Today’s topics are citizen development, the 4th industrial revolution, trusted data, industrial DataOps, innovation, data monetization trends, data layers, AI ambiguity and vertical SaaS
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Kissflow launches 2024 Citizen Development Trends Report
https://finance.yahoo.com/news/kissflow-launches-2024-citizen-development-120000792.html
Citizen Development is no longer a concept for the future. It is already driving digital transformation in organizations around the world.
IoT devices will be the catalyst for the 4th industrial revolution
As industries across the globe grapple with the challenges of modern manufacturing and production, the rise of IoT promises to revolutionize industrial automation.
How to Power Successful AI Projects with Trusted Data
https://www.precisely.com/blog/data-integrity/how-to-power-successful-ai-projects-with-trusted-data
Trusted AI requires data integrity. For AI-ready data, focus on comprehensive data integration, data quality and governance, and data enrichment.
Industrial DataOps set to revolutionise digital transformation
https://itbrief.asia/story/industrial-dataops-set-to-revolutionise-digital-transformation
Industrial DataOps is emerging as a vital solution in overcoming the obstacles associated with industrial digital transformation.
Innovation in action: examples of how companies are implementing digital transformation
Studies show that generative AI (GenAI) has the potential to increase annual productivity growth by USD 2.6 to 4.4 trillion, with revenue growth from GenAI being greatest in the financial services, high-tech, media and life sciences sectors.
To build success, agile manufacturers harness big data
The key to unlocking the full potential of big data lies in its transformation.
Data Monetization Trends: Insights From 1000 Organizations
AI and analytics, using data to improve internal processes, unstructured content, healthcare, trading, market places, open data, licensing, and harvesting web content.
Innovate Americas 24: Want your AI to work? Sort out your data layer
Data experts differ on whether there are five, seven, nine, or more, essential measures of data quality. Two characteristics that consistently make the list, however, are data completeness and accessibility.
Thriving Amid AI Ambiguity
https://www.innosight.com/insight/thriving-amid-ai-ambiguity/
Companies manage AI uncertainty by identifying key variables, plotting scenarios, and adopting a flexible strategy.
Vertical SaaS: Now with AI Inside
https://a16z.com/vertical-saas-now-with-ai-inside/
We are now witnessing the beginning of a third wave of vertical SaaS: cloud + fintech + AI