Systems | Development | Analytics | API | Testing

Isn't the Data Warehouse the Same Thing as the Data Lakehouse?

A data lakehouse is a data storage repository designed to store both structured data and data from unstructured sources. It allows users to access data stored in different forms, such as text files, CSV or JSON files. Data stored in a data lakehouse can be used for analysis and reporting purposes.

Seven Ways to Gain Data Clarity in An Uncertain Climate

It’s been a rollercoaster ride for everyone over the last few years, with particular pressure on Chief Financial Officers (CFOs) to support CEOs steering their organizations through things none of us expected to experience in our lifetime. Unfortunately, with the financial markets going into turmoil over the last few months and consumers of all shapes and sizes starting to cut back on spending, the uncertainty isn’t going to stop anytime soon.

Leveraging Data Analytics in the Fight Against Prescription Opioid Abuse

Every day in the US thousands of legitimate prescriptions for the opioid class of pharmaceuticals are written to mitigate acute pain during post-operation recovery, chronic back and neck pain, and a host of other cases where patients experience moderate-to-severe discomfort.

Computer Vision 101: What It Is and Why It Matters

10 years ago, it would be ridiculous for people to believe that someday they would be able to use their faces to unlock their phones. That’s because it had been extremely difficult to create cartoon characters without profound drawing skills – but now we can easily turn photos into cartoon characters. Struggling with parallel parking? No worries, because self-parking systems are becoming standard equipment in vehicles.

The 7 best Python ETL tools in 2023

In a fast-paced world that produces more data than it can ingest, the right Python ETL tool makes all the difference. But not all Python tools are made the same. Some Python ETL tools are great for writing parallel load jobs for data warehousing, others are specialized for unstructured data extraction. In this article, we’ll explore the 7 best tools for ETL tasks and what business requirements they help you fulfill: Let’s dive right into the best tools and see how they compare.

The Evolution from DevOps to DataOps

By Jason Bloomberg, President, Intellyx Part 2 of the Demystifying Data Observability Series for Unravel Data In part one of this series, fellow Intellyx analyst Jason English explained the differences between DevOps and DataOps, drilling down into the importance of DataOps observability. The question he left open for this article: how did we get here? How did DevOps evolve to what it is today, and what parallels or differences can we find in the growth of DataOps?