Big Data

Ch. 3 Discussion Questions

1. Is Big Data really a problem on its own, or are the use, control, and security of the data the true problem?

2.  What are the implications of having incorrect date points in your Big  Data? What are the implications of incorrect or duplicated customer  data? How valuable are decisions that are based on faulty information  derived from incorrect data?

3. Explain the difficulties involved in managing data.

4. What are the problems associated with poor-quality data?

5. What is master data management? What does it have to do with high-quality data?

6. Explain why master data management is so important in companies that have multiple data sources.

7. Describe the advantages and disadvantages of relational databases.

8. Explain why it is important to capture and manage knowledge.

9. Compare and contrast tacit knowledge and explicit knowledge.

APACitation

No plagiarism

Bookto be used :

Management Information Systems, Rainer, Prince, Watson, 3rd Edition

Is Big Data really a problem on its own, or are the use, control, and security of the data the true problem?

Introduction

Big data is a term that’s been around for a long time, but it’s only recently become a buzzword. The concept of big data was born with the digital revolution. But now, large amounts of data are coming out at an unprecedented rate. What can be done with all this data? How do we make sense of all these bits and bytes? And how do we protect this data from abuse? Can we really use technology to solve our society’s problems?

Big data is a term that’s been around for a long time, but it’s only recently become a buzzword.

Big data is a term that’s been around for a long time, but it’s only recently become a buzzword. In fact, if you Google “big data” and “data,” you’ll find articles from as far back as 2012 that talk about the importance of big data analytics for businesses.

But what does “big” mean? And why should you care about this new trend? Let us explain:

• The first thing to understand when talking about big data is what constitutes small or medium-sized datasets–and how they relate to each other.*

Specifically: If we were looking at two types of datasets–small and medium-sized–then we would need different terms than simply saying “big” when referring to them.*

The concept of big data was born with the digital revolution.

The concept of big data was born with the digital revolution. As computer technology advanced, so did our ability to process and analyze information quickly. This led to a new kind of data: “big” or extremely large sets that could be processed on high-performance computers. To understand this term better, let’s look at when it first came up:

• In 1965, Melvin Minsky published his paper “Strong AI.” In it, he highlighted three major obstacles for artificial intelligence (AI): lack of memory; limited computational power; and low communication speed between human beings and machines*. He called these issues “the Three Laws of Robotics,” which later became known as Minsky’s Laws.*
• In 1969, John McCarthy coined the term “information processing systems” (IPS) as part of his doctoral thesis on formal languages.* IPSs are systems built around one or more processors capable of performing logic operations–or processing data in terms of something other than physical reality–on input streams consisting mainly but not exclusively text data.*

But now, large amounts of data are coming out at an unprecedented rate.

But now, large amounts of data are coming out at an unprecedented rate. The amount of data produced every two years is doubling every two years. In 2017 alone, it was more than all the data produced in the previous 100 years combined!

So what’s going on here?

What can be done with all this data?

• Predictive analytics:
• Machine learning:
• Fraud detection:
• Customer service: Just as you can use data to predict which products will sell, you can also use it to predict which customers are likely to buy more of your products in the future, or what products they’re most likely to buy from you. This information can help you better target advertising campaigns and make sure that each customer gets exactly what they want when they walk into your store or website. You could also use predictive analytics for marketing purposes–for instance, if this data suggests that a certain type of product will be popular among young people who live in Brooklyn but don’t own cars yet (so-called “Millennial” consumers), then maybe there’s an opportunity for new types of services like UberPool where people share rides with each other instead of having their own cars all day long! In addition, some companies have begun using machine learning algorithms based on big data sets collected over years by scientists at MIT Media Lab and Harvard University who’ve analyzed thousands upon thousands hours’ worth of data collected during experiments involving insects walking across floors made up entirely out their own bodies’ fluids…

How do we make sense of all these bits and bytes?

Big Data is used to describe the large amounts of data that are generated by digital technologies. The term can refer either to the amount of information that is collected or its usage in analytics, but it’s often used interchangeably with “data-driven” because they both involve using algorithms and computer systems to process data.

Big Data has become a buzzword in recent years, as we’re seeing more and more companies using big data analysis on a daily basis. However, there are many different types of big data projects out there; some focus on just one type while others combine several types into one project or solution.

And how do we protect this data from abuse?

It’s important to note that, while Big Data is a real problem, it’s not an isolated one. In fact, the use of data can be used in many ways and by many different groups:

• Individuals (i.e., customers) – Use your personal information to sell products or services to you. This is called “data brokerage” and happens all over the place online–it’s why we’ve seen so many companies try out new ways of collecting our personal information without our permission!
• Corporations – Companies collect our data for their own use when they track where we go online using cookies or similar methods; this helps them understand how people use things like web browsers and apps on our devices so they can better serve us with relevant content later down the road!
• Governments around the world – Governments want access too–they need more information about citizens so they can make decisions about policies related solely on what each individual needs as opposed to his/her entire population group which might mean ignoring some people who need help most when considering policies such as healthcare reform plans based upon “public opinion polls”.

Can we really use technology to solve our society’s problems?

Yes, we can use technology to solve our society’s problems. In fact, it’s already happening. But we need to be careful about how we use it and what the risks are of doing so.

In order for our digital world to continue evolving and becoming more integrated into our lives, there needs to be a balance between privacy protection and access by all members of society–not just those with money or power over others (or both). A balance between control and freedom is necessary if we want everyone in society who uses technology every day: children; seniors; disabled individuals; scientists researching new drugs against cancer; artists creating art works that inspire millions around the globe through social media platforms like Facebook or Instagram–to name just a few examples–to be able describe why this type of technological advancement matters so much today?

With all these questions in mind, let’s take a look at what we’re dealing with when it comes to big data today.

In the past, we’ve been able to assume that the data we create and use is kept safe. We have only recently started to realize that this isn’t necessarily true, and that our data can be used in ways that we don’t expect or understand. The issue with this is not just about security–it’s also about control: if we don’t know what information is being collected on us (and who has access), then how are we supposed to keep anything private?

When it comes down to it, big data has become such an important part of our daily lives that it’s time for us all as individuals and businesses alike take steps toward better understanding how these technologies have been used up until now.

Conclusion

So, what are we to make of all this? Is big data a problem on its own, or are the use, control, and security of the data the true problem? What can be done with all this information? How do we make sense of these bits and bytes? And how do we protect this information from abuse? As much as I would like to say there is a simple answer for each one of these questions (and there usually is), it’s important to remember that just because something is technologically possible doesn’t mean it will always be beneficial or ethical. So while we may have big data at our disposal now—and that’s great!—there’s no reason why some people shouldn’t still control who gets access to their personal information

# Conclusions