Data Management is a fundamental element of successful #clinicaltrials. #QPS data management services include data coding, compliance outputs, and publication and presentation materials. To learn more, visit our page https://shorturl.at/ipt7H or email info@qps.com. #datascience
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helping with data automation, visualization, and PDSA quality improvement for behavioral health and human services - #qualityimprovementdad
Data lies, data cheats, and data steals. Just ask Mr. Analystowski. ❌ Data lies all the time when your governance doesn't enforce key point collections. ❌ Data cheats when you make decisions without considering that clinical context might explain that the data actually shows the way you want it ❌ Data steals time away from clinical work when supervisors spend hours and hours on exports, pivot tables, grant reports, and analysis that are old the second they are finished. At CCNY, Inc.: ✅ We are supporting clinical staff to restore your time for clinical work by automating data movements. ✅ We are supporting data deficiency reporting so that you can know your data has fidelity and measurements have enough integrity to be trusted. ✅ And we are supporting quality improvement initiatives that properly evaluate data within the context of your clinical process So - if data is just the data. What are you doing to abide? #behavioralhealth #qualityimprovement #data
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Clinical Data Management Syllabus Here's a detailed syllabus for an online course on Clinical Data Management (CDM), covering the setup, conduct, and closeout phases
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Head of Open Data Products, Open (Source) Data Product Specification maintainer, Books authored: Terraforming Data Product Governance, AI-Powered Data Products, Deliver Value in the Data Economy, and API Economy 101.
Exploring the Frontier of Data Products: Seeking Insights on Emerging Standards I'm on a fascinating journey, delving into the evolving world of data products and their emerging standards. My research so far has introduced me to a range of intriguing concepts like the Open Data Contract Standard, Data Contract Descriptor, Data Product Descriptor Specification, and the Open Data Product Specification. While familiar with DCAT, my focus is on the newer, cutting-edge standards that are shaping our industry. I'm reaching out to this knowledgeable community for insights. Are there other emerging standards in data products that I should be exploring? Any new developments or initiatives that are gaining traction? Your expertise and any pointers you can provide will be invaluable in broadening my understanding of this rapidly progressing field. All tips, resources, or thoughts on this topic are welcome and greatly appreciated. Looking forward to your input and sparking some enlightening discussions! #dataeconomy #standards #dataproducts
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If you research it, we can support it! Understanding the importance of utilizing QDA software is crucial for effective research practices and outcomes. Explore this comprehensive guide on qualitative data analysis techniques to enhance the integrity of your analysis no matter your field of study or market. Uncover best practices and practical applications of various methods to improve the accuracy of your work and gain deeper insights into qualitative data analysis. [Read more](https://lnkd.in/g5gV3eWz) #ResearchAnalysis #QualitativeData #DataAnalysis #ResearchInsights #NVivo
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Person 1: “What is data redundancy and why should we avoid it?” Person 2: “Great question! Data redundancy is like having multiple copies of the same book scattered around your house. It takes up extra space and makes it harder to keep track of things. In databases, data redundancy means storing the same piece of data in multiple places, which can lead to inconsistencies and errors. Real-life example: Imagine a hospital’s patient management system where a patient’s address is stored in both the billing and medical records. If the patient moves, you have to update their address in multiple places. If you miss one, you end up with conflicting information. Avoiding redundancy means updating the address in one central place, ensuring accuracy and saving storage space.” #DataRedundancy #DataManagement #DataIntegrity #DataCleaning #DataScience #TechExplained #DatabaseManagement #Efficiency #AccurateData #BigData #data #linkedinlearning #dailyposts #learningjourney #analyst
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Epidemiology & Biostatistics Consultant a/k/a Data Scientist | Exclusive and innovative solutions for data science challenges in public health, research and education
What are data? Well, they are measurements. They are just values. What do they mean? Well, it depends on the context. If you are used to research datasets, then it’s easy to know what the data points mean as measurements. But what if you are dealing with data coming from applications? Then it gets a little harder! If you want to break through communication barriers to get the answers you need to complete an analysis of data from applications - and be seen as an expert – register for our upcoming online workshop, “Application Basics – Crossing Domains”! #R4sasUsers #DethwenchLive #healthcare #dataanalytics #rstats gur saran Rowena Isabelle Magat Kotari Abhishek Makayla Aleksich Anushka Bhattacharya Samrit Pramanik Wicliff Chomba
Since we entered the era of Big Data, the boundaries between healthcare data and data in other domains (such as business) have become blurred. Healthcare data analysts are often expected to be able to apply research designs to data originating in healthcare and other applications. Rigorous data science requires careful planning, which can be challenging when you are limited to using application data to generate your results. If you want to understand datasets from applications well enough to analyze them and produce results, register for our online workshop. With the knowledge you gain from this interactive workshop, you can break through communication barriers to get the answers you need to complete your analysis and be seen as an expert! Title: Application Basics: Crossing Domains Dates: Saturday and Sunday, April 27 and 28, 2024 Timing: Each session starts at 12:00 pm ET and runs about 3 hours Register here: https://lnkd.in/eisytH3j
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Epidemiology & Biostatistics Consultant a/k/a Data Scientist | Exclusive and innovative solutions for data science challenges in public health, research and education
If you have the skills of research design and statistics, you theoretically should be able to apply scientific inquiry to many fields. But it’s not easy when you are not using your own measurements for your analysis! What if you have to take data that are just lying around in business applications, and turn them into something meaningful? Being able to practice data science in many fields starts with understanding the data, and the underlying measurements. If you are interested in practicing data science in many fields, join me this weekend for our online workshop, “Application Basics – Crossing Domains”! The workshop will help you break through communication barriers when dealing with data outside your domain to get the answers you need to complete your analysis and be seen as an expert! #R4sasUsers #DethwenchLive #healthcare #dataanalytics #rstats chandana Jasti Derek Baker, MPH Austin Anders JOYDIP PAL, MBA, SAS® Rajesh Enjamoori Pradip Nakadee Alice McKnight, MPH Quintin C. Latin, CISO, CEH, CHFI
Since we entered the era of Big Data, the boundaries between healthcare data and data in other domains (such as business) have become blurred. Healthcare data analysts are often expected to be able to apply research designs to data originating in healthcare and other applications. Rigorous data science requires careful planning, which can be challenging when you are limited to using application data to generate your results. If you want to understand datasets from applications well enough to analyze them and produce results, register for our online workshop. With the knowledge you gain from this interactive workshop, you can break through communication barriers to get the answers you need to complete your analysis and be seen as an expert! Title: Application Basics: Crossing Domains Dates: Saturday and Sunday, April 27 and 28, 2024 Timing: Each session starts at 12:00 pm ET and runs about 3 hours Register here: https://lnkd.in/eisytH3j
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🔍 𝐃𝐚𝐲 𝟏𝟗 𝐨𝐟 𝐭𝐡𝐞 𝟑𝟎-𝐃𝐚𝐲 𝟑𝟎 𝐂𝐡𝐚𝐥𝐥𝐞𝐧𝐠𝐞 𝐨𝐧 𝐂𝐥𝐢𝐧𝐢𝐜𝐚𝐥 𝐃𝐚𝐭𝐚 𝐀𝐧𝐚𝐥𝐲𝐭𝐢𝐜𝐬 💡 𝐂𝐡𝐞𝐜𝐤 𝐪𝐮𝐞𝐬𝐭𝐢𝐨𝐧 𝟏𝟗: How do you ensure data quality, integrity, inconsistency, and accuracy in clinical data analytics? Data quality and integrity are ensured through: 🔍 Data validation 🧹 Data cleansing 📏 Data standardization 📝 Regular audits 🔍 Quality control checks These steps are crucial for maintaining reliable and accurate clinical datasets. 🏥📊 𝐑𝐞𝐚𝐝𝐲 𝐭𝐨 𝐥𝐞𝐚𝐫𝐧 𝐚𝐧𝐝 𝐠𝐫𝐨𝐰? 📈 👉 Follow The Whiteboard 👍 Like this reel and tag a friend who might be interested 💬 Get ready to dive deep into ensuring data quality 💪 𝐂𝐨𝐧𝐭𝐚𝐜𝐭 𝐮𝐬 at +91 9160794975 or mail us at info@thewhiteboard.co.in #TheWhiteboard #DataQuality #ClinicalData #HealthcareAnalytics #DataScience #DataAnalysis #DataValidation #DataCleansing #DataStandardization #LearnAndGrow #TechInHealth
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Principal Analyst Data Governance | Posting commentary for analysts since 2017 | Brier Score of 0.211 | Experimental science: show me the evidence | Veritas filia temporis | Views mine own
This is a useful report by the UN Economic Commission for Europe on data stewardship and its relationship to the two other parts of the data triad, governance and management. Here in NZ we're fortunate to have a Government Chief Data Steward based out of our national statistics office, StatsNZ. Interesting that five of our bigwigs took part in the study, a useful working group for us to be part of and contribute to. The NZ team put together Chapter Four, data governance models and data stewardship. #datagovernance here means the system of decision rights and accountabilities for the management of the availability, usability, integrity and security of the data and information, and the resulting regulations, policies and frameworks that provide enforcement. #datastewardship here means ensuring the ethical and responsible creation, collection, management, use and reuse of data so that they are used for public good and benefit the full community of users. #datamanagement here means the development, execution and supervision of plans, practices, concepts, programs and the accompanying range of systems that contribute to the organization and maintenance of data processes to meet ongoing information lifecycle needs. Our current industry phase is chock-full of frameworks etc etc etc which all fall somewhere on a continuum between complementary and rivalrous. This report helped me put these three professional approaches in a useful relationship. It's a great read and a welcome contribution by the representatives of national statistics offices which I've used to good effect in several public sector verticals.
Data Stewardship and the Role of National Statistical Offices in the New Data Ecosystem
unece.org
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If there is one core lesson I'm learning as a data consultant, it's this - This stuff takes TIME. 🕜 Being a relationship-based service business, engagements take a while to convert. You need to prioritize enriching those relationships and delivering quality work. Remain patient. Quality work and Referrals are a HUGE source of pipeline health. #consulting #analyticsengineering
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