When researching and naming data analysis techniques, data wrangling or data preparation for broader data analysis, is typically not included on this list. Even though most IT professionals, data analysts and business people that work with large volumes of data recognize it as an important first step in the data preparation process, too many times data wrangling is regarded as janitorial work, an unglamorous rite of passage before exploring “real” data analysis techniques. In fact, we believe data wrangling should be included under “data analysis techniques” as much the final results. Data wrangling, a core data analysis technique is not done in one fell swoop–it’s an iterative process that helps you get to the cleanest, most usable data possible prior to your analysis. Each step in the data wrangling process exposes new potential ways that the data might be “re-wrangled,” all driving towards the ultimate goal of generating the most robust data for final analysis.
At Trifacta, we think about data wrangling process as the most critical first step and complimentary to other data analysis techniques. Our data wrangling process includes six core activities to prepare data for analysis and to get the most business value out of your data:
- Discovering – allows you to understand your data and how it’s useful for analytic exploration and analysis
- Structuring – gives you the ability to format data of all shapes and sizes to work with traditional applications
- Cleaning – lets you fix and standardize the data that might distort your analysis
- Enriching – allows you to take advantage of the wrangling you’ve already done
- Validating – identifies and surfaces data quality and consistency issues
- Publishing – provides you the ability to plan for and deliver data for downstream analysis
While each of these activities may sound labor-intensive and even tedious, remember that Trifacta’s data analysis techniques using Trifacta Wrangler are heavily automated – from a single keystroke or mouse click, Trifacta uses a suite of algorithms that can identify patterns and leverage them to suggest data transformations. Incorporating Trifacta into your data preparation process and arsenal of data analysis techniques doesn’t require much time, but will yield huge results.
To learn more about data wrangling and the data analysis techniques we empower data analysts, IT professionals and business users with, download our white paper, Six Core Data Wrangling Activities: An Introductory Guide to Data Wrangling with Trifacta.