The Rise of Embedded Analytics and Embedded AI: Proportional Business Value at Last?

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

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

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?

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

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

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

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.

From ER Diagrams to AI-Driven Solutions

In this contributed article, Ovais Naseem from Astera, takes a look at how the journey of data modeling tools from basic ER diagrams to sophisticated AI-driven solutions showcases the continuous evolution of technology to meet the growing demands of data management. Understanding how data modeling tools have changed over time gives us important insights into why organizing and analyzing data well is so important.

The Democratization of AI: 3 Dangers Business Leaders Must Confront

In this contributed article, Simone Bohnenberger-Rich, PhD, Chief Product Officer at Phrase, explores the dangers and challenges posed to business leaders as gen AI companies like ChatGPT open up their tools for deeper integration into organizations.

Pandora’s Box or Lockbox? The Top 3 Barriers to Implementing Generative AI

In this contributed article, Shayde Christian, Chief Data & Analytics Officer at Cloudera, discusses issues surrounding the barriers organizations face when it comes to implementing GenAI and how to navigate them.