The way that companies govern data has evolved over the years. Previously, data governance processes focused on rigid procedures and strict controls over data assets. But now, with the data-driven culture, modern enterprises are adopting an agile approach toward data governance that primarily centers around data accessibility and empowering business users to take responsibility for governing and managing data.

If you're noticing bottlenecks or disadvantageous data silos in your enterprise workflows, enterprise automation could be the answer.

Its ability to simplify a variety of tasks such as making HTTP requests, handling responses, and managing network activities, has made Alamofire one of the most popular and powerful networking libraries in Swift. Today we’ll be looking at how Alamofire can be integrated with Bugfender to cut through the complexities of URLSession to streamline networking operations in our apps.

Minimum Viable Architecture plays a critical role in the success of your MVP. Learn how to avoid the most common pitfalls in implementing this strategic approach.

As government agencies work to improve both customer experience and operational efficiency, two tools have become critical: cloud services and data. Confluent and Amazon Web Services (AWS) have collaborated to make the move to and management of cloud easier while also enabling data streaming for real-time insights and action. We’ll be at the AWS Public Sector Summit in Washington, DC on June 26-27 to talk about and demo how our solutions work together.

Hadoop. The first time that I really became familiar with this term was at Hadoop World in New York City some ten or so years ago. There were thousands of attendees at the event – lining up for book signings and meetings with recruiters to fill the endless job openings for developers experienced with MapReduce and managing Big Data. This was the gold rush of the 21st century, except the gold was data.

The journey toward achieving a robust data platform that secures all your data in one place can seem like a daunting one. But at Snowflake, we’re committed to making the first step the easiest — with seamless, cost-effective data ingestion to help bring your workloads into the AI Data Cloud with ease. Snowflake is launching native integrations with some of the most popular databases, including PostgreSQL and MySQL.

In today’s data-driven world, Apache Kafka has emerged as an essential component in building real-time data pipelines and streaming applications. Its fault tolerance, scalability, and ability to handle high throughput makes it a great choice for businesses handling high volumes of data.

In the digital age, data is the lifeblood of organizations, driving strategies, innovation, and decisions. However, harnessing its power requires more than just collecting the data. It demands meticulous management of data quality, governance, and lineage. These pillars form the backbone of informed decision-making, enabling organizations to transform raw data into actionable insights. According to Gartner, poor data quality costs organizations an average of $12.9 million every year.

Snowflake is a modern, robust data platform for cloud data management that provides users with the opportunity for unique scalability, flexibility, and performance. However, keeping costs under control is crucial to maximize the benefits on offer with this platform.