Analance

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4 Ways the Pharmaceutical Industry Can Benefit from Predictive Analytics

The world of pharmaceuticals is no stranger to data. Clinical research itself relies significantly on empirical data to test theories and determine treatment effectiveness. As the industry grows, so does the amount of data available. This offers a prime opportunity for pharma organizations to scale analytics adoption and incorporate more sophisticated data science techniques.

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Robotic Process Automation: What It Is and What It Means for Your Business

The data science world today is filled with so many terms that promise to facilitate digital transformation—robotic process automation (RPA) being one of them. Like related technologies, it is associated with optimized business processes and cost control, but how exactly does it accomplish these and what other opportunities does it provide your industry? Let’s explore this capability further.

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AI in HR: Helping Human Resources Be More Human

We’ve already made the case for how important analytics is in the field of human resources, but let’s not stop there. Organizations can take it one step further with AI-powered insights. Not only will artificial intelligence help streamline operations and improve efficiency, but it also plays an integral role in optimizing the human aspect of employee management: quality conversations and interaction, mentoring, and promoting motivation in the workplace.

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How to Build an AI Dashboard That Aligns with Your Brand

Dashboards—they’re the face of your analysis, the interface of your business. They help you organize and visualize your data and most importantly customize how you present intelligence to different stakeholders. They reveal valuable insights at a glance, keep you informed, and can chart your next steps to success. They ultimately serve the purpose of keeping everyone in the organization on the same page.

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Business Intelligence vs Advanced Analytics: Differences That Form a Powerful Team

In today’s technological landscape, businesses are more data-dependent, with vast pools of data at their disposal. What to do with it and how to make sense of it all is a challenge we attempt to solve with data science—starting with data discovery and ending with analytics that aid in critical business decision making. Now, there are numerous ways to extract meaning from data.

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5 Ways Stream Analytics Can Take Patient Care to The Next Level

The Internet of Medical Things (IoMT) is a connected system of smart medical devices and applications that have the capability to stream and process data wirelessly in the cloud. These connected devices remotely monitor patient vitals and activities, which can then be used by medical officers to administer proactive care with personalized treatment plans through stream analytics in healthcare.

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Quality Data = Quality Results: Why Data Quality Management Matters

Organizations across various industries capitalize on business opportunities with the help of advanced analytics that work to capture and convert data into value-creating insights. Capturing value from data needs a disciplined focus on data quality management to ensure the organization only harnesses good data for analysis to inform decisions and drive positive outcomes. However, failure to manage data quality will impose unwanted costs, risks, and reputation damage.

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4 Ways the Healthcare Industry Can Benefit from Predictive Analytics

In the realm of healthcare, data and reports have always played a significant role. Medical charts, electronic health records, health surveys—doctors, nurses, pharmacists, and hospital personnel have long relied on these to base their diagnosis and make their decisions. But a fast-paced industry will need more than just the basic patient intelligence and visualizations to keep up with the growing patient base and scientific demands.

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Data Collection, Preparation, and Cleaning: A Guide

What do data analysis and baking a cookie have in common? Well, aside from the fact that they both produce something valuable—one being insightful information and the other being a sweet treat—both also involve following a couple of steps before the final outcome. In the case of data analysis, there are three key tasks that need to be achieved before one can start analyzing data: data collection, data preparation, and data cleaning.

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Analytics in Marketing: Using Data to Drive Customer Delight

Gone are the days when marketers can simply claim that they have the leading product or service in the industry and then just hope for the best. These days, the effectiveness of marketing is maximized by focusing on the customer—planning around them, addressing their needs, and making them feel valued and heard. And incorporating data analytics in marketing is one way that businesses can discover insights into their preferences and trends to improve the customer experience.