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Without Uncovering Dark Data, You’re Not Uncovering Business Opportunities

In this special guest feature, Odhrán McConnell, Chief Technology Officer at Trint, points out that according to recent estimates, approximately 90 percent of a company’s data is dark, meaning it hasn’t been analyzed or leveraged to the benefit of the business. If you’re a business that uses any type of technology (which, in the year 2020, is likely almost everyone), you’re sitting on mounds of unstructured – and highly valuable – data.

The Future Outlook of Serverless

In this special guest feature, Emrah Samdan, Vice President of Products for Thundra, takes a look at the future outlook of serverless technology. The future of serverless and the production readiness of serverless for many use cases will continue to improve and the potential to cover many others is arriving. The industry expects serverless to be the default computing platform by 2025.

Decision Intelligence vs. Business Intelligence: What Is Your Company Running On?

In this special guest feature, Karl Hampson, Chief Technology Officer, AI + Data, for Kin + Carta, discusses two different perspectives for how your company’s data assets are being utilized: decision intelligence vs. business intelligence and what is your company running on.

Embracing and Leveraging the Data-Driven Pressure in Industry 4.0

In this special guest feature, John Joseph, CEO & Co-founder of Datanomix, explores why real-time actionable manufacturing data is needed for the entire organization to determine the true quote to cost value, how leveraging data analytics that can be learned, consumed, and responded to in seconds, not minutes or hours will set factories ahead – especially post COVID-19, and how to leverage data to make smarter business decisions and better quote to cash estimates.

The Evolution of ASR and How It Could Transform Your Business

In this special guest feature, Scott Stephenson, CEO of Deepgram, dives into the evolution of automatic speech recognition (ASR), popular use cases, current limitations, and a few predictions for how the technology will continue to evolve in the enterprise. The advent of Siri, Alexa and Google Home has made ASR increasingly popular. After all, ASR is the driving force behind a wide array of modern technologies. If you have a smartphone, for example, then you have ASR right at your fingertips. However, ASR is so much more than Siri or Alexa and has burgeoning potential across the enterprise.

MLOps Graduates to Enterprise Model Management (and what that means for global enterprise)

In this special guest feature, Mrinal Chakraborty, DISC Solution Leader at Pactera EDGE, discusses six core aspects of MLOps which are augmenting Enterprise Model Management. The MLOps market will be over $4 Billion in just a few years, and promises to be a major component of the AI solution landscape shortly – but many enterprises are slow to evolve to machine learning lifecycle management which promises to make ML more reliable by defining the processes of its development and deployment.

Starting A Successful AIOps Initiative

In this special guest feature, Hari Miriyala, VP Software Engineering at cPacket Networks, discusses how many enterprises are considering or deploying AI/ML tools to make their IT team more efficient, reduce troubleshooting time, or improve their organization’s security. But without the right foundation of accurate, precise and consistent input data, this move to AIOps provides little value.

Top 3 Data Analytics Challenges and How to Resolve Them

In this special guest feature, Jerry DiMaso, CEO and co-founder of Knarr Analytics, discusses how effective analytics has become such a determinative factor that it’s now evident that those who master it will thrive. However, the journey toward that goal isn’t without obstacles. What are the most common data analytics challenges and how can companies confidently confront them?

How to Truly Leverage Data for Asset Performance Management

In this special guest feature, Bryan Friehauf, EVP and GM of Enterprise Software Solutions at Hitachi ABB Power Grids, discusses how preventing information overload and an organizational attention deficit is crucial for every business. For the energy industry, despite having access to more data than ever, organizations struggle to make use of the right data. This becomes an issue for critical systems like asset performance management (APM).

Maximizing the Impact of ML in Production

In this special guest feature, Emily Kruger, Vice President of Product at Kaskada, discusses the topic that is on the minds of many data scientists and data engineers these days, maximizing the impact of machine learning in production environments. Data scientists and data engineers need integrated tools that speed the development and delivery of ML-powered products. ML platforms are an emerging solution embraced by many enterprises and are purpose-built to help get ML to production efficiently and reliably.