What is an example of big data in Accenture?
sending user survey responses from various store branches to a single, central database. providing real-time data feeds on millions of people with wearable devices. tracking the work hours of 100 employees with a real-time dashboard.
What are examples of big data? Big data comes from myriad sources -- some examples are transaction processing systems, customer databases, documents, emails, medical records, internet clickstream logs, mobile apps and social networks.
Big data defined
The definition of big data is data that contains greater variety, arriving in increasing volumes and with more velocity. This is also known as the three Vs. Put simply, big data is larger, more complex data sets, especially from new data sources.
Big data analytics helps businesses to get insights from today's huge data resources. People, organizations, and machines now produce massive amounts of data. Social media, cloud applications, and machine sensor data are just some examples.
1}entering and tracking a company's daily transaction records in a spreadsheet. 2)tracking the work hours of 100 employees with a real-time dashboard. 3)providing real-time data feeds on millions of people with wearable devices.
Answer - D) Big data is a collection of data that is used in volume, yet growing exponentially with time. 9. Identify among the options below which is general-purpose computing model and runtime system for Distributed Data Analytics.
Big data is classified in three ways: Structured Data. Unstructured Data. Semi-Structured Data.
Answer. Big data is a field that treats ways to analyze, systematically extract information from, or otherwise deal with data sets that are too large or complex to be dealt with by traditional data-processing application software.
- Structured data. Structured data has certain predefined organizational properties and is present in structured or tabular schema, making it easier to analyze and sort. ...
- Unstructured data. ...
- Semi-structured data. ...
- Volume. ...
- Variety. ...
- Velocity. ...
- Value. ...
- Veracity.
The correct answer is option A (Big data refers to data sets that are at least a petabyte in size). Big data is normally referred as the large volume of data like petabyte and exabyte in size (1 petabyte = 1,00,000 GB).
What is big data used for?
Big data is the set of technologies created to store, analyse and manage this bulk data, a macro-tool created to identify patterns in the chaos of this explosion in information in order to design smart solutions. Today it is used in areas as diverse as medicine, agriculture, gambling and environmental protection.
Data is defined as facts or figures, or information that's stored in or used by a computer. An example of data is information collected for a research paper. An example of data is an email.

A great example of real-time processing is data streaming, radar systems, customer service systems, and bank ATMs, where immediate processing is crucial to make the system work properly.
Expert-verified answer
Big Data analytics examples includes stock exchanges, social media sites, jet engines, etc.
tracking the work hours of 100 employees with a real-time dashboard. entering and tracking a company's daily transaction records in a spreadsheet. sending user survey responses from various store branches to a single central database. providing real-time data teeds on millions of people with wearable devices.
Data governance and management policies- Accenture help businesses implement to ensure their data is trustworthy and reliable.
Big data is a collection of data from many different sources and is often describe by five characteristics: volume, value, variety, velocity, and veracity.
What are the main components of Big Data? (A) MapReduce (B) HDFS (C) YARN (D) All of these Answer -D 3. What are the different features of Big Data Analytics? (A) Open-Source (B) Scalability (C) Data Recovery (D) All the above Answer -D 4.
Using those disciplines, big data analytics applications help businesses better understand customers, identify operational issues, detect fraudulent transactions and manage supply chains, among other uses.
- Structured data. Structured data has certain predefined organizational properties and is present in structured or tabular schema, making it easier to analyze and sort. ...
- Unstructured data. ...
- Semi-structured data. ...
- Volume. ...
- Variety. ...
- Velocity. ...
- Value. ...
- Veracity.
What is big data explain 5 V's of big data in detail?
Big data is a collection of data from many different sources and is often describe by five characteristics: volume, value, variety, velocity, and veracity.
What is the key objective of data analysis?to generate cultural support and alignment across an organization. to find meaning in data and use it to make informed decisions. to develop an enterprise-wide data strategy and data governance policies.
(a) It helps Data Analysts shape an analytics problem from a business problem. (b) It allows companies to make definitive predictions about the future. (c) It finds creative solutions to business problems without human intervention. (d) It gives companies the ability to make informed decisions.
Answer - D) Big data is a collection of data that is used in volume, yet growing exponentially with time. 9. Identify among the options below which is general-purpose computing model and runtime system for Distributed Data Analytics.
Big data is the set of technologies created to store, analyse and manage this bulk data, a macro-tool created to identify patterns in the chaos of this explosion in information in order to design smart solutions. Today it is used in areas as diverse as medicine, agriculture, gambling and environmental protection.
Big data is classified in three ways: Structured Data. Unstructured Data. Semi-Structured Data.
What are the main components of Big Data? (A) MapReduce (B) HDFS (C) YARN (D) All of these Answer -D 3. What are the different features of Big Data Analytics? (A) Open-Source (B) Scalability (C) Data Recovery (D) All the above Answer -D 4.
The term Big Data refers to a dataset which is too large or too complex for ordinary computing devices to process. As such, it is relative to the available computing power on the market. If you look at recent history of data, then in 1999 we had a total of 1.5 exabytes of data and 1 gigabyte was considered big data.
There are generally four characteristics that must be part of a dataset to qualify it as big data—volume, velocity, variety and veracity. Value is a fifth characteristic that is also important for big data to be useful to an organization.
The main purpose of data analysis is to find meaning in data so that the derived knowledge can be used to make informed decisions.
What is data analyst in Accenture?
Data Analysts are responsible for various customer issues depending on account assignment; tasks may be related to transaction processing, issue resolution, ensuring that department and customer needs are met, and assisting with special projects, as needed.
Highest reported salary offered as Data Analyst is ₹50lakhs. The top 10% of employees earn more than ₹25lakhs per year. The top 1% earn more than a whopping ₹42lakhs per year.