In this contributed article, Ellie Dobson, VP Product at Apheris, suggests that organisations know that data is often the most valuable asset that they own. But unlocking the full potential of these data assets is difficult in the face of privacy and security concerns. This is compounded by a lack of existing infrastructure that allows for collaboration across organisations.
AI Isn’t Screenwriters’ Enemy – In Fact, It Can be a Creative Superpower
In this contributed article, Ben Pines, director of content at AI21 Labs, discusses how generative AI can help screenwriters—not put them out of business, a concern that many have expressed and which is also among the reasons the Writers Guild of America went on strike.
Get Lit: 5 Steps to Building your Organization’s Data Literacy as you Prep for AI
In this contributed article, Christine Andrukonis, Workplace Transformation Expert and founder of Notion Consulting, believes that the ultimate goal of data literacy is to provide a framework for data-driven decision-making. Nothing is stopping you from developing a learning program that’s also fun, engaging, and beneficial to employees in all parts of their lives.
Tips for Responsible Use of Generative AI in Enterprise
In this contributed article, Thor Philogéne, CEO and Founder of Stravito, discusses how the effective integration of generative AI in enterprise requires the identification of clear goals and pain points; reliable data and a human-centric design.
Three Roadblocks to Using Data to Its Full Potential
In this contributed article, Sridhar Bankuru, VP of Software Development at RightData, walks us through the top pain points of businesses today within their data trust journey, and looking ahead, how they can start trusting their data again.
Rethinking How Data is Stored and Processed Brings Scale and Speed to Modern Data-Intensive Applications
In this contributed article, Prasad Venkatachar, Sr Director – Products & Solutions at Pliops, discusses how modern data-intensive applications that include E-commerce, Social Networking, Messaging, and online gaming services heavily depend on Key-Value stores. All these business-critical applications demand state-of-the-art data storage and processing infrastructure to serve the data at high throughput with low latency and highly fault-tolerant and yet cost-effective. To achieve this blend of high performance and cost effectiveness, we must fundamentally reimagine how data is stored and processed at scale and speed. This article will cover how organizations can accomplish these design objectives and architect state-of-the-art data storage and processing infrastructure.
Finding a Purple Swan with Predictive Analytics
In this contributed article, Vijay Veerra, Principal Consultant of Business Solutions and Research with Altimetrik, discusses the power of predictive analytics in identifying “purple swans” and their potential impact on businesses. Purple swan refers to a rare yet foreseeable event that offers unparalleled rewards. This article explores how companies can use predictive analytics to spot these events on the horizon, set their course accordingly, and sail toward a promising future.
GenAI’s Role in Testing
In this contributed article, David Brooks, SVP of Evangelism at Copado, discusses how much has been said about AI’s ability to generate code. But what is often overlooked is its ability to generate test scripts as well. Test scripts are susceptible to hallucinations just like code. So while GenAI can easily create the script, it is your responsibility to review the results.
Starting Your Advanced Analytics Journey: Three Areas to Focus On
In this contributed article, Amish Amin, executive director, security and analytics, Comcast, discusses the importance of advanced analytics when it comes to cutting through the massive amounts of data within a single organization. In large organizations today, the amount of data that needs to be sifted through continues to grow in volume. In fact, the global datasphere is expected to
more than double between 2022 and 2025. Not only is there an incredible amount of information, but there aren’t enough people to properly analyze it all. In his piece, Amish explains that by applying advanced analytics, organizations can drive valuable insights, cut through the noise and, ultimately, increase efficiency. He also outlines three areas to consider when it comes to an advanced analytics initiative and four best practices.
AI Won’t Eliminate Programming, But Can Make It Better
In this contributed article, Mike Loukides, Vice President of Emerging Tech Content at O’Reilly Media, makes the argument that the number of programmers who will be “replaced by AI” will be small and explains how the use of AI will change the discipline for the better.