10 data pipeline challenges your engineers will have to solve
When choosing to build or buy, consider whether the following challenges are worth the squeeze.
When choosing to build or buy, consider whether the following challenges are worth the squeeze.
Data quality is fairly simple nomenclature to describe the state of the data being processed, analyzed, fed into AI, and more. But this modest little term belies an incredibly critical and complicated reality: that enterprises require the highest level of data quality possible in order to do everything from developing product and business strategies, and engaging with customers, to predicting the weather and finding the fastest delivery routes.
GitHub Actions is a powerful continuous integration and continuous delivery (CI/CD) platform that allows developers to automate build, test, and deployment pipelines. Workflows automatically build and test code whenever an event occurs, such as a pull request or a deployment of merged pull requests to production. Best of all, you can use it without leaving the comfort of your own repository!
Have you ever considered how much data a single person generates in a day? Every web document, scanned document, email, social media post, and media download? One estimate states that “on average, people will produce 463 exabytes of data per day by 2025.”
The lingering effects of the global pandemic are merging with inflation to create a perfect storm for retailers looking to find the right inventory stature for the seasons ahead. Companies are getting squeezed between rising supply chain costs and falling consumer confidence. To succeed in this volatile market, McKinsey suggests that retailers “accelerate decision-making tenfold.”
Data centers consume a lot of energy; some say it can be as much as 1.8% of total U.S. electricity consumption. It’s why power consumption, cooling costs, and space requirements are at the heart of the sustainable data center.