Large Language Model (LLM) applications are everywhere. From chatbots, to webscraping tools and even the usage of LLM's to automate administrative tasks completely. All of this cutting-edge technology, obviously, has the potential for enormous business impact. However, can we prove that our investments in this technology are driving value? When is the performance of these applications "good-enough"?
Lots of companies have done great without really paying too much attention to their data and its underlying processes. They have grown over time without doing so. But there is a risk in missing the next wave. Discover how Power BI will ease the switch.
Choosing the Best Option for Your Data Pipelines with dbt
Unfortunately generative AI and Large Language Models are not an universal solution to all our problems. But how can you create impact with it in your business?
Navigating the Transition with a Change Management strategy
As Microsoft released new APIs and Collibra has kept up with numerous new developments, the integration between Power BI and Collibra offers several new possibilities. Check out more details and download our guide with tricks and tips to facilitate this new integration.
The EU AI Act has arrived and we're at a crossroads: do we wait for regulations to guide us, or do we start asking the hard questions now?
Envision a situation where you're tasked with managing clickstream data received via Snowplow. In this blog post, we'll guide you through our solution, step by step.
In this technical blog post, we will explore the key features and benefits of MSSparkUtils, and how it can be effectively utilized to accelerate working with Spark on Azure Fabric.
