Topic outline
-
What is "big data?" Big data is usually defined as a substantial amount of unstructured and structured data that is so large it is difficult to process using traditional methods. The amount of data is either too big, received too quickly, or exceeds available processing capacity. This requires organizations to have advanced systems to manage big data. Big data processing consists of a set of techniques and computing models that access large scales of data. This process extracts useful information that supports or provides evidence for decision-making. However, this can require a lot of space, and purchasing hardware can become costly. Cloud computing allows for the delivery of different services through the internet. For example, resources can include tools and applications like data storage, databases, and software. Cloud computing systems stores and grant access to data over the internet instead of on a local server or hard drive. This unit will cover big data and cloud computing.
Completing this unit should take you approximately 7 hours.
-
There are many definitions of big data. For this lesson, think of big data as consisting of extremely large data sets. They are large primarily because of volume, velocity, and variability. Volume does not relate to storage. However, it addresses how to discover relevant insights from enormous amounts of data.
Because of technology, organizations can collect and store data faster than ever before. Velocity refers to this accelerated pace and challenges organizations to find ways to collect, process, and make use of vast amounts of collected data. Variability refers to data that comes in unstructured and structured forms. Therefore, organizations require scalable architecture to store, manipulate and analyze big data.
-
Read this article and focus on the definition, types of data considered big data, and how to analyze it. Then take notes on the tools currently used to analyze big data.
Technology continues to advance an organization's ability to collect data. Next, you will learn about storing and making big data accessible by developing the infrastructure.
-
Big data storage is an infrastructure designed to store, manage, and retrieve massive amounts of data. This allows the storage and sorting of big data. It also makes the data easily accessible for processing by other software and services that work with big data.
-
Watch this video on the infrastructure for big data and pay attention to the discussion on analytical models. Then take notes on the different types of big data systems used in the business world.
Big data storage is used to enable easy access to large amounts of data. You learned the importance of big data infrastructure. In this next section, you will learn about the role of big data storage for data analytics.
-
-
Big data analytics explores large amounts of data to reveal unhidden patterns, correlations, and other relevant insights. Because of today’s technology, organizations can analyze data and almost immediately get results.
There are benefits to using technology and big data analytics. While earlier organizations had to gather information and conduct analyses to make future decisions, today, organizations can identify insights to make immediate decisions.
-
Read this article and pay attention to the four ways to process data, how big data analytics are used, and the methodology.
-
-
Not many people are trained to work with big data. This creates challenges for organizations that store and use big data. This is not the only challenge. Other challenges include (1) handling large amounts of data, (2) real-time analysis can be complex, and (3) data security.
-
Read this article. What are the main challenges of using big data?
-
Read this article about the healthcare sector. Compare and contrast the challenges associated with each industry.
-
-
-
Cloud-based services provide on-demand service to users via the internet. This is also known as cloud computing. Cloud computing delivers computer services ranging from applications to storage processing power. For example, instead of owning your own computing infrastructure, companies will rent access to applications and storage from a cloud service provider.
-
Read this article. Review the introduction to cloud computing and take notes on the aim and purpose of cloud computing. Then read the remainder of the article to become familiar with cloud-based services.
Keep in mind that cloud-based services can adapt or grow to meet the needs of the user. Service providers can deliver hardware and software based on organization needs. One benefit is that there is no need for organizations to own or allocate resources toward Information Technology (IT) staff.
-
Cloud-based organizations use cloud computing to deliver computing services. This includes servers, databases, networking, software, analytics, and intelligence over the cloud (internet). The cloud offers faster innovation, economic scalability, and flexibility of organizational resources.
-
Watch this video on cloud computing and business expectations. Pay attention to cloud computing and the future of IT. Take notes on the comparison between "old" computing and "cloud" computing. Listen to the examples given for each industry.
-
-
An organization’s entire virtual server can be copied or backed up to an offsite data center. Cloud disaster recovery is a service that allows for backup and recovery of remote systems on a cloud-based platform. This enables data to be retrieved and restored on a virtual host in minutes.
-
Read these sections to familiarize yourself with disaster recovery. Pay attention to the review of cloud computing and disaster recovery plans, and list the challenges associated with disaster recovery. Finally, compile a list of the different types of disaster recovery platforms.
Organizations that use cloud-based services can backup and store data in a virtual location. You learned that storing data in the cloud creates a faster and more agile organization. Think back to the list you made about the challenges associated with disaster recovery. Use what you learned about those challenges as you read this article and begin this next section.
-
-
You learned that cloud computing provides services such as applications, data servers, and computer networking. This is normally done by a third-party server located in a data center or a private cloud. The ability for organizations to become flexible, scale economically, and make faster analysis makes cloud computing the primary choice. However, there are also challenges to consider before implementing cloud computing technology.
Big data includes large amounts of both unstructured and structured data. Recent advances in technology allow organizations to store big data using traditional (non-virtual) and cloud-based services (virtual). These systems play an important role in big data analytics. However, big data and cloud computing have challenges. Remember, refer to your notes on the advantages and challenges of cloud computing.
-
Watch this video on minimizing risk in the cloud environment. Compare the challenges mentioned in this video with the list you made in the previous section. What were some common challenges that the organizations in this video faced? Why are data breaches and leaks a result of poor security?
-
-
-
This review video is an excellent way to review what you've learned so far and is presented by one of the professors who created the course.
-
Watch this as you work through the unit and prepare to take the final exam.
-
We also recommend that you review this Study Guide before taking the Unit 4 Assessment.
-
-
-
Take this assessment to see how well you understood this unit.
- This assessment does not count towards your grade. It is just for practice!
- You will see the correct answers when you submit your answers. Use this to help you study for the final exam!
- You can take this assessment as many times as you want, whenever you want.
-