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Make Your AWS Data Lake Deliver with ChaosSearch (Webinar Highlights)

When CTO James Dixon coined the term “data lake” in 2011, he imagined a single storage repository where organizations could store both structured and unstructured data in their raw format until it was needed for analytics. But without the right storage technology, data governance, or analytical tools, the first data lakes quickly became “data swamps” - morasses of data with no organizational structure and no efficient way to access or extract meaningful insights.

Executing Data Integration on Amazon Redshift

Amazon Redshift says it executes data operations ten times faster than other enterprise data warehouses because of a hardware-accelerated cache called Advanced Query Accelerator (AQUAD). It also claims three times better price-performance than other similar technologies. Statements like these are what make Redshift an attractive option for companies that want to push data into a warehouse for analytics.

3 things to do as part of your first-time release strategy for fintech apps

Fintech is one of the fastest-growing mobile app categories in the U.S. To stand a chance as a fintech startup, you need to make sure that your fintech app delivers a top-notch experience. Read about the three main things you need to do to get there!

Lenses 5.0: The developer experience for mass Kafka adoption

Kafka is a ubiquitous component of a modern data platform. It has acted as the buffer, landing zone, and pipeline to integrate your data to drive analytics, or maybe surface after a few hops to a business service. More recently, though, it has become the backbone for new digital services with consumer-facing applications that process live off the stream. As such, Kafka is being adopted by dozens, (if not hundreds) of software and data engineering teams in your organization.

8 Benefits of Setting Up a Data Warehouse in AWS Redshift

AWS Redshift is a managed data warehouse solution from Amazon Web Services. It’s part of their popular cloud-based computing platform and used by many familiar enterprises, such as Lyft and McDonald’s. Data warehouses are storage and analytical solutions for large amounts of data. They take data gained via ETL or ELT services like Integrate.io or AWS Glue and turn it into useful information and datasets that businesses can analyze and utilize for strategic insights.

Amplify your relationship with testers this valentine's day!

Valentine’s day is a day to express your love to the other person 💞. You need not explicitly do this through words. Showing gratitude, care or making them comfortable all are signs of expressing love. But is it the same with people doing jobs together? Relationships other than romantic ones often overlook this aspect of work that keeps people happy and make them stay for long – just like what happens in a relationship.

A Beginner's Guide to Amazon Redshift

Data. Big data is everywhere in your business and odds are good that you have petabytes of it. From your customer's purchasing information to financing data, you need to make sure that you are properly managing your data. This means working on recording, organizing, and analyzing it. As the old expression goes, "Junk in, junk out." If you don't properly manage your data, you'll have nothing but junk. This means that you have to store your data and datasets.

Make the leap to Hybrid with Cloudera Data Engineering

Note: This is part 2 of the Make the Leap New Year’s Resolution series. For part 1 please go here. When we introduced Cloudera Data Engineering (CDE) in the Public Cloud in 2020 it was a culmination of many years of working alongside companies as they deployed Apache Spark based ETL workloads at scale.