Author: Devin Partida

Data engineers are increasingly in high demand, especially as more company leaders realize it’s necessary to use reliable information for better decision-making. However, even the most skilled and experienced professionals can make mistakes. Here are some of them and how to steer clear of these blunders. 

Preventing Safe and Effective Data Collaboration

Data usage does not happen in a vacuum. The times when only a few people or departments have access to information are in the past. It’s now standard practice for employees throughout organizations to use and add to databases. As a result, data engineers must incorporate collaboration capabilities into their design and management of information pipelines. 

Machine learning is one of the most disruptive technologies across industries today. Despite this versatility and potential, many organizations struggle to capitalize on this technology’s full potential, especially in sectors like manufacturing that lack widespread ML skills and knowledge.

High upfront costs, complex deployments, data quality issues, and meager returns on investment (ROI) hinder manufacturing ML projects. If the industry hopes to implement this technology effectively, it needs a better approach to developing and using these models. MLOps offers an ideal solution.

Fintech companies need the DevOps software development approach to ensure they are delivering safe, high-performance apps. Development and operations, or DevOps, is a software development method that combines traditionally siloed teams into one unit. 

This change allows for faster releases and updates, improved app performance, easier compliance and auditing, and stronger security. Why are these features crucial for fintech companies today? How does DevOps improve performance, compliance, and security? 

It is an observable fact that the average temperature on the surface of the Earth is increasing. What humans do with this information today will directly impact the future quality of life and condition of infrastructure when they get there.

Humans spent $212 billion on data centers in 2022 and multiple industries reported double-digit growth in their data center spending, with health care and pharmaceuticals (13%), education (13%), and computing and IT services (11%) leading the way. Other notable entries include finance and banking (8%) and engineering and architecture (7%).