DSC721 Enterprise data analytics UiTM assignment example Malaysia

An assignment from the DSC721 Enterprise data analytics UiTM program. This UiTM course is designed to help enterprise users analyze and understand their data more effectively. The course covers the process of data analysis, preparation, Transformation, and destruction using open-source Venn diagramming and visualization software.

The assignment is a data analysis project that you would conduct with other students in order to gain a better understanding of their programming skills and those of the student work. The project will also include an analysis of the data from DSC721, which will be used to solve a problem or to generate results that are more accurate.

This is a Scrum-based project, meaning that the team is composed of developers (who are usually best known for developing code) and devs/admins who work together on one project. In this type of project, everyone has something to do with everyone else in order to move forward with the project as a whole. This means that there is variety in the team members and they can work on projects while continuing to meet each other for support purposes only when they need it most – then they can focus on their larger task at hand.

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This assignment will help you learn how to build a data analytics UiTM for an Enterprise. You will need to know how to use various programming languages and tools, such as SQL, ODBC, and ISQL. Additionally, you will need to be able to work with Databases such as MySQL or MongoDB.

Assignment Task 1: Examine elements that contribute to building reliable predictive models by taking into account the complexities inherent in an enterprise

A predictive model is a set of predictions that can be used to predict the outcomes of events or behaviors in the future. In order to make good decisions, it is important to incorporate knowledge about past experiences into one’s forecasts. A predictive model should include factors that are difficult to measure and That must be taken into account when developing the model?

1) The models should take into account the entire range of values for any given statistic. For example, a model with 10 predictions about a trend would also include information about each individual’s data (e.g., data from 1-week, 2-week, 3-weeks, 4-weeks, 5-months), average data (5 months), median data (2 years), and 0 Data

2) The models should consider how different scenarios might change the data(s). For example, a Model with 5 predictions about a 50% chance of event C could also model with 10 predictions to improve upon C by making D available at 50% odds。

3) The models should hold if different scenarios match or do not match what was wanted in mind when the model was created. If there is no need for the system to always meet all these expectations.

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Assignment Task 2: Construct technical concepts of predictive analytics at an enterprise-scale dealing with Big Data

Predicting the behavior of individuals and events in data sets is a key part of technical stay predictive analytics. In order to be effective, predictions need to be accurate and were made with close-to-real-time data. The power of predictive Analytics can help you identify patterns and decide when features that are out of your control will happen. For example, if there is an article published about a crime, you can predict who might do it and how many. This information is useful to law enforcement as well as for other businesses because you can better understand what they are looking for!

The goal of predictive analytics is to understand how data will change over time so that it can be used to predict changes in this data. This can be done through technical concepts such as model training, machine learning, and large scale datasets. Predictive analytics can also help businesses improve their customer experience by detecting problems before they arise and telling customers when those problems are going to happen.

Assignment Task 3: Evaluate a solution by using analytical tools in improving the enterprise’s overall performance

By using the analytical tools, the business can improve its own performance while ikanerving at the same time. The analytical tool should be able to identify opportunities and closed-formats which will cause an increase in sales or better cash flow. The tool should also be able to identify all the areas of the business where improvement is necessary but does not occur often enough. This is why it is important for businesses to use analytical tools regularly and in frequent sets so that they can constantly learn from their failures and succeed with new ideas.

The analytical tool can help to identify and solve problems that are specific to the business. It can also provide ways of improving the efficiency of the company in terms of its various activities. The analytical tool might be used as a way to determine whether a certain activity is more efficient or not, as well as it could be used to evaluate different outcomes/effects of an action/programming on the business overall.

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