Read below for a roundup of interesting sites, resources, and articles from around the web, curated and contextualized by unbiased analytics experts at IIA. Highlights include a piece exploring McKinsey and Salesforce's AI partnership for enterprises, an article on the importance of closed-loop feedback control in data pipelines, and a blog on how to discuss data monetization strategies. Follow us on Twitter and LinkedIn to receive daily updates on IIA content and curated content as it becomes available.
Featured Articles on Data and Analytics Strategy
Data Management Principles for Data Science (KD Nuggets)
This article delves into essential data management principles for data science projects. It stresses the importance of data quality, consistency, and documentation. It highlights the significance of understanding data lineage and maintaining a clear data pipeline. The article also discusses data governance, security, and ethical considerations in data science. Overall, it underscores that robust data management practices are crucial for successful and responsible data science initiatives.
Why Your Data Pipelines Need Closed-Loop Feedback Control (Towards Data Science)
This blog discusses the importance of closed-loop feedback control in data pipelines. It emphasizes that data pipelines should incorporate feedback mechanisms to detect and rectify issues, ensuring data quality and reliability. Closed-loop feedback systems help monitor, analyze, and adjust data pipelines in real-time, enhancing their efficiency and accuracy.
Will Big Data Be The Key To Affordable Precision Medicine? (Smart Data Collective)
This article underscores the significance of big data in enabling affordable precision medicine. It highlights that big data analytics can efficiently analyze vast amounts of patient data, genomics, and clinical information, resulting in personalized and cost-effective healthcare solutions. Big data plays a pivotal role in identifying patient-specific treatments and improving overall medical outcomes, making precision medicine more accessible and practical for patients while reducing healthcare costs.
5 Ways Dark Data Is Changing Data Analytics (Smart Data Collective)
This piece discusses five ways in which dark data is transforming data analytics. It highlights how previously untapped and unstructured dark data, such as social media posts and customer feedback, is now being used to gain valuable insights. Dark data is helping companies enhance customer experiences, improve decision-making, enhance security, and fuel innovation. By harnessing this unutilized data, organizations are uncovering new opportunities to drive business growth and improve their overall data analytics strategies.
Featured Articles on AI and Machine Learning
McKinsey partners with Salesforce to offer speedy AI adoption plans for enterprises (VentureBeat)
McKinsey has partnered with Salesforce to provide swift AI adoption plans for enterprises. This collaboration aims to assist companies in integrating artificial intelligence solutions into their operations more efficiently. The partnership leverages Salesforce's AI capabilities to create tailored AI strategies and solutions for businesses, aiming to accelerate AI adoption and drive innovation in the corporate sector.
As Senate tackles AI regulation, everyone has an opinion (except ChatGPT) (VentureBeat)
The article discusses the various opinions and perspectives on AI regulation as the Senate addresses the issue. It highlights that ChatGPT, the AI model in question, has remained silent on the matter, underscoring the need for AI systems to play a role in these discussions. It reflects on the importance of AI's involvement in shaping its own regulatory landscape and suggests that AI should be a part of the conversation regarding its governance.
Featured Articles on Leadership in Data
How to Have Better Strategy Conversations about Monetizing Data (MIT Sloan Review)
"Leaders can’t identify and manage data monetization opportunities if they can’t productively discuss the topic." This article emphasizes the importance of aligning data monetization efforts with overall business goals and suggests a structured approach to foster better strategic conversations on this topic.