Systems | Development | Analytics | API | Testing

Let’s boldly go where no one has gone before. Get ready, Star Trek fans! Jean-Luc Picard will be representing our microservice. Once we have Jean-Luc in our ship (microservice in production), what happens on day 2? We still need to add authorization, load balancing, rate limiting, etc. With an API gateway, like Kong Gateway, you don’t have to know how to do this because a set of program components, called plugins, allow you to implement this without any problem.

Amazon S3 (Simple Storage Service) has been around since 2006. Most use this scalable, cloud-based service for archiving and backing up data. Within 10 years of its birth, S3 stored over 2 trillion objects, each up to 5 terabytes in size. Enterprises value their data as something worth preserving. But much of this data lies inert, in “cold” data lakes, unavailable for analysis. Also called “dark data”, it can hold key insights for enterprises.

Redshift’s JOIN clause is perhaps the second most important clause after SELECT clause, and it is used even more ubiquitously, considering how interconnected a typical application database’s tables are. Due to that connectivity between datasets, data developers require many joins to collect and process all the data points involved in most use cases. Unfortunately, as the number of tables you’re joining in grows, so does the sloth of your query.

PostgreSQL is the preferred platform of millions of developers around the world. The open-source tool is one of the most powerful databases on the planet, with the ability to handle sophisticated analytical workloads and high levels of concurrency. That makes PostgreSQL (also called Postgres) a popular DB for scientific research and AI/ML projects. It’s also a popular production database for data-driven companies in every industry. But no database is perfect.

The Cloudera Enterprise Data Maturity Report is a global survey of 3,150 business and IT decision makers assessing organizations’ maturity when it comes to their current capabilities and handling of data and analytics.

As an estimated 92% of enterprises have adopted hybrid and multicloud strategies, according to the 2021 State of the Cloud Report from Flexera, cloud operations (CloudOps) teams face increasing pressure to simultaneously manage costs while improving business outcomes. What levers can CloudOps teams pull to achieve operational objectives such as reducing hybrid and distributed cloud complexity, enhancing security, and automating processes?

For decades, the technologies and systems that deliver analytics have undergone massive change. What hasn’t changed, however, is the goal: using data-driven insights to drive actions. Insight to action has been a consistent vision for the industry. Everyone from data practitioners to technology developers have sought this elusive goal, but as Chief Data Strategy Officer Cindi Howson points out, it has remained unfulfilled — until now.

Data teams across companies have continuous challenges of consolidating data, processing it and making it useful. They deal with challenges such as a mixture of multiple ETL jobs, long ETL windows capacity-bound on-premise data warehouses and ever-increasing demands from users. They also need to make sure that the downstream requirements of ML, reporting and analytics are met with the data processing.