doesn’t need to be stored in a table, you can simply close the query and do nothing with it. The Explorer is like a playground - feel free to explore your data and test what results you can achieve.

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Need help?

If you run into any issues along the way, feel free to contact our support team. We’ll be happy to help!