Big Data Business Intelligence Quality Assurance Scalability 
Gorilla Logic
MAY 19, 2021
Not surprisingly, the skill sets companies need to drive significant enterprise software builds, such as big data and analytics, cybersecurity, and AI/ML, are among the most competitive. Some of the most common include cloud, IoT, big data, AI/ML, mobile, and more. Skill shortages can delay project kickoffs and delivery.
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. Who needs a data lake?
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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.
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. As a rule, good data integration products have. high security. Source: Oracle.
Openxcell
JANUARY 18, 2022
It is specifically used for white-box monitoring and the data collected through this application is used in the Business intelligence space. Besides, it also monitors the micro-services of the business. Developed in Java, this open-source tool is completely scalable and provides accurate data analysis.
Altexsoft
OCTOBER 17, 2019
Low-quality data can also impede and slow down the integration of business intelligence and ML-powered predictive analytics. US company executives that participated in the Data trust pulse survey by PricewaterhouseCoopers noted that unreliable data is one of the obstacles to monetizing data.
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