Altexsoft

AUGUST 29, 2023

The term was coined by James Dixon , Back-End Java, Data, and Business Intelligence Engineer, and it started a new era in how organizations could store, manage, and analyze their data. This article explains what a data lake is, its architecture, and diverse use cases. Quality assurance.

Architecture 52

Architecture Data Storage Artificial Inteligence 52

Altexsoft

SEPTEMBER 9, 2022

Metadata discovery and capture refers to extracting metadata across your data assets. Metadata quality assurance is checking if metadata complies to quality requirements. You can get more information about data labeling in machine learning from another post (it’s one of the main steps of preparing datasets for ML).

Tools 59

Tools Technical Review Software Review Systems Review 59

Altexsoft

JULY 19, 2022

This basic principle corresponds to that of agile software development or approaches such as DevOps, Domain-Driven Design, and Microservices: DevOps (development and operations) is a practice that aims at merging development, quality assurance, and operations (deployment and integration) into a single, continuous set of processes.

Architecture 52

Architecture Data Analytics Data Engineering 52

Altexsoft

OCTOBER 8, 2021

As a rule, good data integration products have. easy-to-use interfaces; capabilities to examine, clean, and transform data; native connectors for different data integration use cases; scalability and elasticity to fit the changing landscape of data; and. Data profiling and cleansing. high security.

Tools 52

Tools Data Software Review Open Source 52

Datavail

SEPTEMBER 8, 2022

According to an IDG survey , companies now use an average of more than 400 different data sources for their business intelligence and analytics processes. What’s more, 20 percent of these companies are using 1,000 or more sources, far too many to be properly managed by human data engineers.

Data 40

Data Nonprofit Quality Assurance Education 40