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Which of the following are benefits for organization generated data? Improved Safety Better Profit Margins Higher Sales
- Improved Safety.
- Better Profit Margins.
- Higher Sales.
- High Velocity.
- Customer Satisfaction.
What are the benefits of big data in the workplace?
As a summary, organizations are gaining significant benefit from integrating big data practices into their culture and breaking their silos. Some major benefits to organizations are operational efficiency, improved marketing outcomes, higher profits, and improved customer satisfaction.
What are the three major data sources used in big data?
Size of the data. Using the three major data sources: Machines, People, and Organizations. 13. What does it mean for a device to be "smart"? Connect with other devices and have knowledge of the environment.
Why don't more companies use large data storage?
Companies can't afford to own, maintain, and spend the energy to support large data storage unless the cost is sufficiently low. Larger storage means easier accessibility to big data for every user because it allows users to download in bulk.
What is the best description of personalized marketing enabled by big data?
Access of larger storage becomes easier for everyone, which means client-facing services require very large data storage. 3. What is the best description of personalized marketing enabled by big data? Marketing to each customer on an individual level and suiting to their needs.
Which of the following are reasons mentioned for why data generated by people are hard to process Choose all that apply?
Which of the following are reasons mentioned for why data generated by people are hard to process? Very unstructured data. They cannot be modeled and stored. The velocity of the data is very high.
What is a benefit of using pre built Hadoop images?
What is a benefit of using pre-built Hadoop images? Guaranteed hardware support. Less software choices to choose from. Quick prototyping, deploying, and validating of projects. Quick prototyping, deploying, and guaranteed bug free.
Which of the following are parts of the 5 P's of data?
1. Which of the following are parts of the 5 P's of data science and what is the additional P introduced in the slides?People.Purpose.Product.Perception.Process.Programmability.Platforms.
What is the benefit of a commodity cluster?
Commodity clusters exploit the economy of scale of their mass-produced subsystems and components to deliver the best performance relative to cost in high performance computing for many user workloads.
Which of the following are benefits of big data processing?
Benefits and Advantages of Big Data & Analytics in BusinessCost optimization.Improve efficiency.Foster competitive pricing.Boost sales and retain customer loyalty.Innovate.Focus on the local environment.Control and monitor online reputation.
Which of the following are the goals of HDFS?
The goals of HDFS are handling the hardware failure and recovery, handling datasets effectively, and provide high network bandwidth for data movement.
What are the 5 V's of big data?
The 5 V's of big data (velocity, volume, value, variety and veracity) are the five main and innate characteristics of big data. Knowing the 5 V's allows data scientists to derive more value from their data while also allowing the scientists' organization to become more customer-centric.
Which of the following are the 6 V's in big data?
Big data is best described with the six Vs: volume, variety, velocity, value, veracity and variability.Volume. Volume is an obvious feature of big data and is mainly about the relationship between size and processing capacity. ... Variety. ... Velocity. ... Value. ... Veracity. ... Variability.
What are some advantages of doing data analytics in the cloud?
Here are four benefits of adopting the cloud for your data analytics.#1 Increased scalability. Think about your on-site IT infrastructure. ... #2 Faster insights. ... #3 Easier maintenance and disaster recovery. ... #4 Stronger decision making. ... Understand your data and your business needs.
What is the specific benefit of a distributed file system?
It allows the data to be share remotely. It improved the availability of file, access time, and network efficiency. Improved the capacity to change the size of the data and also improves the ability to exchange the data. Distributed File System provides transparency of data even if server or disk fails.
What is commodity hardware in big data?
Commodity hardware, in an IT context, is a device or device component that is relatively inexpensive, widely available and more or less interchangeable with other hardware of its type.
What are commodity systems?
A commodity marketing system encompasses all the participants in the production, processing and marketing of an undifferentiated or unbranded farm product (such as cereals), including farm input suppliers, farmers, storage operators, processors, wholesalers and retailers involved in the flow of the commodity from ...
Why is mobile advertising related to big data?
Since almost everyone owns a cell/mobile phone, the mobile advertising market is large and thus requires big data to contain all the information.
Why is large storage important?
Larger storage means easier accessibility to big data for every user because it allows users to download in bulk. It isn't, it was just an arbitrary example on big data usage. Access of larger storage becomes easier for everyone, which means client-facing services require very large data storage. 3.
Week 1 Quiz Answer
Q1) Which of the following is an example of big data utilized in action today?
Why Big Data and Where Did it Come From
Q1) Which of the following is an example of big data utilized in action today?
Which organization from the retail shopping domain heavily utilizes big data?
Let's travel from package delivery to the retail domain. An organization from the retail shopping domain that heavily utilizes big data is Walmart. Walmart is a big organization that gets 250 million customers in 10,000 stores.
What is the Big Data course?
Interested in increasing your knowledge of the Big Data landscape? This course is for those new to data science and interested in understanding why the Big Data Era has come to be. It is for those who want to become conversant with the terminology and the core concepts behind big data problems, applications, and systems. It is for those who want to start thinking about how Big Data might be useful in their business or career. It provides an introduction to one of the most common frameworks, Hadoop, that has made big data analysis easier and more accessible -- increasing the potential for data to transform our world! At the end of this course, you will be able to: * Describe the Big Data landscape including examples of real world big data problems including the three key sources of Big Data: people, organizations, and sensors. * Explain the V’s of Big Data (volume, velocity, variety, veracity, valence, and value) and why each impacts data collection, monitoring, storage, analysis and reporting. * Get value out of Big Data by using a 5-step process to structure your analysis. * Identify what are and what are not big data problems and be able to recast big data problems as data science questions. * Provide an explanation of the architectural components and programming models used for scalable big data analysis. * Summarize the features and value of core Hadoop stack components including the YARN resource and job management system, the HDFS file system and the MapReduce programming model. * Install and run a program using Hadoop! This course is for those new to data science. No prior programming experience is needed, although the ability to install applications and utilize a virtual machine is necessary to complete the hands-on assignments. Hardware Requirements: (A) Quad Core Processor (VT-x or AMD-V support recommended), 64-bit; (B) 8 GB RAM; (C) 20 GB disk free. How to find your hardware information: (Windows): Open System by clicking the Start button, right-clicking Computer, and then clicking Properties; (Mac): Open Overview by clicking on the Apple menu and clicking “About This Mac.” Most computers with 8 GB RAM purchased in the last 3 years will meet the minimum requirements.You will need a high speed internet connection because you will be downloading files up to 4 Gb in size. Software Requirements: This course relies on several open-source software tools, including Apache Hadoop. All required software can be downloaded and installed free of charge. Software requirements include: Windows 7+, Mac OS X 10.10+, Ubuntu 14.04+ or CentOS 6+ VirtualBox 5+.
Is Walmart a big data company?
Overall, by leveraging big data and analytics, Walmart has maintained its position as a top retailer. UPS and Walmart examples were just two out of a number of companies using big data. Big data is producing results for companies in all sectors.
