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4 Ways to Democratize Analytics and Data Science for Continuous Intelligence

Blog: The Tibco Blog

For digital businesses today, acquiring data is one of the most critical actions it can take. However, the data renders useless unless businesses leverage it to achieve actionable insights. Enter, continuous intelligence. 

According to Gartner, continuous intelligence is defined as a “design pattern in which real-time analytics are integrated into business operations, processing current and historical data to prescribe actions in response to business moments and other events.” With continuous intelligence, you can inform every decision, ensure optimal outcomes, guide every interaction, and drive every process of your digital business. In fact, by 2022, more than half of major new business systems will incorporate continuous intelligence that uses real-time data to improve decisions. 

As indicated by Gartner, continuous intelligence is going to be one of the top 10 data and analytics trends for 2020. Continuous intelligence is comprised of two essential elements: analytics and data science, and situational awareness. But, in order to unlock the full potential of these elements, you must democratize them. 

The infusion of AI and automation in analytics and data science is democratizing these technologies, giving more users across an organization faster access to deeper, actionable intelligence. These innovations empower business users, data analysts and data scientists, to have the best capabilities for their roles yet work collaboratively to provide continuous intelligence for the business across strategic through operational use cases.

Democratize analytics and data science to unlock your data’s full potential

Here are four ways to democratize analytics and data science (otherwise known as augmented intelligence according to Gartner) for continuous intelligence:

1. Search-driven analytics: Natural language interfaces to speed up finding and delivering insights. 

2. AI-powered insights: Machine learning to speed up data preparation, insight discovery, analysis, and delivery of insights. 

3. Embedded data science: Using data science with the user simplicity of analytics dashboards for high-value use cases. 

4. Streaming analytics & data science: Applying analytics and data science on streaming data at critical business moments. 

Watch this webinar to learn more about each of these ways to democratize analytics and data science for continuous intelligence, complete with relevant demos and use cases. 

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