With Thanksgiving around the corner, it's a perfect moment to take a step back and get some recipes to be data savvy within your organization. Fortunately, Talend experts have a recipe for data success that will help you to stay above the fray.
There are plenty of trends and hot topics in the enterprise technology market today. One common area we hear about from users is that there’s a lot of data to collect, manage, and analyze. And whatever industry you’re in, you probably want to do something more with your data. We built BigQuery, one of the important tools in the Google Cloud Platform (GCP) arsenal, to provide serverless cloud data warehousing and analytics with built-in machine learning to meet modern data needs.
60% of agencies say that organic drives the most traffic for clients right now. How will that change over the next 12 months? We asked them to share.
A popular term emerging from the software industry over the last few years is serverless computing, more commonly referred to as just “serverless”. So what does it mean? In its simplest form, a serverless architecture is a computing model where a service provider dynamically manages the allocation of computing resources based on a Service Level Agreement (SLA), provisioning and running resources only for the time needed and without requiring end-user involvement.
In the previous blog, we walked through the installation and set-up of Talend Open Studio and briefly demonstrated key features to familiarize you with the Studio interface. In this blog, we will build a simple job to load data from a local file into Snowflake, a cloud data warehouse technology. More specifically, we will build a new job that takes customer data from your local machine and maps it to a target table within Snowflake.
For over 30 years, the dashboard has been the delivery paradigm of choice for decision support and executive information systems. It started with Business Objects and Cognos, and today Qlik, Tableau, Power BI and other vendors are still using dashboards as the medium of data delivery. Rather than thinking about whether there’s a better way to deliver insights, dashboard dinosaurs just keep using the same paradigm.
