Instructions
- Create substantive, professional, and scholarly postings in well-developed five or more sentences.
- Cite your sources if used.
- Correct grammar, spelling, and punctuation usage should be utilized in order to gain maximum points.
- Reply to the topic below by midnight Wednesday in the module it is due. Then, reply to 2 classmates by midnight Sunday. This discussion is worth 25 points. Please refer to the discussion board rubric located under the three vertical dots (hamburger sign) in the upper right-hand corner or under Course Resources.
- You will see your classmates’ responses only after you have submitted your initial reply.
- Click "Reply" below to begin your original post.
Discussion Topic
We probably all agree we live in a highly technical world, and it’s growing. In fact, big data has become a part of everyday life. Ever thought of how each click of the mouse or your words on social media are tracked? Companies gather data about everything you do on your phone, computer, TV, Alexa, Amazon Echo, Google Home Mini, etc. In fact, the number of bytes used and required to gather information have grown astronomically over the past 20 years. All this data gathering creates problems for statistics.
As you read Chapter 7, pay particular attention to the information about Big Data on pages 356 through 358, watch the TED Ed and TED videos below, then address the questions.
TED Ed – There is a mind-boggling amount of data floating around our society. Physicists at CERN have been pondering how to store and share their ever more massive data for decades – stimulating globalization of the internet along the way, whilst ‘solving’ their big data problem. Tim Smith plots CERN’s involvement with big data from fifty years ago to today.
TED – Big Data is Better Data
Self-driving cars were just the start. What’s the future of big data-driven technology and design? In a thrilling science talk, Kenneth Cukier looks at what’s next for machine learning — and human knowledge.
Big Data is Better Data (Links to an external site.), by Kenneth Cukier
TED Ed – Statistics are persuasive. So much so that people, organizations, and whole countries base some of their most important decisions on organized data. But any set of statistics might have something lurking inside it that can turn the results completely upside down.
After watching the videos and reading the text, address the following:
- Define big data and data mining.
- What purpose does collecting huge amounts of data serve?
- Consider Twitter. Do you believe big data is accurate and reliable? Why or why not?
- What type(s) of sampling methods could be used with big data?
- What sampling errors could occur and how could they be avoided?
- Has collecting big data been helpful for businesses? Why or why not?
- What do you see happening in the future with big data?