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Data Standardization: Key to Scaling Analytics in a Digital, Social World

February 14, 2017

To make data useful for collaborative study, modeling, and large-scale analytics, data standardization is a necessary process. Standardizing data—such as matching the terms “Ave vs. Avenue vs. Ave.” to “Ave.”—increases the speed at which data analysts can work.

The need for data standardization has grown exponentially as data sources become more and more diverse, regardless of sector, industry, or business purpose. And completing the process of data standardization at scale often means the difference between success or failure for a business today.

Standardizing Marketing Data: Origami Logic Supports More Clients, More Quickly, with Better Data Quality
Origami Logic is a leader in marketing analytics that helps clients master their marketing performance by letting them see what’s working and what’s not, so they can optimize their efforts.

To do this, Origami Logic combines and standardizes various types of marketing data—social media data, clickstream data, CRM data, etc.—for  integration into its customer-facing application. Origami Logic came to Trifacta with a specific problem: manual data preparation in Excel was time-consuming, prone to human error, and overall more difficult to assess in terms of data quality.

As Origami Logic began to scale their operations, the process had reached a breaking point. It was time for Trifacta to step in.

By leveraging Trifacta, Origami Logic accelerated the data standardization process, reduced costly engineering resources, and saved anywhere from 80 to 100 hours per week. Trifacta’s visual and automatically-generated histograms allowed the Origami Logic team to quickly identify the contents of each file and assess data quality, delivering an accurate analysis. Finally, transformations of individual client’s data became automated, reducing errors and, ultimately, delivering marketing analytics to Origami Logic’s customers faster than ever before.

Standardizing Election Data: NationBuilder More Efficiently Prepares Diverse Voter Data
NationBuilder—a software platform for political candidates to grow their communities—experienced its own data standardization issues. To execute on its mission of lowering the barriers to leadership, NationBuilder knew it must build and maintain its voter file, an aggregate of the entire country’s voter registration data with their voting history, more efficiently.

This presented a distinct challenge. Voter data is made up of messy, poorly-formatted, and inconsistent datasets from hundreds of different state and county offices. The files are very large and constantly being updated, requiring NationBuilder to refresh millions of voter records regularly, quickly, and at scale. In order to achieve a consistent nationwide voter file, NationBuilder had to create complex custom data transformation tools and devote valuable engineering resources to the constant maintenance of these fragile tools.

Trifacta enabled NationBuilder to dramatically reduce the time spent reformatting data by making the data standardization process both simple and repeatable. Leveraging Trifacta wrangle scripts, NationBuilder easily refreshes national voter data quickly whenever new data becomes available.

Customer data transformation tools are also a thing of the past. NationBuilder has expanded its voter file wrangling efforts to a broader and much less technical team, lessening expense and democratizing its own systems.

Standardizing with Trifacta is Anything but Standard
Trifacta’s visual tools and automated processes reduce time, errors, and scaling issues so prevalent in today’s data standardization practices. This has allowed Trifacta’s customers to support their own clients’ needs to cull, structure, and analyze increasingly disparate data sets more quickly, easily, and at a lower cost.

Trifacta tackled data standardization challenges with MarketShare marketing attribution data— read more here.

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