Next Stop - Building a Data Pipeline from Edge to Insight
This is part 2 in this blog series. You can read part 1, here: Digital Transformation is a Data Journey From Edge to Insight
This is part 2 in this blog series. You can read part 1, here: Digital Transformation is a Data Journey From Edge to Insight
Xplenty provides features to efficiently extract, transform, and store data from various sources. Chartio provides Visual SQL features that let us explore and analyze data. Furthermore, it includes functionality to arrange charts and metrics in dashboards that can be shared. Both these tools can be used synergically. In this post, we will cover how you to configured Xplenty to use Chartio data. In a subsequent post, we will explain how to visualize the data provided by Xplenty in Chartio.
Learn about the technical challenges involved in building an idempotent data pipeline.
Learn how idempotence protects you from the worst consequences of data integration failures.
A data pipeline is a series of actions that combine data from multiple sources for analysis or visualization. In today’s business landscape, making smarter decisions faster is a critical competitive advantage. Companies desire their employees to make data-driven decisions, but harnessing timely insights from your company’s data can seem like a headache-inducing challenge.
Growing heavy civil construction business brings on a modern data stack of Fivetran, BigQuery and Looker to gain a competitive edge. Want to hear more from Emery Sapp & Son's Clayton Hicklin? Join him and a number of other incredible data professionals at the 2020 Modern Data Stack Conference October 21-22. Register here.
Data scientists and engineers at the online data science education platform focus on attribution, customer lifetime value and the ideal customer profile.
Consider these comparisons before you try to build your own data pipeline