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Posted: April 14th, 2022
BI, Analytics, Decision Support- DQ6
Today’s challenge is what to do with all of the data that has been created as a result of the Internet. The field of data science is trying to store, manage, classify and provide meaningful access to it. Think like a futurist. Create a report on where the field is going. Some points you might want to include are:
What is Big Data?
Why is it important?
Where does Big Data come from?
What do you believe the future of Big Data will be?
Will it lose its popularity to something else?
If so, what will it be?
What is Big Data analytics? How does it differ from regular analytics?
What are the critical success factors for Big Data analytics?
What are the big challenges that one should be mindful of when considering implementation of Big Data analytics?
What are the common business problems addressed by Big Data analytics?
In the era of Big Data, are we about to witness the end of data warehousing? Why?
What are the use cases for Big Data/Hadoop and data warehousing/RDBMS?
What is stream analytics?
How does it differ from regular analytics?
What are the major uses of IoT?
Why is the IoT considered a disruptive technology?
The IoT has a growing impact on business and e-commerce. Find evidence.
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Today’s challenge is figuring out what to do with all of the data generated by the Internet. Data science is attempting to store, manage, classify, and provide meaningful access to it. Consider yourself a futurist. Make a report on where the field is headed. You might want to include the following points:
What exactly is Big Data?
What is the significance of this?
Where does Big Data originate?
What do you think the future of Big Data will be like?
Will it succumb to something else’s popularity?
What, if anything, will it be?
What exactly is Big Data analytics? What distinguishes it from traditional analytics?
What are the most important success factors in Big Data analytics?
What are the major obstacles?
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