Trifacta Legends Hall of Fame

Our monthly series showcasing users who are doing legendary work with data

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  • What Is a Customer Data Platform? A Guide to CDPs

    Today’s customers leave digital footprints behind just about every purchase. Any given buyer may start by searching on Google, visiting an eCommerce store, cross-referencing on Amazon or Google Shopping, reviewing the company’s social media channels—and several times back again—before finally making a purchase.  Gathering this kind of data is certainly helpful. But being able to […]

    Matt Derda  |  October 26, 2020

    Your Guide to the Benefits, Challenges, and Best Practices of Data Governance

    Picture this scenario: a group of health insurance analysts want to understand the variation in cost of a medical procedure. However,  the data they receive from partnering hospitals is stored in different systems throughout the organization and its accompanying metadata doesn’t match up, making it nearly impossible for users to understand the context of the […]

    Will Davis  |  October 25, 2020

    How to Merge Cells in Google Sheets

    Google Sheets has become the spreadsheet tool of choice for many analysts, in part due to its accessibility and collaboration features. Let’s take a closer look at how to perform a common function in Google Sheet: merging cells. More importantly, read on to learn how to merge cells in Google Sheets without losing data.  How […]

    Bertrand Cariou  |  October 25, 2020

    Leveraging the Six Elements of Excel Formatting

    Small formatting adjustments can make all the difference to a Microsoft Excel workbook. A small pop of color here, a change of font there, and suddenly, your workbook is no longer just a sea of rows and columns, but an organized, presentable table of data.  Below, we take a closer look at how to format […]

    Will Davis  |  October 24, 2020

    What Is Data Modeling and Why Does It Matter?

    Data doesn’t exist in a vacuum; understanding the relational nature of data is key to understanding its value. For example, what good would customer IDs be to a product team if those IDs didn’t coincide with the specific products that customers bought? Or, how would a marketing team conduct pricing analysis without being able to […]

    Bertrand Cariou  |  October 22, 2020

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    Understanding Automated Cloud Data Warehouse with BigQuery and Looker

    This blog illustrates how the combination of Cloud Dataprep, Looker, and BigQuery fulfills the three necessary elements for a scalable, self-service data warehouse a.k.a. self-service analytics.  What is self-service analytics? Self-service analytics empower the everyday business user to create their own end-to-end analytics solution—that is, accessing data, preparing and cleansing it for use, and generating […]

    Bertrand Cariou  |  October 22, 2020

    October Legend: Misagh Jebeli

    Misagh Jebeli is truly an innovator in the data and analytics space. In the very first IT class he ever took, the teacher went over how Walmart uses data to arrange items in their shelves to boost sales. That was the moment Misagh fell in love with data.

    Matt Derda  |  October 22, 2020

    How Callahan Improved Media Impact by 90% By Automating its Cloud Data Warehouse

    What makes Callahan such a unique digital marketing agency? They start with front-end data analysis to inform client strategy—in other words, gathering as much data as possible (far beyond what would be considered standard marketing sources) to understand the client’s baseline business and marketing operations. The goal is pinpointing exactly wherein lies the biggest opportunity […]

    Bertrand Cariou  |  October 21, 2020

    Predicting COVID-19 Cases with Machine Learning and Trifacta

    In the fight against COVID-19, one of the best weapons at our disposal is data. But interpreting COVID-19 data isn’t always cut and dry. There’s no blueprint for a novel virus; instead, the global scientific community has had to sift through complex and ever-evolving data and, bit by bit, begin to assemble an understanding of […]

    Bertrand Cariou  |  October 14, 2020

    How to Extend Cloud Dataprep by Using BigQuery Javascript UDFs

    Since Trifacta is a data company, we try to be as data-driven as possible. This means that product usage data analysis informs many of our product, sales, and marketing decisions. Our team has built our usage data pipeline entirely in GCP, so we can use both our own technology (Google Cloud Dataprep) and native GCP […]

    Connor Carreras  |  October 12, 2020

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    Cleanse Salesforce Address Data using Cloud Dataprep by Trifacta

    Introduction We’ve all been there. Imagine having an upcoming event where sponsors are to receive a personalized invitation in the mail for your event. Before any mail can be sent, the sponsors must first be available in Salesforce for event registration and post-event surveys. These sponsors don’t already exist in Salesforce so we must upload […]

    Emilio Taylor  |  October 1, 2020

    Trifacta and AWS Team Up to Create Intelligent, Automated Machine Learning

    A wrench in the plans. Sand in the gears. Gum in the works. These three idioms mean the same thing: friction, the one thing you want to avoid when you’re tackling machine learning. And yet friction is all too common. To function properly, machine learning algorithms need data to be structured in a specific way. […]

    Matt Derda  |  September 30, 2020

    Humble Brag: Users Say We’re the Best at Data Prep in G2’s Fall Reports

    At Trifacta, one of our key pillars is to start with the user. Everything we do is to empower the people who use Trifacta to do more with their data, do it faster and do it better. Today, Trifacta was named as a leader in the G2 Grid for Data Preparation as well as the top […]

    Matt Derda  |  September 23, 2020

    Cleaning Dirty Data & Messy Data

    The appeal of being a data analyst or data scientist does not come from cleaning messy data. And yet, it’s the activity that often ends up consuming the majority of their total analytic time—on average, 80 percent of it—while just 20 percent is dedicated to visualizing and analyzing data, creating machine learning models, or other […]

    Will Davis  |  September 22, 2020

    Trifacta Legend September 2020: Christopher Dean

    Christopher Dean is a rising star in the data and analytics space. Earlier this year Christopher was named one of DataIQ’s 100 most influential people in data. In his interview below, it’s obvious why.

    Matt Derda  |  September 21, 2020

    Snowflake Software and Trifacta

    The cloud computing market is often boiled down to a race between the “Big Three” cloud providers—Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP). But while these platforms may anchor an organization’s cloud strategy, they are far from the full picture. The cloud computing market is made up of numerous technologies, products, […]

    Matt Derda  |  September 20, 2020

    Unveiling New Cloud Data Warehouse Use Cases for Cloud Dataprep at Google Next ‘20

    The biggest news for all things Google Cloud can be found at the Google Cloud Next conferences in the US and in Europe. This year it’s being dubbed Google Cloud Next ’20: OnAir in light of its transition from an in-person even to a multi-week digital event series. During our virtual Next ‘20 presentation, we […]

    Bertrand Cariou  |  September 17, 2020

    Why Analytics Leaders Need to Read Data Preparation for Dummies

    There’s a common misperception about data management, and it goes something like this: Consolidating your organization’s data into a centralized analytics environment  solves everyone’s problems in finding, accessing, and using data. And when it comes to analytics, you can just run statistical algorithms leveraging high-performance computing engines and voilà! Relevant, accurate, meaningful, and actionable data […]

    Will Davis  |  September 14, 2020