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2022 and Vertical Industry Data — A Sleeping Giant Awakens

In this contributed article, Steven Schwartz, Chief Operating Officer (COO) of Narrative, believes this coming year will be the one that marketing a company’s data as a viable revenue-generating “product” will gain traction across a myriad of vertical industries. Businesses are looking for ways to expand their revenue lines, and data’s unique attributes make it attractive to sell, from a pure P&L perspective.

insideBIGDATA Latest News – 11/24/2021

In this regular column, we’ll bring you all the latest industry news centered around our main topics of focus: big data, data science, machine learning, AI, and deep learning. Our industry is constantly accelerating with new products and services being announced everyday. Fortunately, we’re in close touch with vendors from this vast ecosystem, so we’re in a unique position to inform you about all that’s new and exciting. Our massive industry database is growing all the time so stay tuned for the latest news items describing technology that may make you and your organization more competitive.

The Future of AI is the Edge; Can GPUs Take the Heat?

In this special guest feature, Ludovic Larzul, Founder and CEO, Mipsology, describes how in the future, AI will be everywhere. And though some computation will continue to take place in data centers, more will happen at the edge. There is just no other way for smart consumer devices, smart city applications and autonomous cars to work. As such, application developers must ensure that their designs work as well in the real world as they do in the climate-controlled lab.

How Edge Analytics could Drive the Next Wave of Digital Transformation

In this contributed article, Gary Ogasawara, Cloudian’s Chief Technology Officer, discusses how edge computing is still a work in progress. The first wave of digital transformation helped IT-focused companies gain a competitive edge. The next wave will extend existing cloud development practices, applications, and data models to the edge to help accelerate the digital transformation for other industries.

With More Data Comes Great Responsibility and a Need for Education

In this sponsored post, Dr Kendra Vant, Executive General Manager of data at global small business accounting platform Xero, discusses what responsible data use looks like in practice for tech companies and professionals. From strengthening insights into how a business operates and keeping businesses better equipped and informed, through to saving time with automation and even deepening a business’ understanding of its customers – the potential of data to make life easier for businesses and their customers is awe inspiring.

In the Roaring 2020s, Data Will Be Your Most Vital Asset

In this contributed article, Dimitri Sirota, CEO and co-founder of BigID, explains why contextual insight and automation is key to understanding data and why so many organizations need to re-think their understanding of effective data management to capitalize on the upcoming boom.

How to Evaluate Your Data Footprint

In this special guest feature, Ahson Ahmad, Chief Product and Customer Officer, Ripcord, presents an interesting take on ‘Data Heat’ which is how it’s possible to help customers determine which data to delete, and which data to store.

“Above the Trend Line” – Your Industry Rumor Central for 11/19/2021

Above the Trend Line: your industry rumor central is a recurring feature of insideBIGDATA. In this column, we present a variety of short time-critical news items grouped by category such as M&A activity, people movements, funding news, financial results, industry alignments, customer wins, rumors and general scuttlebutt floating around the big data, data science and machine learning industries including behind-the-scenes anecdotes and curious buzz.

2022 State of Data Engineering: Emerging Challenges with Data Security & Quality

The 2022 Data Engineering Survey, from our friends over at Immuta, examined the changing landscape of data engineering and operations challenges, tools, and opportunities. The modern data engineering technology market is dynamic, driven by the tectonic shift from on-premise databases and BI tools to modern, cloud-based data platforms built on lakehouse architectures.

Book Review: Synthetic Data for Deep Learning

“Synthetic Data for Deep Learning,” by Sergey I. Nikolenko (published by Springer), represents a very good academic treatment of the subject. But what gives the book more street cred is the fact that the author is also Chief Research Officer for Synthesis AI, a start-up company pioneering this accelerating field. It’s nice to know the book represents both the academic and practical perspectives of the topic.