Analytics Big Data Business Intelligence Quality Assurance 
Gorilla Logic
MAY 19, 2021
Monetize data with technologies such as artificial intelligence (AI), machine learning (ML), blockchain, advanced data analytics , and more. Some of the most common include cloud, IoT, big data, AI/ML, mobile, and more. Internet of Things (IoT), big data, and AI/ML capabilities for software outsourcing.
Altexsoft
AUGUST 29, 2023
In 2010, a transformative concept took root in the realm of data storage and analytics — a data lake. 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.
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Altexsoft
SEPTEMBER 9, 2022
In data science , metadata is one of the central aspects: It describes data (including unstructured data streams) fed into a big data analytical platform, capturing, for example, formats, file sizes, source of information, permission details, etc. Metadata quality assurance. Types of metadata.
Mobilunity
MARCH 26, 2024
SAP NetWeaver Business Warehouse (BW): As a matter of fact this component does not only change raw data into meaningful insights but it also serves as a hub where data from multiple sources can be consolidated thus providing an inclusive business intelligence and reporting platform.
Mobilunity
NOVEMBER 24, 2021
The demand for specialists who know how to process and structure data is growing exponentially. In most digital spheres, especially in fintech, where all business processes are tied to data processing, a good big data engineer is worth their weight in gold. ETL troubleshooting and quality assurance.
Altexsoft
OCTOBER 8, 2021
But more often than not data is scattered across a myriad of disparate platforms, databases, and file systems. What’s more, that data comes in different forms and its volumes keep growing rapidly every day — hence the name of Big Data. Also, solutions provide automated data mapping. That’s a lot of work.
Altexsoft
MAY 31, 2019
Delivery estimation is based on such critical parameters as population density, vehicle type, and capacity, predictive traffic analytics, etc. Quality assurance tracking. Logistics analytics. As LMS collects a huge range of data, it should be put to good use. Logistics analytics dashboard, Source: Datapine.
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