- This topic has 20 replies, 17 voices, and was last updated 2 years, 9 months ago by Pimthong Sinchai.
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2021-09-18 at 12:38 am #31372SaranathKeymaster
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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2021-09-22 at 9:12 pm #31529Auswin RojanasumapongParticipant
An example of data that I think could be considered as Big Data is an activity in social media.
Activities in social media could be Big Data due to 10Vs as follow:
Volume -> The amount of data generated in social media per time unit is very high, and it’s getting higher when time passes.
Velocity -> Due to the very large number of users, the data was created with very high velocity
Variety -> Data generated from social media comes in various formats, such as text, images, VDO clips, sound clips, geolocation, click data, etc.
Variability -> There is inconsistency in the data from the social media (from various users and data types) that needs to be found by outlier detection methods in order to do analysis.
Veracity – > The data generated in the social media system reflects what the users of the social media think/act and should be the one V that might reflect the usefulness of this data.
Validity -> Using data from social media to analyze for any purpose should be carefully considered, and data cleansing is necessary before analysis.
Vulnerability -> Much social media data is personal data, so it is vulnerable to a data breach if the data is kept insecure.
Volatility -> Current trends and situations change very fast, and so as social media-generated data. The data generated from 2 – 3 years ago might be irrelevant and out of trend to use to predict the future.
Visualization -> Data from social media can be visualized to show the trend, predict the probability of the social event, and plan for many activities, such as commercials.
Value -> If the data from social media is cleaned, it is very useful for many purposes, such as predicting the activities, though and needs of the people.
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2021-09-26 at 2:21 pm #31665Arwin Jerome Manalo OndaParticipant
Good example on using social media! Nowadays, fake information have spread on social media and they affect mainly the veracity of information. Misinformation can skew analytics to a wrong direction.
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2021-09-24 at 6:35 pm #31615Karina Dian LestariParticipant
One example of big data in health is data collected from wearable devices or smartwatches. They have the 7V of big data characteristics, such as:
– Volume: as the technology becomes more advance and available, the wearable devices are now used by many people thus it increases the volume of the data
– Velocity: smartwatches measure the pulse rate, oximeter, walking/running distance in real-time
– Variety: the data that is collected by smartwatches are varied. It collects sensor data, and some smartwatches can also measure geolocation data to record the walking path of the wearer.
– Veracity: since smartwatch is a personal belonging, the data that are collected are believed to be personalized to just one person. However, the smartwatch is not able to differentiate if it wears by different people.
– Variability: the data could be varying a lot because the sensor for detecting pulse rate may not work as intended, or if it is collecting geolocation the GPS may not detecting the location correctly
– Value: data that are collected are valuable to see the health of the person. It can also be an early detection if the pulse rate of the wearer is suddenly increasing than usual
– Vulnerability: the data from smartwatches is also vulnerable because it collected very personal data and it is also prone to data breach if the security of the smartwatches is not strong enough -
2021-09-25 at 8:06 am #31629TARO KITAParticipant
One of the examples of Big Data in healthcare could be data produced in hospital activities such as EMRs, doctors’/ nurses’ notes.
Volume/ Velocity/ Variety/ Variability: A number of patients’ records, in the form of the structured or semi-/ unstructured, and various data types such as hand-written notes/ images, are produced, collected, and stored on a daily basis through medical activities.
Value/ Visualization: They could be used for disease research, disease prediction, new drug discovery in the forms of charts, graphs, maps, and other visual forms.
Veracity/ Vulnerability: The Big Data from hospital activities can be used to support doctors to make decisions as they are the record of actual medical activities with each patient’s identity. However, they are also susceptible and vulnerable to data breach because of its patients’ information.
Validity/ Volatility: They have to undergo careful analysis to determine whether to include or exclude from the study in view of validity and relevance.
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2021-09-26 at 2:18 pm #31664Arwin Jerome Manalo OndaParticipant
An example would be health data collected from fitness tracker/ smartwatch, let’s say the Apple Watch, implemented on a pilot program by a health agency.
Volume – Implemented at the population level, the amount of health data taken over time will get larger over time.
Veracity – Quality of data depends on the reliability of technology to collect, analyze, and translate the input stimuli to meaningful information. Likewise, it depends on the users, let’s say that if they forget to wear the watch for a day, then there is no datum to assess. This can lead to impairment on the ability to make truly informed and evidence-based decisions.
Value – Once the health data are collected, these can be used to study trends among the study population. Let’s say that these are patients at risk of cardio-pulmonary events. Heart rate monitoring and O2 sat are important predictors of impending health event.
Velocity – Each minute that passes by, the physiological processes of the human body changes. This creates new sets of data (eg, increased heart rate, decrease 02 saturation) needed for synchronization to servers
Variety – Health data collected may include a variety of information, which include oxygen levels, heart rates, ECG, number of steps, type of physical activity taken among others-
2021-10-03 at 3:44 pm #31831Napisa Freya SawamiphakParticipant
I like the idea of implementing data from smartwatch on a pilot program by a health agency. Apple watch is commonly used now. It would be useful to integrate these data in formal health databased for medical assessment. However, the data assurance is important and need too be considered as well.
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2021-09-28 at 1:49 am #31686Tossapol PrapassaroParticipant
An example of big data is e-commerce company, for example, Amazon, etc.
Volume: According to many online shoppers nowadays, they search for a variety of products. Therefore, the company had vast amounts of data about their customer to use this invaluable information to make profits.
Velocity: The e-commerce company has to suggest and match the product to the user on time; therefore, they have to analyze the data promptly to streamline the process of leading the customer to buy their products.
Variety: The type of data that they collected to get to know their customer can come from many sources; for example, amazon may collect the text data that you put into their website or your voice data from Alexa echo(the ecosystem of amazon) or maybe the book or the picture that you read form kindle ebook of amazon. So, they can collect various types of data to know you.
Veracity: To determine the truth of this data, they may have to use various tools to analyze, such as the machine learning algorithm, mathematics, statistic, etc.
Value: The data that the company collected can help them understand the shopper’s habits and match with their product, so it could help to make benefits and profits to the company.
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2021-09-28 at 4:28 pm #31692Pisit SaiwangjitParticipant
If you ask me, I convince that the Electronic Health Record (EMR) is considered as Big Data because its characteristics are in line with the 5Vs of Big Data;
• Volume: the EMR tends to have a huge quantity of data. All of the patients information that visit the hospital is accumulated in the EMR database every single day.
• Velocity: EMR is needed to process fast in some time-sensitive scenario, for example, the detection of the prescription of drugs which patients are allergic to or possible cross drug allergy.
• Variety: The EMR comprises a wide variety of data types, such as, health conditions, ultrasound files, X-ray films, laboratory tests, patients’ health insurance, etc.
• Value: The data which is stored in the EMR database can be used in many useful ways including to evaluate the treatment, predict the treatment outcomes, determine the disease pattern, etc.
• Veracity: The collected data in EMR is somehow trustworthy because the data is obtained by the devices such as, blood pressure monitor, EKG monitor, etc. -
2021-09-28 at 5:23 pm #31693Napisa Freya SawamiphakParticipant
An example of big data is Personalized medicine for oncology diagnosis, prognosis, and treatment (Genomic analytics)
– Volume: Genomic data and gene sequencing can be collected from individuals in the database and accumulated over time.
– Veracity: High volume of genomic data collected from huge population, can show the possible correlation between the specific gene and diseases or targeted treatment.
– Variety: Genomic data is normally a structured data with specific gene code and sequence. However, it is complex and consists with multiple patterns of sequencing.
– Velocity: Using the genomic bank, the data should be analyzing and matching gene sequences fast. So, the healthcare professionals can use the results to make a decision on the personalized treatment as early as possible, to prevent disease progression.
– Value: If we can find the casual relationship between the unique genomic data and the occurrence of diseases, poor prognosis, or specific treatments that patients are likely to response to, it will be useful for early diagnosis and medical care decision. It also can be applied to patients with similar gene characteristics. -
2021-09-28 at 8:14 pm #31696Navin PrasaiParticipant
Volume: refers to the quantity of data generated from different sources like social media, images, videos.
Velocity: refers to the time how fast Big Data can be processed.
Variety: refers to the different types of data including structured and unstructured data like text, sensor data, audio, video. Mostly unstructured data are stored in big data.
Value: refers to the reliable data stored which gives valuable information. For instance, people shared a lot of valuable information using social media.
Veracity: refers to the reliability of the information to make a decision. -
2021-09-28 at 9:02 pm #31697chanapongParticipant
An example of big data is the navigation or mapping application like Google Maps.
Volume: As crowded traffic occurs in all cities, especially in urban areas, the data that can be collected is enormous.
Velocity: Real-time process of data is required to operate the application when navigating to the destination.
Variety: Different types of data are collected. Vehicle’s location obtained by GPS, traffic cameras, satellite, and mobile phone location is the example of obtained data to be further analyzed.
Veracity: Considering the data trustworthiness of these applications is depend on how fast and volume of the data be updated and processed. There is an incident when using the mapping application navigating the user to the roadworks or incorrect destination.
Value: The collected data can suggest the shortest route and time to users when using the application. It can help reducing fuel usage and carbon production.
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2021-09-30 at 3:06 am #31731Anawat ratchatornParticipant
Thank you for sharing.
Mapping application is a very good example that I use everyday without considering it is an example of big data.
I agree about all mentioned, additionally, some application can generate 3D virtual image that might be more complicated to utilize and collect. -
2021-10-02 at 10:16 pm #31826Auswin RojanasumapongParticipant
I agree with you about navigation data from map applications. The data can be generated in the background without the user knowing that the data has been created. The data from the crowd that is in motion can generate a large number of data all the time.
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2021-09-30 at 3:45 am #31732Anawat ratchatornParticipant
Example of big data that we involves everyday is data from wearable devices.
– Volume: Today, wearable devices are more affordable and collect more data than in the past. Million of people wearing the devices everyday, so sensors in the devices collect a lot of data from all around the world into providers server.
– Velocity: Some wearable devices always connect to network and transfer collected data to the network in real-time, But some are collected data on its own storage and then transfer data to the network periodically. In the aspect of receiving analyzed data from the network, most issue is not an emergency issue, so it might not necessary to transfer data in real-time
Variety: Wearable devices contain many type of sensors and collect many variety of data such as health data, behavior data and also environment data. other than variety type of data, these data are collected in different way.
Veracity: Data are collected by sensors contained in devices. Trustworthiness of data depend on quality of those sensors and the way that user wear it.
Value: The collected data can utilized in many ways. According to variety of data, These data can be benefit in health, marketing, and many other ways.
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2021-09-30 at 10:54 am #31746Sri Budi FajariyanParticipant
Malaria program data in Indonesia can become big data, based on the characteristics of big data, including:
1. Volume : Indonesia is a big country. there are more than 10,000 health facilities both public and private. currently around 9,000 health facilities report data on malaria programs. With the number of users and the number of malaria cases, the data on the malaria program will get bigger every year.2. Variety: Malaria program data reported in Indonesia is not only data on individual cases, but also reports on logistical data, human resources, individual data of microscopic competence, data on the implementation of malaria diagnostic quality management, vector surveillance and control data, focus investigation data, point coordinates, etc.
3. Velocity: the flow rate of malaria data is influenced by the amount of data recorded in the program and the number of users who report data
4. Veracity: the accuracy of malaria program data because it is inputted by people who have knowledge of malaria
5. visualization: malaria program data can be visualized to facilitate data analysis
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2021-09-30 at 12:46 pm #31749Ashaya.iParticipant
The example of Big Data in healthcare that obviously seen such as Electronic Medical Records (EMR), the characteristics that fit into 5Vs are included;
Volume: There are very large amount of patient data contains in EMR
Velocity: Data processing in EMR should be real-time or at least, nearly real-time to serve the effective and safety medical services.
Variety: EMR involved many types of data such as patient information, laboratory and special examination result, prescription detail, etc.
Value: Data in EMR can be retrieved to use for further statistical process, study and analysis.
Veracity: the patient’s data should be trustworthy. Patient’s data in EMR are from history taking, physical examination, laboratory test so can be a certain amount of trust. -
2021-10-01 at 5:54 am #31763SaranathKeymaster
Interesting examples of big data. Thanks everyone!
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2021-10-04 at 12:30 am #31838Theekhathat HuapaiParticipant
NCD patient data has been changed from static data to big data from these characteristics :
Volume: Thailand is a developing country with public health coverage. Every trimester, NCD patients will have a routine check-up at primary care unit around the country. A large number of new health data will be generated and send to a database.
Velocity: NCD patient’s data is not dynamic if we see it as an individual patient. On a population scale, it can become a rapid change.
Variety: NCD patient’s data is composed of multiple categories. Such as physical, laboratory examination.
Veracity: Electronic data records have a standardized method to ensure the integrity of data. But the pitfall is how we are gathering health data. (Technique in blood pressure measuring)
Value: A new health benefit from NHSO will be included with an examination in high-risk populations. Big data in NCD patients can be used to create predicting models of NCD.
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2021-10-07 at 10:45 pm #31960Weerada TrongtranonthParticipant
Online Shopping is one of big data, Based on these characteristic :
Volume : Nowadays, It’s the age of E-commerce. Customers prefer shop in online platform. That’s why number of users (customers and Traders) and Products increase so fast. Includes transactions that have very large amount each day
velocity : information of products, users, customers dramatically increase on the internet platform
Variety : There are multiple trmendous catagories that customers can easily choose and compare quality and price
Value : Data from transaction and users would be lots of benefit in economical scales
Veracity : The transactions are real and come from the real trading whiach are trustworthy -
2021-10-10 at 9:43 pm #32047Pimthong SinchaiParticipant
Google is the one example of Big Data, I think everyone get used to it. There are 7Vs involved with which are:
– Volume -> Large amount of data, Google was processing over 20 petabytes of data per day! a lots odd data
– Velocity -> Data velocity in almost real time derives from the ubiquity and availability of devices connected to the internet, both wireless and wired.
– Variety -> Data diversity going from stored and structured data kept in business databases to unstructured data, semi-structured data and data in different formats, i.e., over 3.5 million people make calls, send SMS, tweet, search and browse the internet from their cell phones.
– Veracity -> The aim is to promote the search for data veracity so that we may retrieve reliable information. Accurate data allow for greater utilization because of their quality.
– Value -> The key to Big Data is not the countless amounts of information but rather how it is used and handled.
– Variability -> The algorithms must be able to understand the context and decode the exact meaning of every word in its specific environment.
– Visualization -> making the analyzed data to more understand and easy to read.
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