Question

Compose and submit to the Weeks 1 and 2 Discussion Forum - "Summary and Analysis: Academic" thread a structured post (a structured post has an overall introduction, an overall conclusion, and a developed body that flows well - generally at least a few paragraphs - at least 250 words, not including the question text itself), using your own words. Please include, as well:

1. An APA/ MLA/Chicago/etc. reference for the item - basically, let your professor and your classmates know how to find it if we want to read/watch it.
2. TL;DR
3. Why you chose this item.
4. A brief summary of the main points that the author made in the item.
5. An analysis of the item. Points to address (all 7 of them):
   1. Did the author have a clear purpose for the item? What makes you believe so?
   2. Was this purpose accomplished? How?
   3. Did the author present compelling evidence to support main points?
   4. Does the item have gaps? What sort?
   5. Did the author present the information in a way that readers would find appealing? In what way?
   6. Is the world a better place for this item being written/given? How?
   7. How does this item relate to the real world, either business-wise, or personally? If it doesn't, state why?

Assignment:

Summarize the following articles below using above information

Big Data: Concepts, Technologies, and Applications" by Hugh Watson

Major Myths About Big Data's Impact on Analytics

Answer 1

Summary :

We are living in the era where data has more importance then earlier time . In the past we have less devices which generating data online or offline but now everything is connected with internet and this is a reason of huge data generation while another reasons are people are now more educated to use devices and internet .

Whether its social media giants Facebook or Google or any bank : everyone today needed the generated data from the users or system to analyse it and come to a point to make future decision making or strategy planning.

Big Data : Now companies have so huge amount of data to store , process , analysis and because of it's size it's called as Big Data. For example only eBay (an e-commerce site ) capture 1 terabytes data per minute and it have data in petabytes which ultimately need to be warehousing.

Data Warehousing is this method to extract , transform and load the data.

This data have multiple sources and multiple variety. Some sources are RFID , relational databases , GPS etc.

Data Analysis : Data Analysis is analysing the data from multiple resources and transforming it into a simple format so the business decision makers can see the trends of data and on the basis of that they can manage their future works or forecasting.

Data Analysis is divided into two types -

Descriptive Analysis and Predictive Analysis

Descriptive Analysis means analysing the past data and generate reports on that or creat dashboard using any Business Intelligence Tool to understand the trends and take the help from it to the current work .

Predictive Analysis means prediction of the future trends on the basis of past and current scenarios.

Conclusion: Hence we can say that this big data alone can not create any effect on the business but when this data been analysed and the stated to the decision makers in a simple way then it can create a great impact on the business.