Altexsoft

JUNE 26, 2019

When conducting various quality assurance activities , development teams are able to look at the product from the user’s standpoint. What is user acceptance testing and how is it different from quality assurance? Traditionally, quality assurance engineers will be responsible for end-user feedback processing.

Quality Assurance 85

Quality Assurance Testing Weak Development Team Software Review 85

Apiumhub

DECEMBER 22, 2023

At Apiumhub , we have been proud media partners of most of Geekle’s online events since the beginning including the Global Summit for Node JS , the Android Development Global Summit , and the Worldwide Software Architecture Summit. AI in Product and Business Analytics Conf – February 27.

Case Study 60

Case Study Quality Assurance Software Development Architecture 60

Gorilla Logic

MAY 19, 2021

Modern enterprise software must integrate with your critical business systems and data, such as billing, inventory management, ERP, and CRM. Develop an adaptive network and applications for both legacy and microservices-based architectures . Get the most out of your data with data warehousing and analytics. .

Software Review 94

Software Review Technical Review Software Development Team Review 94

Mobilunity

NOVEMBER 24, 2021

After assessing the data storage needs, the ETL specialist determines the toolset and methodologies for establishing the data pipeline architecture for the business. Data models usually are the product of cooperation between data scientists, business analytics, and programmers. ETL troubleshooting and quality assurance.

Development 52

Development Storage Recruiting Architecture 52

CIO

APRIL 9, 2025

For many, the level of sophistication can easily range from more sophisticated solutions like Power BI, Tableau, SAP Analytics or IBM Cognos to mid-tier solutions like Domo, Qlik or the tried and true elder statesman for all business analytics consumers, Excel.

Analytics 153

Analytics Artificial Inteligence Enterprise Data 153

CIO

APRIL 8, 2025

We also examine how centralized, hybrid and decentralized data architectures support scalable, trustworthy ecosystems. As data-centric AI, automated metadata management and privacy-aware data sharing mature, the opportunity to embed data quality into the enterprises core has never been more significant.

Weak Development Team 153

Weak Development Team Technical Review Technical Advisors Systems Review 153