Systems | Development | Analytics | API | Testing

Imagine this: data consumers in your organization no longer anxiously wait for essential data, self-serving data with ease and confidence. Data engineers, freed from dull routine tasks and ad-hoc requests, tackling strategic projects at speed. Meet Data Apps. This new Keboola feature empowers business teams with self-serve data while freeing data engineers to focus on high-impact work. How?

Although it might seem a little early, I was just thinking: what will 2023 be remembered for? For many it will be the year that Beyonce and Taylor Swift took to stages around the world and pushed the boundaries of live music (I’m a confirmed Swiftie if you didn’t know). It is also the year of AI. When I speak with customers, they all talk about how they are steering towards AI adoption.

MySQL and PostgreSQL offer many of the same features and capabilities—but there are critical differences between these two Relational Database Management Systems (RDBMS) that cannot be ignored. If you’re not familiar with these differences, here’s a quick and easy overview: In this guide, we provide a brief history and overview of each database system.

Confluent and AWS Lambda can be used for building real-time, scalable, fault-tolerant event-driven architectures, ensuring that your application logic is executed reliably in response to specific business events. Confluent provides a streaming SaaS solution based on Apache Kafka® and built on Kora: The Cloud Native Apache Kafka Engine, allowing you to focus on building event-driven applications without operating the underlying infrastructure.

The importance of a well-structured data lake architecture cannot be overstated. As businesses work with an ever-increasing influx of data, the need for a robust, scalable, and efficient data storage solution becomes crucial. Let’s explore Data Lake Architecture Design—a concept revolutionizing how enterprises store, access, analyze, and compute their data.

Adopting a new business intelligence (BI) solution requires a thorough understanding of its feature-set and functionality in order to ensure analytics is integrated into your business as seamlessly as possible and that the value of your new tool is realized. Previously, we have covered how Yellowfin can be used with Power BI as a complementary solution.

By the end of this two-part series, we will dive into what data warehouse architecture is and how to implement one for your organization. Part one will look at architectural layers and common data warehouse components, while part two dives into multi-tiered data warehouse architecture.

Companies are now making a decisive shift from traditional on-premises Oracle software to Oracle’s cutting-edge cloud solutions. In fact, a recent Gartner report on cloud expenditure found that cross-industry cloud spend has risen from 8% as a percentage of total IT spend in 2018 to 16% in 2022. Worldwide spending on public cloud services is expected to grow by 21.7% in 2023.

Organizations that consistently use data for decision-making and improving operations outperform their competition. In fact, B2B companies utilizing data experience above-market growth and earnings increases of 15 to 25%. McKinsey forecasts that by 2025, almost all employees will use data to support their work naturally and regularly. Compare that to how organizations currently apply data-driven approaches—sporadically throughout the organization.