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DSC650 Data Technology And Future Emergence Assignment Sample Malaysia

The course will provide a foundation for exploring key data analysis and management techniques that are applied to massive datasets.

These skills enable real-time decision making in distributed environments, business intelligence within the web as well as scientific discovery at large scales by permitting students to understand one of many paradigm shifts happening today: Map Reduce parallel computing model with associated technologies such Hadoop Distributed File Systems or NoSQL databases.

This gives students a fundamental understanding of data analysis and management techniques that are essential in today’s environment. The key technology behind these methods is MapReduce, which enables real-time decision making for distributed environments as well as business intelligence on the Web or scientific discovery at large scale!

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Assignment Brief 1: Demonstrate an understanding on the basic concepts and practices of big data technology. 

Big data technology is all about collecting and managing huge amounts of data. This can include anything from customer data to website traffic information. By using big data technology, businesses can gain a better understanding of their customers and what they want, as well as improve the efficiency of their operations.

There are a number of different big data technologies available, each with its own strengths and weaknesses. It’s important to choose the right technology for the job, as not all technologies are suitable for every task.

Businesses that want to make use of big data technology should carefully consider their needs and then select the right tools for the job. With the right planning and execution, businesses can reap the benefits that big data has to offer.

One of the most essential parts of big data is understanding how it works. By definition, big data is massive amounts of information that are too large for traditional software tools to handle. That means that organizations must implement new technologies in order to collect and manage all this information. This can be a big change from using existing technology, as some companies have grown accustomed to managing their information in traditional ways.

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Assignment Brief 2: Display information management skills related to data technology and future emergence.

Information technology is all about managing data, and the future of information technology will be more focused on data management skills. In other words, the future of information technology will be more focused on managing data in a way that is efficient, effective, and secure.

Data management skills are essential for any business or organization that wants to make the most of their data. By efficiently and effectively managing your data, you can reduce waste, improve decision making, and protect your organization from cyber threats. So if you want to stay ahead of the curve in information technology, make sure you focus on developing your data management skills.

But what exactly is data management? At its simplest level, data management means finding a way to store and organize your data in such a way that it can be easily accessed when you need it. This might seem like something that isn’t worth worrying about if you only have a small amount of data, but as the number of devices that collect information in your organization increases, so too does the amount of data you need to store and organize. That’s why data management skills are becoming increasingly important in information technology.

On top of that, because the number of devices that collect information is increasing, cyber threats are also increasing. This means that protecting your data is becoming more important than ever before.

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Assignment Brief 3: Demonstrate the use of data technology in big data environment

Data technology is used in big data environments to collect, process, and analyze large amounts of data.

The goal of big data analytics is to identify patterns and trends in the data that can be used to improve decision-making. For example, a retailer might use big data analytics to identify customer buying patterns and preferences. This information can then be used to create targeted marketing campaigns that are more likely to result in sales.

Big data technologies can also be used to improve operations by identifying areas where improvements can be made. For example, a transportation company might use big data analytics to optimize traffic routes and reduce wait times.

By using data technology in a big data environment, businesses can gain a competitive advantage by gaining insights into their customers’ needs and behaviors, as well as insights into their own operations.

As the access to big data continues to grow, companies are also facing challenges with centralizing data across distributed environments. Data is growing at exponential rates, but traditional tools are not equipped to handle this increase in scale. Existing tools, such as relational databases or data warehouses, are unable to scale efficiently and cost-effectively. These tools might require days or weeks for data preparation, especially when the data is scattered across multiple sources.

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