Data Accessibility - Pillar 2: Usability - Raw data alone doesn’t create value, it must be structured and consumable. Having access to raw data is not enough, it must be structured, understandable, and ready to use. True data accessibility means presenting information in ways that both people and systems can easily interpret and act on — through dashboards, reports, APIs, or simple exports. Example: A healthcare provider once relied on technicians to manually extract patient records from multiple systems before doctors could review them. With a unified, usable data API, doctors can now access accurate patient histories in seconds, enabling faster and safer treatment decisions. You can take a look at "The 5 Pillars of Data Accessibility" on our blog: transformz.ca/blog/the-5-pil… #DataAccessibility #DataUsability #DigitalTransformation #TransformZ #Automathing

Explore how data usability and the Taking Root Movement are driving true interoperability forward. 🚀 #InteropDoneRight #CommonWell #DataUsability #SequoiaProject

Thanks for the reminder! Looking forward to learning from Didi Davis and diving deep into data usability and the Taking Root Movement tomorrow. #InteropDoneRight #CommonWell #DataUsability #SequoiaProject

🔔 Reminder: Interoperability Unlocked is TOMORROW, May 22! Join us at 12 PM ET for a special session with Didi Davis from The Sequoia Project as we dive into Data Usability and the Taking Root Movement. Don’t miss it! #InteropDoneRight #CommonWell #DataUsability #SequoiaProject

Raw data isn’t enough—it needs to be organized, accessible & actionable. EMPEQ CEO @HerbertDwyer and Aiman Al Sakka, P.E. break down how usability turns data into smarter decisions. 👉 Learn more: empeq.co/what-makes-data-usa… #DataUsability #TechInsights #SmartDecisions #Innovation

Balancing data security and privacy with accessibility and usability can indeed be challenging, but here are some strategies to help mitigate the conflict: foxconsulting.co/post/striki… #datasecurity #dataprivacy #dataaccessibility #datausability #datagovernance #dataencryption

Today I would like to discuss about one of my #DataAnalysis projects that I built. The name of that project is “Salary Analysis”. Here, I analysed the salary of various job titles. I used #Python, #Pandas to manipulate/analyse the data and #Plotly to visualize. Check Project from Here :- ujjwal01.com/index.php/salar… Let’s discuss about various challenges/problems that I faced in this project and how I as a #dataanalyst solved them so that aspiring #dataanalysts can understand that every problem, limitation, or error needs a different methodology. 1) Dirty Data :- I got data from #Kaggle for this project and even it had good usability score, I was concerned about accuracy, cleanliness, and consistency. What I did :- Loaded dataset into the database and checked for the basic properties such as relevant data types, missing values, data consistency, redundancy and more. Using operations such as “UPDATE”, “ISNULL”, “COALESCE”, “TRIM”,” DISTINCT” were common. What can you learn :- Make sure to check for these things in the data especially data types as they can completely ruin or limit your data analysis if they are wrong according to the actual data of that column. Don’t consider the usability score on #Kaggle as the ultimate factor for #dataintegrity, #dataconsistency, and #datausability. 2) EDA :- On performing #EDA, when I selected various experience level to have a better understanding about the salary trends, I saw significant salaries such as 300k USD for mid-level experience for a #DataAnalyst. What I did :- I quickly understood that outliers are present in the data and performed box plot technique to remove outliers from the dataset. After doing thorough EDA again, I got consistent and logical trends which were acceptable. What can you learn :- Never run to create visuals after basic cleaning of the data, always perform EDA, if you have not removed outliers in the data cleaning process. Also, sometimes outliers contribute to critical analysis which simply means that data or outliers provide critical analysis and contribute results to the analysis, so you should not remove outliers in those scenarios. 3) Representing Analysis using Visuals :- I used #plotly to visualize the insight and I was getting the problem of limited visuals to efficiently convey the insight. I was getting stuck at only few visuals such as bar charts, line charts, scatterplots etc. What I did :- I noticed problem, which was for similar insights, I had to create separate tabs for visuals such as for different experience level, I had different visuals in different tabs which was inefficient. So, searched on the #plotly documentation and got to know about “facet columns” that allows us to create multiple visuals according to the criteria that we pass it, I used it. What can you learn :- Always use documentation of libraries/technologies, it’s really powerful. #datanalysis #dataanalyst #businessanalyst #Python #pandas #plotly

🌟 Join us for a special session on advancing data usability in healthcare with @sequoiaproject at #HIMSS24 in @ClinicalArch booth #2281 at 2-2:40 PM! Featuring Didi Davis, Dr. William Gregg w/ @HCAhealthcare & Charlie Harp. #DataUsability Register Now! ➡️ hubs.ly/Q02lf5170

#ResearchShowcase: Daria Kim (@mpi_inno_comp) and Man Wai Kwok critique the EU Data Act for inadequately addressing data usability within its framework, highlighting unclear technical concepts. Read the full paper here: papers.ssrn.com/sol3/papers.… #EUDataAct #DataUsability

I am really looking forward to participating in the #StateofInterop23 Propelling Interoperability Through Data Quality and Usability panel today. There is still time to register for this fantastic line up of speakers today. #Interoperability #datausability @sequoiaproject

Gratitude to @BCILifeSciences for fueling our recent Leadership Think Tank on Data Usability! Your support made rich discussions possible, unveiling valuable insights. These sessions strengthen the AONL Foundation. 🌐🤝 #LeadershipThinkTank #DataUsability #HealthcareInnovation

Happening now in📍Washington, DC: The Data Usability Taking Root Summit is kicking off its first in-person meeting! Thank you to our Taking Root Initiative co-sponsors @AHIMAFoundation #datausability #interoperability @DidiDavis @MariannYeager

Looking forward to seeing you at the @sequoiaproject #DataUsability Taking Root Summit tomorrow and many thanks to @healthgorilla for supporting this important work to advance #Interoperability and #quality of data exchanged in the real world.

Big post-holiday week. Heading now to DC for tomorrow’s @sequoiaproject #DataUsability Taking Root Summit, then back in time to present at Thursday’s virtual @ONC_HealthIT #DataQuality Symposium with a group of #HealthData rockstars. Fun and learning together!

Check out @DidiDavis on stage at #HIMSS23 talking #datausability, happening now!

Continuing progress in #HealthData #interoperability. These numbers don’t lie. Now we focus on #DataQuality, #DataUsability and workflow integration.

Hot Off The Press: The Data Usability Workgroup released the final Implementation Guide and encourages industry adoption into 2023. Join us at #SEQ22 to hear more! View the IG and more here: bit.ly/3uMUKoe #Interoperability #datausability

Today is the last day to submit feedback on the draft #DataUsability Workgroup Implementation Guide! Learn more about the guide and submit feedback today: bit.ly/3eAwdy6

How do #EducationInEmergencies professionals think about & use data? @LizzieBuckner @ddshep & @anniecsmiley offer insights from #EiE pros across sectors & levels, and detail other factors that influence #DataAccess and #DataUsability in @JournalonEiE. doi.org/10.33682/tgfd-m9eg

Building a Mature Data Infrastructure to Accelerate Data Usability bit.ly/2OTNupn #DataInfrastructure #DataUsability #DataDemocratisation #DigitalTransformation #CloudComputing #DataAnalytics