Welcome to insideBIGDATA’s “Heard on the Street” round-up column! In this regular feature, we highlight thought-leadership commentaries from members of the big data ecosystem. Each edition covers the trends of the day with compelling perspectives that can provide important insights to give you a competitive advantage in the marketplace.
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.
What is a RAG?
In this contributed article, Magnus Revang, Chief Product Officer of Openstream.ai, points out that In the Large Language Model space, one acronym is frequently put forward as the solution to all the weaknesses. Hallucinations? RAG. Privacy? RAG. Confidentiality? RAG. Unfortunately, when asked to define RAG, the definitions are all over the place.
Happy Birthday ChatGPT!
Today, November 30, 2023, mark’s the first anniversary of OpenAI’s ChatGPT. In the last year, the AI chatbot has secured support from major Silicon Valley companies and seen integration across various fields including academia, the arts, marketing, medicine, gaming, and government. These are exciting times, so we decided to put together this round-up of commentaries from around the big data ecosystem. Enjoy!
Altair® Launches Altair RapidMiner® 2023 Platform To Deliver Next-Gen Gen AI Capabilities
Altair (Nasdaq: ALTR), a global leader in computational science and artificial intelligence (AI) announced that Altair® RapidMiner®, its data analytics and AI platform, is becoming more integrated, more powerful, and easier to use thanks to a new series of groundbreaking updates.
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.
Four Ways SMBs Can Harness the Power of Data, Without a Data Scientist
In this contributed article, Robyn Meyer, Vice President, Solutions at Transportation Insight, delves into the challenges faced by small and medium-sized businesses (SMBs) in leveraging data effectively and offers practical strategies to overcome these hurdles.
Heard on the Street – 11/27/2023
Welcome to insideBIGDATA’s “Heard on the Street” round-up column! In this regular feature, we highlight thought-leadership commentaries from members of the big data ecosystem. Each edition covers the trends of the day with compelling perspectives that can provide important insights to give you a competitive advantage in the marketplace.
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.
Emerging Tools and Frameworks in AI: A Comparative Analysis
In this contributed article, graphic designer and content writer, Erika Ballo delves into some emerging tools and frameworks in AI, comparing their strengths, usability, and ideal use cases.