How Does Failing Fast in Data Analysis Help Your Projects Flourish?

20 October 2022 16:00

Failing Fast

It’s no secret that finding the right datasets for your analysis creates a huge hurdle when starting new data projects. You have countless sources to choose from, yet even when you think you’ve found the perfect data, your project fails to produce the results you are looking for. This cumbersome process of searching for, importing, and testing data consumes too much time because of the constant need to switch between different digital environments. This frustrating back-and-forth leaves less time for driving insights in your data analysis, but it is immensely important to use the right data for creating accurate outcomes.

So, what do you do? Fail fast.

Failing Fast

Failing fast isn’t completely failing to find insights using data. Instead, it’s the notion of testing data, recognizing its inability to produce the results you’re looking for, and returning to discovery quickly. It may seem more beneficial to try and make the data you already have work for your project instead of going out and searching for new data—and sometimes it is—but this more often ends up just delaying your outcomes. The discovery process is already time-consuming. Adding more time in attempts to create new models or piecing together analysis with insufficient data just delays decision making and hinders performance.

Instead, commit to failing fast which allows you to be more agile in your analysis approach. If current data isn’t creating the outcomes you are seeking, return to your sources to find a dataset that does. This keeps projects moving forward instead of stalled at a roadblock.

Nexis® Data Lab Keeps Data Analysis Flowing

When you have to search high and low for relevant sources, then spend more time exporting and importing data into your analytics tools, failing fast isn’t an easy option. Nexis® Data Lab, on the other hand, eliminates the inconvenience by bringing your data discovery and analysis environment into one platform. With the unrivaled universe of content available from LexisNexis® combined with a Jupyter Notebook environment that supports Python and R libraries, you can cut out wasted time by limiting the back-and-forth between data discovery and testing to one place.

To speed up the tedious process of data discovery, Nexis Data Lab provides powerful search tools and filters that allow you to pinpoint exactly what you need in an instant. This is because of LexisNexis SmartIndexing Technology™, which tags all of the content we aggregate with thousands of controlled and extracted terms, enabling highly-targeted and efficient searches over traditional research. This search technology helps cut down the time it takes to find relevant sources.

Because this search is in the same environment as your analysis, you can instantly import hundreds of thousands of documents to analyze in your Jupyter Notebook. If this data doesn’t work, failing fast with Nexis Data Lab is as simple as switching back to the data discovery page and importing a new set into your workspace.

Containing this back and forth of discovery and testing into one platform, combined with an intuitive data search engine and Python and R libraries to assist in modeling, you can fail fast and find the right data for your project even faster, generating the insights and outcomes you need more efficiently than with any other traditional research tools.

Do you want to speed up your speed to insights? Talk to our Sales Team about Nexis Data Lab today and see what an all-in-one discovery and analysis platform can do for your next data project.

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