In this contributed article, Subbiah Muthiah, CTO of Emerging Technologies at Qualitest, takes a deep dive into how raw data can throw specialized AI into disarray. While raw data has its uses, properly processed data is vital to the success of niche AI. Industries such as medical, legal, and pharma require data that is contextualized, categorized, and verified. Business leaders must master data processing to succeed in an AI-powered world.
How Private Networks Are Driving the Data-Powered Enterprise of Tomorrow
July 19, 2024 by
In this contributed article, Ana Redondo, Product Strategy Lead at Amdocs Technology, explores how enterprises will begin shifting their focus in 2024 to better leverage their data analytics. She explains how this shift in mindset will bring forth an upcoming data revolution. Including how the reservoirs of data, from legacy to next-gen operational technology systems, combined with the troves from the Edge and Network, will provide a new level of insights for enterprises.
Branding in 2024: Harness AI, Or AI Will Harness You
July 15, 2024 by
In this contributed article, Todd Irwin, founder and Chief Strategy Officer at Fazer, drops some hard truths about AI. It’s not magic fairy dust that will magically make your brand cool. It’s time to future-proof your brand. Integrate AI or get left in the digital dustbin.
The Rise of Embedded Analytics and Embedded AI: Proportional Business Value at Last?
July 10, 2024 by
In this contributed article, Artyom Keydunov, co-founder and CEO of Cube, believes that although business intelligence (BI) solutions have gone a long way to make more data available to non-technical users, challenges remain. With a universal semantic layer, organizations can create curated, intuitive data experiences that are more accessible than ever, enabling users to derive far more value from enterprise data.
How Organizations Can Avoid AI Sticker Shock
July 5, 2024 by
In this contributed article, Chris Opat, Backblaze senior vice president of cloud operations, highlights how companies can innovate with AI while staying within the budget by understanding the type of AI you’re training, its latency requirements, the quantities of training data, and what third-party data you’ll need.
Enhancing Business Innovation and Operational Efficiency Through Historical Data
July 1, 2024 by
In this contributed article, Adrian Kunzle, Chief Technology Officer at Own Company, discusses strategies around using historical data to understand their businesses better and fill gaps are often overlooked. When organizations maximize historical data, they can improve AI-driven decisions, reduce the overhead of data warehouses and ETL processes, while simultaneously driving portability and automation.
The Rise of Streaming Data and Its Cost Efficiency – How Did We Get Here?
June 25, 2024 by
In this contributed article, Sijie Guo, Founder and CEO of Streamnative, believes that with remote work entrenched in the post-pandemic enterprise, organizations are restructuring their technology stack and software strategy for a new, distributed workforce. Real-time data streaming has emerged as a necessary and cost efficient way for enterprises to scale in an agile way. There are two sides to this coin with dual cost advantages – architectural and operational.
Advocating Collaboration in Safe AI Management
June 20, 2024 by
In this contributed article, Rosanne Kincaid-Smith, Group COO at Northern Data, delves into the ethical considerations of ensuring AI safety and emphasizes the need for a collective approach to AI management – involving a mixture of technical and societal bodies who understand its far-reaching impact. The piece sheds light on the growing concerns surrounding the emergence of next-generation AI technologies and underscores the new collaborative efforts of the US and UK in addressing safety concerns linked to the integration of AI into business operations.
Unlocking the True Power of AI by Turning Conventional ML Wisdom On Its Head
June 14, 2024 by
In this contributed article, Iain Wallace, Director of Machine Learning and Tracking Research at Ultraleap, discusses how rethinking your approach to machine learning can drive true AI innovation.
Personalizing Employee Experiences with Product Analytics
June 10, 2024 by
In this contributed article, Vara Kumar, co-founder and head of R&D and pre-sales at Whatfix, discusses how in today’s competitive landscape, harnessing the full potential of product analytics is pivotal for companies seeking to optimize their internal and external product usage. There are multifaceted benefits of leveraging product analytics,
showcasing its ability to provide profound insights into product utilization across an organization.
