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A Laundry List for Cleaning Messy Data and Making It Business Ready

In this special guest feature, Mark Palmer, TIBCO SVP & GM of Analytics, Data Science & Data Virtualization, believes that companies who learn to leverage their data will beat out their competition. Making data-driven decisions for business strategy is essential in today’s tech-centric environment, and anyone who is not taking advantage of the information they’ve gathered will fall behind.

Don’t Import It, Embed It! 5 Reasons to Embed Business Intelligence into Your Enterprise Applications

In this special guest feature, Daniel Jabaraj, Vice President of Syncfusion, Inc., discusses the 5 important reasons analyst firm Gartner lists embedded BI as important emerging tech, and reasons why it has the power to significantly affect how business is conducted in the future.

How AI and Behavioral Science are Addressing Vaccine Hesitancy

In this special guest feature, Ram Prasad, Co-Founder, The Final Mile, a Fractal Analytics Company, discusses how AI can help identify problem areas and how behavioral science could be pivotal in understanding why individuals have delayed immunization.

Before Jumping to Machine Learning, You Need a Solid Analytics Foundation

In this special guest feature, Michael Simms, Practice Director for Data & Analytics at Columbus Global Services, discusses four important elements of an effective data journey. Mapping a data journey provides awareness and understanding of where your organization is to ultimately get where you want to go, with enablement and adoption of the technology throughout. Without the clarity provided by a data journey, your organization won’t be positioned to successfully deploy the latest technology.

The Four Shifts Needed to Make Quantum Computing Part of Your Analytics Strategy

In this special guest feature, Christopher Savoie, Ph.D., J.D., founder and CEO of Zapata Computing, provides four necessary shifts organizations need to make to turn quantum computing from an exploration of an edge technology to production-ready technology that creates real value.

AIOps: The Iron Man Suit for IT Leaders

In this special guest feature, Josh Atwell, Senior Technology Advocate at Splunk, believes that by leaning into their data and embracing AIOps, IT teams are improving the customer experience. This begs the question: How can IT leaders leverage AIOps to build an informed plan that keeps up with the ever-changing demands of the business and customers?

APIs: The Real ML Pipeline Everyone Should Be Talking About

In this special guest feature, Rob Dickinson, CTO, Resurface Labs, suggests that to achieve greater success with AI/ML models, through accurate business understanding, clear data understanding, and high data quality, today’s API-first organizations must shift towards real-time data collection.

Four Capabilities to Look for in AIOps Tools

In this special guest feature, Girish Muckai, Chief Sales & Marketing Officer, HEAL Software Inc., discusses four critical capabilities to look for in AIOps tools. Every AIOps tool brings something unique to the table. Evaluating your options based on these four features can help ensure you are set up to move from a break-and-fix to a predict-and-prevent model.

Why Old-World Business Intelligence Is Not Enough to Navigate the New Normal

In this special guest feature, David Drai, Founder and CEO, Anodot, discusses how organizations that implement business monitoring and real-time analytics now will not only better manage challenging business conditions in the short-term but will be well-positioned for growth when economic recovery begins in 2022.

Democratizing Machine Learning to Empower the Modern Business

In this special guest feature, Adam Carrigan, Co-founder and COO of MindsDB, discusses how the democratization of machine learning makes predictive analytics accessible to companies of any size. While machine learning makes a transformative impact on the business world, it seems larger enterprises are the only ones reaping the benefits. So what about smaller and medium-sized businesses? Are they forced to remain on the sidelines of the AI revolution?