Bridging Data and Dialogue: The Role of the Semantic Layer in AI
In the intricate world of artificial intelligence, have you ever wondered how complex data is translated into meaningful insights that we can understand and act upon? Enter the semantic layer, the unsung mediator in this process. Think of it as a filter or a lens, one that takes in vast streams of data — much […]
Improving Data Quality with Data Stewardship
To get value from data, data stewards must understand and apply business requirements. When business ambiguity arises about how to best serve data stakeholders, data stewards need to know how to find out this information and with whom to speak. By doing so, stewards can align fit-for-purpose data with business needs and improve data quality. […]
GenAI Maturity: From Productivity To Effectiveness
As I work with more organizations using Generative AI (GenAI) tools like OpenAI’s ChatGPT and Microsoft’s Copilot, I see an interesting dilemma – many organizations seem satisfied with settling for productivity improvements and “taking costs out of the operations” (reminds me as to why companies went to the cloud). And while GenAI tools can indeed […]
Becoming a Hybrid AI Developer/Scientist
One of the most popular discussion topics these days is AI developer vs AI scientist. Rather than switching from one to the other, I offer simple advice to complement your current skillset to be more polyvalent. For the developer who wants to become a scientist, there a few trade secrets you can easily learn so […]
¿Qué son los LLMOps?
El concepto de LLMOps Los modelos de lenguaje de gran tamaño (LLM) son modelos de aprendizaje automático que realizan tareas relacionadas con el lenguaje, como traducir, responder preguntas, resumir contenido y conversaciones, y escribir código y contenido. Los LLM, como GPT-3, LLaMA y Falcon, son herramientas innovadoras que pueden entrenarse con conjuntos de datos para responder preguntas. […]
The Rise of Chief AI Officer
The recent news of adding CAIOs led to everyone talking about this role in creating safeguards around AI. While the title sounds appealing, it comes with its share of uncertainty in terms of expectations and responsibilities. While bringing its unique distinctive capabilities to the table, this role sits at the intersection of many key roles, […]
Data modeling techniques in modern data warehouse
Hello, data enthusiast! In this article let’s discuss “Data Modelling” right from the traditional and classical ways and aligning to today’s digital way, especially for analytics and advanced analytics. Yes! Of course, last 40+ years we all worked for OLTP, and followed by we started focusing on OLAP. After cloud ear come into the picture […]
The Rise of the Dual Data Scientist / Machine Learning Engineer
There are thousands of articles explaining the differences between data scientist and machine learning engineer. Data science gets broken down even further, with data analysts contrasted to researchers. Professionals skilled in all these domains are called unicorns and believed not to exist. Indeed, they may not work for companies, and ignored when applying for a […]
Five Key Trends in AI and Data Science for 2024
Artificial intelligence and data science became front-page news in 2023. The rise of generative AI, of course, drove this dramatic surge in visibility. So, what might happen in the field in 2024 that will keep it on the front page? And how will these trends really affect businesses? During the past several months, we’ve conducted […]
GenAI and LLM: Key Concepts You Need to Know
It is difficult to follow all the new developments in AI. How can you discriminate between fundamental technology here to stay, and the hype? How to make sure that you are not missing important developments? The goal of this article is to provide a short summary, presented as a glossary. I focus on recent, well-established […]
