In data engineering and analytics, effectively wrangling data is not just a skill but a necessity. Large volumes of complex data have grown exponentially as businesses and technologies evolve. This surge has brought two critical processes in data management to the front line: Data Wrangling and Extract, Transform, Load (ETL). Understanding these processes is pivotal for any organization leveraging data for a strategic advantage.

Going into 2024, API management has become a critical aspect of modern-day business operations. A good API management tool can help you streamline the process of designing, deploying, securing, and monitoring all your APIs.

The world of data is constantly evolving and advancing, bringing exciting new opportunities for those who wrangle it. To make the most of your critical data, you must first map it. However, an increasing number of sources and formats results in a tricky mapping process. Data mapping tools can simplify this process, ensuring you can visualize, analyze, and interpret data accurately and efficiently.

Explore the architectural concepts that power BigQuery’s support for semi-structured JSON, which eliminates the need for complex preprocessing and provides schema flexibility, intuitive querying and the scalability benefits, at large scale.

I consider myself pretty lucky: I love technology and get paid to pursue my hobby. I also get to say yes to opportunities that come my way that can increase value to my company and our clients. It was one of these opportunities that led us to adopt change data capture (CDC) technology, resulting in an added value proposition for our customers.

Qlik’s partnership with AWS provides customers with an end-to-end data integration and analytics solution for AWS. Our accelerates data delivery and readiness for analytics from a wide range of enterprise data sources. And our empowers users at any skill level to freely explore all your data and uncover hidden insights. Add to that Qlik Staige and you can find out how we can help modernize with AI.

BigQuery cross-region dataset replication allows you to replicate any dataset across regions, for additional geo-redundancy.

Secure File Transfer Protocol (SFTP) stands as a robust protocol at the disposal of businesses, offering enhanced collaborative capabilities, operational efficiency, and heightened security for confidential data. Using SFTP, organizations can confidently exchange files among users and locations, irrespective of device variations. This adoption contributes to increased productivity levels and improved security around sensitive data, shielding it from unauthorized breaches.

An MLOps platform enables streamlining and automating the entire ML lifecycle, from model development and training to deployment and monitoring. This helps enhance collaboration between data scientists and developers, bridge technological silos, and ensure efficiency when building and deploying ML models, which brings more ML models to production faster.

Large Language Models (LLMs) have now evolved to include capabilities that simplify and/or augment a wide range of jobs. As enterprises consider wide-scale adoption of LLMs for use cases across their workforce or within applications, it’s important to note that while foundation models provide logic and the ability to understand commands, they lack the core knowledge of the business. That’s where fine-tuning becomes a critical step.