Systems | Development | Analytics | API | Testing

If you’d like to try Yellowfin for yourself, go ahead and request a free trial. Generative AI has made it easier than ever to analyze data with plain English. You’ve probably seen dozens of videos showing how to use ChatGPT for data analysis — upload a CSV, ask a question, and get a chart. But I wanted to see how that stacks up against Yellowfin, which is designed for analytics from the ground up.

Discover how Cisco is transforming its global data strategy to drive faster decisions, accelerate AI innovation, and scale globally — all while maintaining enterprise-grade security and control.

Qlik’s partnership with Amazon Web Services (AWS) is at the very core of our cloud data integration and analytics platform. Think of it like the iconic double helix of DNA. Just as DNA’s intertwined strands carry the fundamental instructions for life, the interconnection between Qlik and AWS carries the innovation and reliability that power the future of enterprise analytics, data integration, and AI.

Salesforce is the backbone of revenue teams across industries. Yet, the individuals who keep it running smoothly, the Salesforce Admins, rarely receive the recognition they deserve. For years, Admins have been seen as the people who “keep the lights on” by resetting passwords, fixing workflows, and generating reports. In reality, their role has grown into something far more significant. They are the unsung heroes of revenue operations, bridging the gap between data, systems, and strategy.

Joe Reis, author of Fundamentals of Data Engineering, known for practical education and his YouTube content — formerly CEO/co-founder of Ternary Data — is reviewing our Keboola MCP (Model Context Protocol) Server with Claude to list Shopify his tables, run exploratory analysis, export data to BigQuery, and generate a star schema. And you can do the same in minutes! We will go through everything here from one-click setup to best propmts to use MCP with.

Everything you need to know about dbt explained; plus how SQL-based modeling helps teams turn raw data into analytics-ready outputs.

Before jumping into AI data cleaning directly, let’s first understand data cleaning itself. Data cleaning, also known as data scrubbing, is a critical data preparation step where organizations remove inconsistencies, errors, and anomalies to make datasets ready for analysis. The cleaning process may involve actions like removing null values, correcting formatting, fixing syntax errors, eliminating duplicate data, or merging related fields like City and Postal Code.

The Wisdom of Crowds Business Intelligence Market Study from Dresner Advisory Services is one of the most recognized annual benchmarks for BI and analytics. It captures how organizations are investing, what priorities they set, and which technologies are delivering the most value. The 2025 edition highlights steady growth in BI spending and shifts in user objectives, from efficiency and revenue impact to security and data quality.