Blog

Much has been written about the shift from ETL to ELT and how ELT enables superior speed and agility for modern analytics. One important move to support this speed and agility is creating a workflow that enables data transformation to be exploratory and iterative. Defining an analysis requires an iterative loop of forming and testing […]

Google Sheets is one of the most widely-used spreadsheet tools. Still, many of its best features go undiscovered. Let’s take a closer look at how to do data validation in Google Sheets, which is commonly used to build drop-down lists.  Why data validation matters Data validation is like the analytic version of copyediting. As much […]

Chances are you’re having to work with several different databases and data warehouses in your analytics stack. It just is what it is today. In order to get an accurate picture in your reporting you have to use everything. However, working with these different database can be like, well this: When publishing tables in different […]

When you enter a date into Microsoft Excel, the program will format it according to the default date settings. For example, if you want to enter the date February 6, 2020, the date could appear as 6-Feb, February 6, 2020, 6 February, or 02/06/2020, all depending on your settings. You may find that if you […]

When publishing data to cloud data warehouse Snowflake for analytic use, data quality is of the utmost importance. Improperly curated data threatens the validity of the end analysis.  Data Quality Rules in Trifacta accelerates the process of ensuring data quality by automatically generating a list of data quality rules for users to select from and […]

If you are using Snowflake as your cloud analytics platform, Trifacta can help accelerate the process of data preparation and cleaning. In this demo, we will demonstrate how to use Trifacta to accelerate the process of preparing data before publishing the results to cloud data warehouse Snowflake. Specifically, we will showcase finding the price-to-rent ratio […]

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 […]

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 […]

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, […]

Before we jump into the definition of an AWS data lake, let’s review why data lakes are important in the first place.  A data lake is a central repository capable of storing both structured and unstructured data. The concept of a data lake is only about 10 years old, but it has already reengineered the […]

These days, we can’t get enough of it–Cloud. Everyone is moving to, or, more precisely, has moved to the cloud for some portion, if not all, of their data analytics. And for good reason. When you need spare compute capacity to do a one-time analytical analysis, you just spin up some servers, run your analytics […]

If you manage a data and analytics pipeline in Google Cloud, you may want to monitor it and obtain a comprehensive view of the end-to-end analytics process in order to react quickly when something breaks. This article shows you how you can capture Cloud Dataprep jobs status via APIs leveraging Cloud Functions. We then input […]