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Data Lakes

What's New: New Apache Iceberg Features Ease the Pain Of Managing Your Data Lake

Are you struggling with the challenges of managing your data lake as you strive to address issues ranging from security headaches to troubleshooting complex pipelines? This BUILD 2024 session addresses those challenges with a look at how Snowflake makes it easier to onboard Apache Iceberg into your data lake. The session dives into new features that simplify security, streamline data ingestion and transformation, and enhance integration with your existing tools. You’ll also see how Snowflake provides enterprise-grade redundancy to the data lakehouse architecture, making it easier for teams to work together globally.

Optimize Your AWS Data Lake with Streamsets Data Pipelines and ChaosSearch

Many enterprises face significant challenges when it comes to building data pipelines in AWS, particularly around data ingestion. As data from diverse sources continues to grow exponentially, managing and processing it efficiently in AWS is critical. Without these capabilities, it’s harder to analyze and get any meaning from your data.

Cloudera Lakehouse Optimizer Makes it Easier Than Ever to Deliver High-Performance Iceberg Tables

The open data lakehouse is quickly becoming the standard architecture for unified multifunction analytics on large volumes of data. It combines the flexibility and scalability of data lake storage with the data analytics, data governance, and data management functionality of the data warehouse.

Building Cost-Efficient Data Lakes: Optimizing Compute, Storage, and Data Transfer

Are you managing a data lake and looking to cut costs without sacrificing performance? This webinar will explore proven strategies for optimising expenses. Learn how to minimise the costs associated with computing, storage, and data transfer while maintaining a high-performing data lake.

5 Ways to Approach Data Analytics Optimization for Your Data Lake

While data lakes make it easy to store and analyze a wide variety of data types, they can become data swamps without the proper documentation and governance. Until you solve the biggest data lake challenges — tackling exponential big data growth, costs, and management complexity — efficient and reliable data analytics will remain out of reach.

Databricks Data Lakehouse Versus a Data Warehouse: What's the Difference?

Businesses today rely heavily on data to inform decisions, predict trends, and optimize operations. However, more data volume and complexity has led to growing pressure to find scalable, cost-effective solutions for data storage while staying within IT budgets. Companies want to handle both structured and unstructured data efficiently, while supporting advanced data analysis and machine learning use cases.

Ultimate Guide to Amazon S3 Data Lake Observability for Security Teams

Today’s enterprise networks are complex. Potential attackers have a wide variety of access points, particularly in cloud-based or multi-cloud environments. Modern threat hunters have the challenge of wading through vast amounts of data in an effort to separate the signal from the noise. That’s where a security data lake can come into play.