Paige Schaefer is a Product Marketing Associate at Trifacta. Previously, she worked in marketing at San Francisco startups NerdWallet and Inkling before finding her way to big data. Paige attended Macalester College in St. Paul, Minnesota.
“Excel running slow” is a common complaint for more and more users. Excel’s ubiquity and ease of use are its strengths, but Excel runs slow when tackling large data sets. We’ve said it before: the simple fact is that Excel’s framework for data processing wasn’t made for big data. It’s not just that Excel becomes […]
MoreTo 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 […]
MoreMost Excel users know their way around a pivot table. A pivot table can quickly summarize basic statistical information (with sums or averages, for example) and display that data in a more meaningful format. But before you can start pivoting your data, you may need to rearrange your data —in other words, you need to […]
MoreData is the lifeblood of contemporary businesses and is used to formulate marketing, sales and customer service strategies. It is at the core of every decision business leaders make to promote the growth and profitability of their organizations. Data empowers leaders to make precise decisions based on facts and trends rather than speculations. Excellent business […]
MoreWhen Mark Ramsey joined GlaxoSmithKline (GSK) in 2015 as its SVP of the R&D Data office, he saw an opportunity to instill change. He considered the life sciences and pharmaceutical industry a “lagging industry” from an analytics perspective, despite its appetite for data, because he rarely saw companies reuse their data. “There’s lots of data […]
MoreData quality refers to the accuracy and cleanliness of data. It includes examining data consistency, completeness, and relevance. Reliable data quality is required for strategic decision-making when we are working with organizational data in an enterprise. The phrase “garbage in, garbage out” is well known to those who wrangle data. And without good data, you cannot […]
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