Tagged: #22828
- This topic has 23 replies, 14 voices, and was last updated 3 years, 7 months ago by Navinee Kruahong.
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2020-09-17 at 11:54 am #22545SaranathKeymaster
Can you give an example of data that you think it could be considered as “Big Data”?
What are the characteristics of the data that fit into 5Vs, or 7Vs, or 10Vs of Big data characteristics?
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2020-09-22 at 8:01 pm #22689Sila KlanklaeoParticipant
In my opinion, The HDC’s 43 files data of the Ministry of public health of Thailand is the Big Data.
The characteristics of the data that fit into 10Vs of Big data characteristics. -
2020-09-26 at 5:46 pm #22777Kridsada SirichaisitParticipant
I think HDC is not big data because of no Variety of data. 43 files is character data that collect from HIS. 43 files tables are structured data. HDC service is the frontend of HCD on cloud but I think i doest not calculate from Hadoop.
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2020-09-26 at 5:48 pm #22778Kridsada SirichaisitParticipant
Facebook is a 10 Vs big data model.
1. Volume
2. Velocity : Facebook have own techonology in backend and fronend for optimise velocity
3. Variety : text image vdo
4. Veracity
5. Variability
6. Validity : may not valid in some content
7. Viscosity
8. Volatility
9. Visualization
10. Value : data was used in many purposes that include e-commerce -
2020-09-27 at 2:29 am #22802Ornpicha ThiampolParticipant
I think data that generate in “youtube” could be considered as Big Data. It’s fit to 10 characteristics.
1. Volume – there is a huge amount of information generated every second like a video, audio and etc.
2. Variety – The data is in the form of text, video, audio, and many more.
3. Velocity- There is a massive and continuous flow data. Youtube generates and processes the data very quickly.
4. Value – Youtube contains an amount of valuable, reliable, and trustworthy data
5. Veracity – The data is sometimes messy and bad quality so it is difficult to control.
6. Variability – There is some inconsistent speed at which big data is loaded into the database.
7. Validity -Youtube will ensure consistent data quality and accuracy. So sometimes we can report inaccuracy data
8. Vulnerability
9. Volatility
10. Visualization -
2020-09-27 at 3:16 am #22803Wachirawit SupasaParticipant
I considered Human Genomic Data as Big Data and It would be fit in 10V Catagories.
1. Volume – Because everyone has different DNA, if we sequencing all of the DNA base pairs, it will take about 200 gigabytes of data and that came from a single human individual alone. Try sequencing all Thailand population, it would take space in the database about 14 exabytes or 14,336 petabytes! However, only 0.1 percent of the human genomic is different so it would take about 125 megabytes, still, it would be a lot of data.
2. Velocity – According to Thailand Statistics, in 2019, there are 700,000 babies born per year or about 2,000 per day. That means the data will be generated about 250 gigabytes per day.
3. Value – There are many benefits from the sequencing genome. We can detect for abnormalities such as Genetic disease or allergy or even predict potential offspring genetic disorder from current parental planning.
4. Variety – Although all human genome consisting only of ATGC base pair but we can regrouping them into the pattern for certain abnormalities that can fasten quarry by computer algorithms.
5. Variability – There are multiple ongoing projects that searching for genetic disorder and we can use the result applies to our database to detect abnormalities.
6. Veracity – Today with our current technology, we can sequence the human genome only in one or two days. And the probability of error is lower than before. We can use multiple companies to sequence and correlate the genome into data we can trust.
7. Visualization – There are many applications from a different company that takes our DNA sample, sequence, and visualize information into easy to read interpretations such as circleDNA, 23andMe, Ancestry, etc.
8. Vulnerability – Because each genome data is very sensitive information, there’s a risk from the data breach that can expose information into public space without consent.
9. Volatility – Some deceased genome may consider obsolete since we cannot conduct any further experiments or information that may not benefit to owner anymore.
10. Validity – We must ensure that genomic data we kept is regularly maintained and free from data corruption that can cause misinterpretation later on.
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2020-10-04 at 1:38 pm #22989Kaung Khant TinParticipant
That’s a distinctive approach to Big Data. Impressive, sir. And I think the human genomic data is the structured data. Anyway, the abnormalities in the DNA sequencing would need some processing before going into analytic process.
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2020-09-27 at 2:23 pm #22806Pongsakorn SadakornParticipant
I will consider the data of E-commerce like Shopee as a 10Vs of Big data.
1. Volume – Shopee has a million data which is including the data of the user and the shop owner.
2. Variety – The variety of data in Shopee is from structured data or semistructured data such as the identity, text, video, hyperlink, audio, etc.
3. Velocity – Both frontend and backend of the website or database generated, created, and refreshed the information continually.
4. Variability – Sometimes, there is an inconsistent speed when the data loaded into your database.
5. Veracity – The unfortunate characteristics of data may cause the confidence or trust of the data.
6. Validity – Shopee is sometimes that is accurate and correct for the user.
7. Vulnerability – Shopee emphasis security concerns because each policy has been always noticed about personal security.
8. Volatility
9. Visualization – Shopee is a good example of a smooth and visual application.
10. Value – The content of data in Shopee is the most important for the user side and the shop owner’s side. -
2020-09-27 at 8:02 pm #22814NaphatParticipant
In my opinion I think “The weather data of Meteorological Department” is a big data and fit to 10Vs of Big data characteristics.
1. Volume: size of data quantity of collected and stored data
2. Velocity: Speed of data the transfer rate of data between source and destination
3. Value: Importance of Data
4. Variety: Type of data and different type of data
5. Veracity: Data quality accurate analysis
6. Validity: Data accuracy used to extract result
7. Volatility: Duration of usefulness Big data volatility
8. Visualization: Data act and data process
9. Virality: The rate at the data is broadcast
10. Viscosity: Lag of event -
2020-09-28 at 12:36 am #22816Saravalee SuphakarnParticipant
My example of big data is “Public transport company as Mass Rapid Transit Authority of Thailand (MRTA)” which operate, develop and control metro system in Bangkok.
1.Volume : Many passenger use the transportation everyday, produced large volume of data and information. They have 3 main lines of metro system in Bangkok in responsibility of MRTA and more than fifty active services stations. Data that produced including technical data about the train, services data, and financial data etc.
2.Velocity : Most of services opened about eighteen hours per day and have customer all the time. A lot of data produce in every minutes. Some of the data and information are essential for make suddenly decision of worker such as the train driver.
3.Variety : many type of data produced in the metro system both structural and unstructural data. Video or picture from security camera are one of type of the produced data.
4.Veracity : As same as other transport service, safety of passenger is important policy of MRTA, Therefore they need data assurance that error-free and credible.
5.Variability :
6.Validity : as the same way if veracity, the system need accurate and correct data.
7.Vulnerability : Although the data of public transportation are less individual privacy concern than health information, but the important issue that must concern is terrorism issue. Public transport is one of the target of the terrorism, so the security of the data is important.
8.Volatility
9.Visualization : The real time data of the transport system should be represented in easily form for monitor and operate the system such as graphic map.
10.Value : The data and information from the system can be applied to optimize the metro system or services, develop the transportation system in Bangkok and main provinces. -
2020-09-29 at 2:26 pm #22847SaranathKeymaster
Seems that most of you give examples of big data from social media, business, and other sectors besides healthcare.
Do you think that data from your Hospital information system would be considered as big data?
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2020-09-29 at 5:26 pm #22854Saravalee SuphakarnParticipant
For my animal hospital, I think it hasn’t been accepted in criteria of big data yet. Because it’s medium size animal hospital that the average number of case per day about 30-50 case, I think that not much volume of data and velocity of input the data to the system isn’t fast enough to be as big data. I consider from 2 V of criteria (Volume and velocity) because I think it’s main characteristics of big data. Although the information system hasn’t been accepted as big data, it need data management too.
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2020-09-29 at 7:42 pm #22855NaphatParticipant
For my office, I think it’s a big data. Since we have been collecting information on our volunteers and patients for over 60 years, in my opinion, I think the character of Big data in my office is only 7vs , because there are few employees to handle and manage in the data. Compared with the large amount of incoming information each day.
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2020-10-02 at 11:36 pm #22934Khaing Zin Zin HtweParticipant
Sadly, I haven’t seen the use of big data in healthcare in my country as the data here is not in consistence with all Vs. However the volume of the data system used to collect HIV data across the whole country is big enough. It also is relatively fast to produce meaningful information (velocity), and gives some insights to the researchers on HIV data.
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2020-09-29 at 8:39 pm #22858Rawinan SomaParticipant
I think the MOPH’s HDC consider as a big data because it fits for 5Vs. The data generate from all health care provider such as hospitals, health promoting hospitals, it is a mass volume of data. The data generate every day and sending to data center each month as batch processing. It can be trustful and origination. It has own value and many purposes like monitoring, analyzing pattern of health status, supporting policy decision, and input for machine learning. Moreover, it lack of variety because it contain only structured data, no JSON, image, video is collected.
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2020-10-02 at 11:26 pm #22932Khaing Zin Zin HtweParticipant
I think Apple Health is big data because of its:
1. Volume: it collects health data from millions of users of iphone, iwatch and other third party apps
2. Velocity: daily progress or long-term trends can be viewed by users anytime
3. Variety: it contains data from sensors, text, images and biometrics, etc
4. Veracity: with advanced technology Apple uses, it can give result to data with relatively high accuracy
5. Value: Apple’s platform ResearchKit and CareKit enables doctors and developers to create apps for medical research and those for understanding and managing health conditions respectively.-
2020-10-04 at 12:03 pm #22987Sittidech SurasriParticipant
I do agree that the Apple Health is considered as a Big Data, and would be fit into 7Vs (Vulnerability, Validity).
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2020-10-04 at 11:52 am #22986Sittidech SurasriParticipant
After reviewing the provided read assignment and addition reading on BIG Data, it made me understand what big data is, how it works and what are the challenges? In my opinion, I would consider that 3Vs (Volume, Velocity and Variety) is basically used to determine which data could be called as a BIG DATA. However, there are 2, 4 and 7 Vs characteristics have been added; Value, Veracity (5Vs), Variability, Visualization (7Vs), Validity, Vulnerability, Volatility (10Vs).
There are many examples of data that could be considered as “Big Data”: Social Networks (Facebook, Tweeter), Web Server Log (Google), Traffic Flow Sensors, Satellite Imagery, Broadcast Audio Streams, Banking Transaction, Financial Market Data, Telemetry from Automobiles.
If we think about Big Data in Healthcare system, the example of data that I would consider as a Big Data is Hospital Data (e.g. Siriraj Hospital) which includes both services (Medical care and treatment, Lab, Pharmacy, Nursing, Nutrition and etc. and management (Administration, Financial, Management, Law etc.) areas. The following characteristics is used to consider as a Big Data:
1. Volume: refers to the quantity of data gathered by a company. Amount of information and data is used in the hospital, and number of customer/patient in each day.
2. Velocity: refers to the time in which Big Data can be processed. A large amount of information/data from users and departments is created, used and stored in a second or day.
3. Variety: refers to the type of data that Big Data can comprise. There are many types (structure and unstructure such as text, sensor data, audio, video, click streams, log files and so on.) of data created, used and stored.
4. Value: refers to the important feature of the data which is defined by the added-value that the collected data
can bring to the intended process, activity or predictive analysis/hypothesis. Data that created, used, and stared in the hospital is very important such as Medical history, Lab results, treatment record, payment etc.
5. Veracity: refers to the degree in which a leader trusts information in order to make a decision. Hospital have the policy, standard or SOP in creating, using and storing for each users to ensure that all information and data are accurate.
6. Variability: variability in big data’s context refers to a few different things. One is the number of inconsistencies in the data. There is a lot of information from users or machines, is generated, transformed, translated, and transferred which would have a variation in each process. These need to be found by anomaly and outlier detection methods in order for any meaningful analytics to occur.
7. Visualization: Many of big data visualization tools is used in the hospital to provide a better solution and service.
8. Validity: validity refers to how accurate and correct the data is for its intended use.
9. Vulnerability: Big data brings new security concerns. After all, a data breach with big data is a big breach as we have learned earlier.
10. Volatility: refer to the duration of usefulness. The hospital has policy to manage; generate and storage of the data.Moreover, I found that 14Vs, and 17Vs characteristics are available and used (The 17 V’s Of Big Data, https://irjet.net/archives/V4/i9/IRJET-V4I957.pdf)
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2020-10-04 at 1:30 pm #22988Kaung Khant TinParticipant
I think “Response to Covid-19” could be considered as “Application of Big Data”. Though I do not know for sure which organization is applying big data in the response of Covid-19, I believe there’s more than one health organization out there using big data analytics for a better and comprehensive response to Covid-19 disease. As the information of Covid-19 comes from different sources as both structure data and unstructured data. And it would be wise to apply the big data in responding to Covid-19 to better understand the nature of Covid-19 for better preventive and curative measures.
And in this particular case, the 5Vs of Big Data characteristics are
1.Volume – The data from COVID-19 comes from different sources such as medical records, medical reports, Facebook posts, and tweets, news and articles from different webpages, research articles from different journals and medical databases, and so on being created and accumulated continuously, resulting in an incredible volume of data.
2.Velocity – From a variety of sources, data is flowed in real-time and at a rapid pace as well as the time of processing and analyzing the big data for important and immediate response reflects the term velocity
3.Variety – As I’ve said above, the data of Covid-19 can be collected from a variety of sources as in structured data and unstructured data including text, photo, audio, videos. There lies a variety
4.Value – No need to say, the application of Big Data to respond Covid-19 definitely helps the medical personnel, public health practitioners, and government staff in decision making and management.
5.Veracity – In doing so, the data quality and accuracy is important so that it can be trusted and applied in the important decision-making process
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2020-10-04 at 2:36 pm #22990Phone Suu KhaingParticipant
Can you give an example of data that you think it could be considered as “Big Data”?
I think data in Mayo Clinic which is mentioned in lecture is Big Data.What are the characteristics of the data that fit into 5Vs, or 7Vs, or 10Vs of Big data characteristics?
1. Volume: Huge amount of patient data is stored
2. Variety: Include both structured and unstructured data. Data is in various forms which is text, image, audio and video
3. Velocity: There is massive continuous data flow.
4. Value: Data can be used for the purpose of better treatment outcome
5. Validity: Require accountable data from trustworthy source -
2020-10-04 at 2:40 pm #22991Phone Suu KhaingParticipant
I also agree that Weather data is Big Data that fit with 10 V.
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2020-10-04 at 9:21 pm #22996Navinee KruahongParticipant
I consider data in Pinterest as Bid Data which fits these Vs;
1. Volume: There are more than 30 billion Pins in the system.
2. Variety: The system include a large number of categories of people’s interest.
3. Velocity: they currently log 20 terabytes of new data each day.
4. Value: people use Pinterest for many proposes such as fashion, decoration, design, etc. It provides the most comprehensive collection of interests online.
5. Veracity: A personalized discovery engine can accurately extract context and intent for each Pin.
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