Bernd Rucker
JUNE 23, 2020
Before I can do that, I will briefly explain a typical event-driven architecture and the resulting challenges. An overall (business) process is carried out by a number of event notifications in a certain sequence, as multiple microservices need to be involved. It‘s’ hard to understand what happens and why.
O'Reilly Media - Data
JULY 23, 2018
The rise of deep learning has made this even more pronounced, as many modern neural network architectures rely on very large amounts of training data. Over the last few years, many companies have begun rolling out data platforms for business intelligence and business analytics. Retail and e-commerce".
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CTOvision
OCTOBER 22, 2014
About two years ago, we began investigating magnetic field architecture (MFA) and hover technology as a better way to build, move people and move materials,” said Arx Pax founder Greg Henderson. Puma Energy is the fuels retailing arm of Swiss-based … Read more on Ferret. Hey, McFly! Hoverboard available on Kickstarter.
Cloudera
DECEMBER 21, 2020
The data is tagged as sensitive data, e.g. “financial”, and the owner field showing “retail banking” instantly informs Shaun which organization to reach out to to ask for access. Protecting their data and business while allowing more self-serve and access.
Apiumhub
AUGUST 12, 2021
This year you will have 6 unique tracks: Cloud Computing: IaaS, PaaS, SaaS DevOps: Microservices, Automation, ASRs Cybersecurity: Threats, Defenses, Tests Data Science: ML, AI, Big Data, Business Analytics Programming languages: C++, Python, Java, Javascript,Net Future & Inspire: Mobility, 5G data networks, Diversity, Blockchain, VR.
Confluent
SEPTEMBER 19, 2019
Around that same time, the disciplines, tooling, and consulting companies that would come to define business analytics were just being formed. The pattern was that every night, your ETL process would dump that day’s transactional activity into your newfangled analytic data warehouse.
Altexsoft
FEBRUARY 8, 2021
This approach demands significant investments in software, equipment, and human resources to create advanced data architecture, but the resulting accuracy and visibility are worth paying for. Develop business-specific analytics platform. Comparison between traditional and machine learning approaches to demand forecasting.
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