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Expert Panel: Challenges with Modern Data Pipelines

Modern data pipelines have become more business-critical than ever. Every company today is a data company, looking to leverage data analytics as a competitive advantage. But the complexity of the modern data stack imposes some significant challenges that are hindering organizations from realizing their goals and realizing the value of data.

A DataOps Observability Dialogue: Empowering DevOps for Data Teams

A DataOps Observability Dialogue: Empowering DevOps for Data Teams It used to be said that software is eating the world, but now data is running things. And it’s high-functioning data teams who make it all happen. But data teams are facing several obstacles that prevent them from delivering innovative analytics at today’s increased speed and scale. Software teams have been facing the same challenges for 10+ years and have tackled them with DevOps. So why are DataOps teams struggling when DevOps teams aren’t? They’re using the same tools to solve basically the same problem. . . .

Unravel Data Demo Video

Unravel’s Keith Alsheimer, Head of Marketing, and Chris Santiago, VP of Solutions Engineering, introduce Unravel’s DataOps observability platform: how it’s designed specifically from the ground up to empower data teams, why DevOps tools don’t work for DataOps, and a short demo of how Unravel AI helps accelerate troubleshooting, automatically where and exactly how to optimize performance, and proactively govern and reduce cloud costs with precision.

Tips to optimize Spark jobs to improve performance

Summary: Sometimes the insight you’re shown isn’t the one you were expecting. Unravel DataOps observability provides the right, and actionable, insights to unlock the full value and potential of your Spark application. One of the key features of Unravel is our automated insights. This is the feature where Unravel analyzes the finished Spark job and then presents its findings to the user. Sometimes those findings can be layered and not exactly what you expect.

Kafka best practices: Monitoring and optimizing the performance of Kafka applications

Apache Kafka is an open-source distributed event streaming platform used by thousands of companies for high-performance data pipelines, streaming analytics, data integration, and mission-critical applications. Administrators, developers, and data engineers who use Kafka clusters struggle to understand what is happening in their Kafka implementations.

Unravel for Google BigQuery Datasheet

Poorly written queries and rouge queries can create a nightmare for data teams when it comes to fixing and preventing performance issues, and as a result, costs can quickly spiral out of control. Whether you want to move your on-premises data to Google BigQuery or make the most of your Google BigQuery investments, Unravel can help businesses that struggle to find the optimal balance of performance and cost of Google BigQuery.

Why Legacy Observability Tools Don't Work for Modern Data Stacks

Whether they know it or not, every company has become a data company. Data is no longer just a transactional byproduct, but a transformative enabler of business decision-making. In just a few years, modern data analytics has gone from being a science project to becoming the backbone of business operations to generate insights, fuel innovation, improve customer satisfaction, and drive revenue growth. But none of that can happen if data applications and pipelines aren’t running well.

Roundtable Recap: DataOps Just Wanna Have Fun

We like to keep things light at Unravel. In a recent event, we hosted a group of industry experts for a night of laughs and drinks as we discussed cloud migration and heard from our friends at Don’t Tell Comedy. Unravel VP of Solutions Engineering Chris Santiago and AWS Sr. Worldwide Business Development Manager for Analytics Kiran Guduguntla moderated a discussion with data professionals from Black Knight, TJX Companies, AT&T Systems, Georgia Pacific, and IBM, among others.