Systems | Development | Analytics | API | Testing

On-premise vs. Cloud: Finding the Best Solution for your Product

When thinking about a product analytics solution, an essential component of the process lies in deciding between two types of data storage: cloud or on-premise. Each has its advantages and disadvantages depending on a number of factors, such as the stage or size of a business, budget, etc. Before we can tackle these variables, we should understand what each option entails.

To Data Fabric or not to Data Fabric, is it really a question?

Data fabric is a term used to describe a set of technologies and practices that enable organizations to manage and access data across multiple platforms and environments. This includes supporting an organization’s need to break down data silos, gain more insight into metadata, optimize data sharing across apps and data platforms. Organizations are starting to explore more flexible ways of managing their data ecosystems and ensuring they can leverage data more effectively.

Classifying DNA Sequences into Gene Families on SageMaker

The cost of DNA sequencing continues to decline exponentially. With the average cost of sequencing mammalian DNA hovering around $1,000 in the beginning of 2023, startups like Ultima Genomics and Illumina are working to decrease the cost to between $100-$200. That’s about the same as a new pair of Brooks running shoes! As the sequencing cost drops, the quantity of genetic data to study and analyze explodes, making it even more important to leverage machine learning techniques.

Why do we need DataOps Observability?

DevOps was started more than a decade ago as a movement, not a product or solution category. DevOps offered us a way of collaborating between development and operations teams, using automation and optimization practices to continually accelerate the release of code, measure everything, lower costs, and improve the quality of application delivery to meet customer needs.