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Modern Data + AI Integration:Strategies and Architectures

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How to Create and Share Static and Dynamic Lookups

Follow along with today’s post as a video.

Today we’re covering how to use Nexla’s data lookups to easily combine and lookup static or live data. Nexla makes it easy to create a static lookup from a CSV file, manual input, or text, which can then be applied with other datasets to match key values.

For lookups that change, any dataset can be used as a dynamic lookup that updates in real time. We’ll be showing both in this video to find stock prices from purchase transactions. The datasets created from lookups can be transformed, validated, and sent to destination like any other dataset. Of course, just like credentials, transforms, and datasets, all lookups are easily shareable within the platform for collaborators to use.

Static Lookups

First we’ll go over creating a static lookup using one set of stock purchase transactions.

Go to Tools, then Lookup. Click on Create Static Lookup in the corner.

This particular example uses a CSV file of stock transaction IDs, names, and ticker symbols, which we can upload directly, but you can also input a text table or build a table yourself.

We’ll name this lookup, then we can use it to get real-time stock prices.

To use the lookup, the next step is to connect a data source.

In this case, it will be a public stock exchange API, but lookups work with all of Nexla’s connectors. The applications and potential are wide.

Select the dataset.

Connect to the API URL, select a lookup table–in this example, it will be the one uploaded previously–and pass the ticker symbol to the ticker field of the API. Nexla will use the static lookup to pass all the ticker symbols added from that CSV.

Nexla will now create that data source, and it can be transformed, shared, or monitored as needed.

After applying a few transformations to slice the data, pull out just the weighted average daily price and ticker symbol from the API response. Now there is a dataset updated with live prices using that lookup that can be sent to any destination.

Dynamic Lookups

To use a dynamic lookup, add the live dataset of stock transactions and send it to a “Dynamic Lookup” destination.

In this example, there is a .json response from another API with that day’s stock transactions, and a dataset is created from that then sent to a dynamic lookup destination.

Now, just like with a static lookup, add the stock price API again and use the dynamic lookup instead. The output dataset will have not only real-time price data, but automatically update to that day’s specific stock trades as well.

Nexla makes it easy to create the datasets that you need and prepare dataflows to send to different destinations. Nexla will continue to run as the data updates, so the data will always be up-to-date and relevant.

Conclusion

Data lookups in Nexla make it easy to get exactly the kind data you need. By combining different static and dynamic lookups, you can quickly make sure your dataset is built how you need it. Collaboration features also make lookups easy to share and use over and over, increasing collaboration and decreasing bottlenecks.

If you’re looking for more information on how Nexla is automating data engineering, get a demo or book your free unified data solution strategy session today. For more on data and data solutions, check out the other articles on Nexla’s blog.

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