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Analytics Insights and Careers at the Speed of Data

Rocket-Powered Data Science

Focus on specific data types: e.g., time series, video, audio, images, streaming text (such as social media or online chat channels), network logs, supply chain tracking (e.g., Dynamic sense-making, insights discovery, next-best-action response, and value creation is essential when data is being acquired at an enormous rate.

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The Shift toward Intelligent Automation

DataRobot

With the power of DataRobot , creating AI and machine learning models with your data becomes less of a bottleneck due to the guardrails and transparency from getting from data to value. DataRobot uncovers insights in data that would be impossible for even expert humans to detect.

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The Foundations of a Modern Data-Driven Organisation: Change from Within (part 2 of 2)

Cloudera

The report classified employees’ reasons for leaving into six broad categories such as growth opportunity and job security, demonstrating the importance of using performance data, data collected from voluntary departures and historical data to reduce attrition for strong performers and enhance employees’ well-being.

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Financial planning & budgeting: Navigating the Budgeting Paradox

IBM Big Data Hub

Why budgeting feels like a marathon Just like marathon training takes months of preparation, crafting a budget involves a lot of data collection, metrics analysis, resource allocation and collaboration. Negotiations and complicated financial models add depth and time to the budgeting process.

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Generative AI Deep Dive: Advancing from Proof of Concept to Production

Speaker: Maher Hanafi, VP of Engineering at Betterworks & Tony Karrer, CTO at Aggregage

💡 This new webinar featuring Maher Hanafi, VP of Engineering at Betterworks, will explore a practical framework to transform Generative AI prototypes into impactful products! He'll delve into the complexities of data collection and management, model selection and optimization, and ensuring security, scalability, and responsible use.

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Some highlights from 2020

Data Science and Beyond

Also, my June webinar with Felipe Flores on running remote teams is probably dated now that many more people have hands-on experience with remote work. The world has adapted quickly, though it seems like Automattic’s globally-distributed model is still quite unusual. Only time will tell. Sustainability.

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5 Data Governance Mistakes to Avoid

Alation

As firms mature their transformation efforts, applying Artificial Intelligence (AI), machine learning (ML) and Natural Language Processing (NLP) to the data is key to putting it into action quickly and effecitvely. Using bad data, or the incorrect data can generate devastating results. between 2022 and 2029. Keen to learn more?