Browse our articles with proven strategies, in-depth guides, and expert tips for succeeding with AI & Data.
Long gone are the days where you had to buy hardware, create server rooms and hire, train, and maintain a dedicated team to run it. Cloud-based data platforms are the new norm. They offer a more agile, scalable, and cost-effective approach to managing and leveraging data. But does that mean the traditional data platforms are dead?
We're living in what could be the most important century. And at the center of this era is Artificial Intelligence and data science, reshaping all aspects of our lives. So we sat down with Visium's founders, Alen Arslanagic, Timon Zimmerman and Matteo Togninalli, to explore their perspective on the challenges and opportunities of AI adoption and on building a customer-centric and authentic AI and data company.
AI and ML in healthcare, backed by data availability, are transforming patient care. Examples like FDA-approved AI/ML medical devices and AI-enhanced autoinjectors illustrate their impact in diagnostics and care delivery, improving accuracy and patient outcomes. So what are some of the most transformative applications of AI and Machine Learning in healthcare?
Traditional data setups, characterized by centralized data lakes and isolated data systems, are proving inadequate in the face of increasing data volumes and evolving business demands. Enter the data mesh paradigm - a decentralized approach that promises to revolutionize data management. However, with any fundamental change, many questions arise. In this case, the key one being: is it worth transitioning to a data mesh?
The rapid adoption of AI in fraud detection is transforming the way financial institutions approach Anti-Money Laundering (AML) strategies. But before embracing these new technologies, financial institutions need to ask some hard-hitting questions: How robust are current compliance processes? Is the system flexible enough to cover the latest regulations? And is the team truly ready for this tech revolution?
For every new drug brought to the market, it costs $6.16 Billion and takes more than 10 years of work. Hence, pharma companies are always interested in new strategies that can facilitate and accelerate the drug development process.
Some businesses start in garages; some at hackathons; others by chance. Ours started with a conversation back in 2017 about how the world could benefit from AI / ML done well and with care. We had a vision and in just a few months a name that embodied it: Visium.
Data-driven companies experience remarkable benefits. According to Tableau, they witness a 35% increase in employee retention and a 40% improvement in time-to-market. But what does it truly mean to be data-driven?
When it comes to implementing AI, one of the biggest obstacles for companies is not the lack of technical infrastructure or cost concerns. The main challenge is choosing the right business use case. So, how do you choose the right one?
Generative models became popular for producing art images or text, however, they can also be applied to anomaly detection. With their ability to learn from unlabeled data, these models offer a powerful solution to tackle complex datasets and enhance real-time detection.
Ever wondered what makes a good data story? In this article we uncover what data storytelling is, its purpose, and what are the essential ingredients for an impactful data story.
Each day, 2.5 quintillion bytes of data are generated in the digital world. But how well are companies tapping into this growth and using it to their advantage? The answer lies in effective data management.
