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Advance Your Data-Driven Programs with Self-Service Analytics

Data-driven decision-making is crucial for organizational success in the current business climate of heightened competition and constant change. Giving business users access to insights at the right time is a top business priority, but it is not easy to do this cost-effectively and on a large scale. Self-service analytics has been promising in this regard. Many businesses have focused on this in recent years, with mixed results. The main reason why self-service initiatives have failed in the past is because of the lack of a unified strategy and incorrect implementation. Having a clear plan and approach can increase adoption rates and advance your data-driven programs. InfoCepts’ various self-service powered solutions and industry innovations have helped clients realize the full potential of their data for faster insights and smarter decisions. . In this blog, we share some self-service implementation tips for success. 1. Clearly define what self-service analytics means to your organiz
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Data Storytelling 101: Best Practices and Tips to Build Your Data Stories

  Humans are natural storytellers. Storytelling has always been a primary means for transmitting knowledge across groups of people, resulting in the formation of cultures and enabling evolutionary success. And now as we enter the digital age where data is the primary currency, we turn to  data storytelling  yet again to communicate complex information, using compelling narratives customized for specific audiences to increase engagement and user adoption. Understanding   data storytelling Data in itself cannot resonate with humans as effectively as stories can. With stories, you get a distinct start, middle, and ending. They have a narrative flow and repetition; they tie information together, providing a framework that the audience can easily follow. While data describes what is happening, stories indicate why it is happening. That said, it takes specific skills and tools to effectively communicate findings to others and convince them to take action. What are the skills requir
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Six Practical Applications of Real-Time Analytics in Healthcare

  Real-time analytics can deliver operational, financial, and clinical improvements to healthcare providers and organizations worldwide. Post the COVID pandemic, organizations are looking to improve patient engagements quickly with real-time decision making, modernize electronic health records system, and accelerate the process of saving lives by digitizing critical business processes. Most recent forecasts indicate that health-related analytics, its applications, and the overall market will grow to $28 billion by 2025--and it's easy to see why. Data and analytics combined with modern innovations in AI and ML can help organizations focus on improving patient care, build smart clinical solutions with real-time actionable insights, and better safeguard patient records.   Here we share six pragmatic applications of real-time analytics in the healthcare industry: 1 . Forecasting patient load and utilization pattern Similar tohow analytics is being widely used in the transport indus
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