Quantitative Maximization
Companies and organizations are collecting an increasing amount of data in this rapidly expanding digital age. However, there is not always a direct correlation between the amount of information/data collected and the value of the data. Our multi-disciplinarian team has extensive experience across all prominent analytic platforms, software packages, and data collection programs to maximize the value from your quantitative data.
Data Opportunities
What is it? There is a growing consensus that quantitative data is quite valuable, but difficult to tap into and leverage it for the valuable asset it is. Maximizing the value of quantitative data requires insight into managing and optimizing multiple data sources and creating the infrastructure to streamline capturing data and getting the most of it. If you want to take advantage of the near limitless power of your data, most of which you are probably already collecting, you need to be confident that you have the right system in place to integrate multiple data sources and access relevant findings from your data.
Most companies and organizations do not need to collect more data, but rather they need to integrate data from multiple sources and optimize the return on investment from the data they already have. There are other options for collecting data from secondary sources or previous data studies and reviews. Only when you have obtained a comprehensive and accurate portrayal of the story told by your data can you truly determine how to expand or improve your data processes.
Let our team help you integrate multiple data sources, and help you build a comprehensive quantitative data collection and optimization strategy to unlock your data’s power.
How can we help you?
- Build data processes for your company or organization to merge multiple data collection strategies and software.
- Integrate data across all major statistical software packages from the most end-user accessible to higher machine learning
- Review current data processes to identify opportunities to get more from your data
- Assess current data sources and optimize data collection moving forward
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A dashboard is a management tool that visually tracks, analyzes, and displays key points by combing multiple data views and graphs.
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Instrument development refers to the development of new measurement scales, while instrument modification or enhancement may refer to improving existing instrument.
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Learn MoreArticles and White Papers About Data Opportunites
Why You Should Go Beyond Microsoft Excel (Part 1)
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How Do We Cultivate a Data-Informed Culture?
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Data-driven Decision Making: 5 Best Practices for Leveraging Quantitative Insights
Introduction According to an article from the Harvard Business School, well-informed decisions incorporate both intuition and data.[1] Research suggests that intuition is particularly valuable when a set of circumstances is quite uncertain—even risky, at times—and when additional data collection may not make decision-making any earlier. Intuition may, in fact, be...
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Maximizing Quantitative Data Opportunities for Independent Researchers: 5 Key Techniques
Introduction Independent research, sometimes referred to as “indie” research,[1] is defined by its dynamic nature: as the name suggests, independent researchers generally dictate their own research activity in terms of topic and so forth.[2] Independent researchers are indeed often afforded many opportunities generally not available to more traditional academic researchers;[3]...
Read MoreFAQ About Data Opportunities
Everyone knowingly or unknowingly misses out on major data opportunities. Determining the usefulness and costs of acquiring or ignoring data opportunities generally requires a multidisciplinerian team of individuals with diverse research background and connection to data systems and sources.
There are many academic, philanthropic, governmental, and professional sources of data that are available for free, at low costs as well as higher costs. Understanding the benefit, need, and fit for these alternate data sources will help determine which sources can be practical and profitable for your needs.
Data reviews will generally save time and money that reasonably and affordably replicate research that is helpful, necessary, or enlightening in areas of a program or project that will impede, expedite, or ignore critical components of whatever you are trying to do.
Predictive analytics and machine learning take information that is readily available to you and make predictions about future events based upon your data, existing theories, algorithms, and probability. These approaches may help identify future opportunities and threats in ways that allow you to have as much control and time to react to imporant events as possible.
Good research design is well balanced, usually incorporates a mixed method approach combining quantitative and qualitative processes and is fully informed by known assumptions and limitations given constraints, targeted outcomes, and informed input by requisite stakeholders.
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Peggy Ostrander, DNPc, APRN, FNP-C Plano, Texas