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ITECH7407- Data Analytics Assignment Help

Task 1- Background information

Write a description of the selected dataset and project, and its importance for your chosen company. Information must be appropriately referenced.

Task 2 – Perform Data Mining on data view Upload the selected dataset on SAP Predictive Analysis. For your dataset, perform the relevant data analysis tasks on data uploaded using data mining techniques such as classification/association/time series/clustering and identify the BI reporting solution and/or dashboards you need to develop for the operational manager of the chosen company.

Task 3 – Research

Justify why you chose those BI reporting solution/dashboards/data mining technique in Task 3 and why those data sets attributes are present and laid out in the fashion you proposed (feel free to include all other relevant justifications).

Task 4 – Recommendations for CEO

The CEO of the chosen company would like to improve their operations. Based on your BI analysis and the insights gained from your “Dataset” in the lights of analysis performed in previous tasks, make some logical recommendations to the CEO, and justify why/how your proposal could assist in achieving operational/strategic objectives with the help of appropriate references from peer-reviewed sources. 

Task 5 – Cover letter

Write a cover letter to the CEO of the chosen firm with the important data insights and recommendations to achieve operational/strategic objectives gives accountability of your time and Money – Avail TOP results originated ITECH7407- Data Analytics Assignment Help services at best rates!


Data analytics is the process of collecting and converting unstructured data from different sources and places and it is made available to the entire analyst and finally data is delivered to organization business. There is large volume of data which is processed. Research institutions and private companies will use terabytes of data about social media business and other functions which came in to sea of data which arises as big data. Big data analytics has a lifecycle which follows a model called Crisp methodology. There are 6 phase in the life cycle listed as shown like Business understanding, Data Understanding, Data Preparation, Modeling, Evaluation & Deployment in which all the process are done in SAP prediction tool and results are predicted based on the attributes in the dataset.

Initial phase deals with the understanding of objectives and knowledge which is converted in to problem definition. The second phase is data understanding which deals with data collection and the quality can be examined to discover some of the insights of data. Third step is the data preparation step which depicts the final dataset which is put in some visualization tool to extract the result. This performs attribute selection, and cleaning of data to remove the noise. In this phase various modeling techniques are applied over the data to get the optimal results. After the modeling process it is evaluated whether it meets all the business objectives. Based on everything it is deployed. A big data analytics consist of following process which is carried out to perform some prediction results. (Katerina Lepenioti, D. A, 2018)

- Business Problem Definition
- Research
- Human Resources Assessment
- Data Acquisition
- Data Munging
- Data Storage
- Exploratory Data Analysis
- Data Preparation for Modeling and Assessment
- Modeling

Business problem definition explains the business strategy and its functions. Once the problem is find, we need to do relevant research mechanisms for doing the business analysis. Data acquisition and data munging process is taken place to predict the accurate results and to provide a proper solution to the enterprise applications. Data analysis takes place to provide the feature result and some predictions in the dataset which is selected.

Data set

Dataset is chosen is related to the pollution control and causes .The main aspect behind this task is to select the dataset which consist of minimum 10,000 rows. With that the predictions are done using SAP software. It predicts the polluted area and it causes. Pollution is one of the main hazards which are causing some dangers to the humans and animals. Here we will analyze the main causes of pollution and its effects over the humans and animals. Data is selected based on that the predictions are done. Pollution mainly causes some lung diseases in animals and humans. Children under the age group of 1-12 yrs can easily affected by some primary diseases due to pollution causes. Many infections like cold, asthma are some of the diseases which are affected and relevant remedies should be taken to control the pollution and the caused diseases in the affected areas. (Metzger, P. L, 2015).

SAP tool and its features

Sap is one of the software which best suits for enterprise applications for doing the business predictions and application related processes.CRM is one of the example of SAP application which do end-end customer related process.SAP project life cycle is shown below in which initial evaluation based on the business is done and project preparation is done by the managers to cover all the requirements to design the blue print. After the blue print is designed business solution is designed and implemented. After the implementation process testing is done and the solution is made live to the client and in the future further support and maintenance service should be given. Once the application is made live client check all the requirements of the system and gives the feedback related to developed solution. Sap tool provides many business and enterprise related solutions with the real time data analytics.

It supports various features to work with the dataset and shows some relative prediction to the real time data in business applications. There are so many responsibilities for the admin like application server monitoring, system log analysis, database maintenance, database backup schedule and restore. We need to maintain the sap license. User should be capable of creating, copying, and deletion process, job scheduling, job monitoring, job deletion etc.Only admin is given all the rights in which all the user can have some access rights to day-day activities.

Overview of SAP prediction analysis

The predictions related to SAP is shown with the concept of segmentation. The manager wants to group the data in to several groups to make the prediction. Algorithm is used iteratively to group the dataset to make the predictions. These group mechanisms are used to cluster the dataset in to groups and with that the exploration of data and anomaly identification can be done with the prediction tool. This example shows the business case turnover of the company which predicts the analysis and prediction of various attributes and their factors. The predictions are base on some attributes which is selected data set.SAP tools is applicable to both small scale and large scale industries. Based on the application need it can be used by the user needs. There are several algorithms which is applicable for SAP prediction analysis which is applied to increase the turnaround time of the system. The below example explains the margin and turnover details of the company with the help of k-means algorithm.

The prediction here taken for analyzing the pollution causes in the areas and its hazards is shown with some eminent prediction which shown as graphs and tables. Here the data can be find out and it goes for the data cleaning process which helps to clear the noise and outliers in the data set which may be further used for prediction. The analysis can be done with any one of the visualizations. There are n numbers of tools available for visualization techniques. They are R, Rapid miner, Shark, SAS, SAP, and Mongo DB etc...Which are currently used in the real time applications like enterprise and research activity. In some cases there is in built tools available which shows the result of data analytics with a predefined manner. (Poornima Selvaraj, P. M., 2018).

Creating the predictive model of selected dataset and its analysis

The built in tool export the dataset and performs some analytical process which is used for prediction of future based results. One example shows the company enterprise applications which show the margin and turnover of the company which predicts the annual sales return process of the company

Likewise all the dataset can be imported to the visualization tool. The dataset selected is related to pollution and hazardous effects to animals and humans. It depicts the land with the toxins present in the land level and sea level to causes pollution. One of the pollution caused often is noise pollution which is caused by vehicles due to fuel used. The fuel used should be in good condition and also the vehicle engine should be s4 level to avoid the minimal pollution level. The graph shows the level of pollution in different manner which predicts the future result of the selected data set. The Data set consist of many attributes like ozone level,Diesel,Toxins,pesticides present in the land to show the land surface is affected by pollution.

Also there is an important attribute which shows the data level analytics and its experimental results in the real time data. The drinking water level should be in cleanup condition. Because it may causes some air borne related diseases which easily affects child under the category of 1-12 yrs because the immunity power may be less in those category of kids. So the pollution may be causing major damage to water by mixing unwanted materials in the water which mix in it and makes the water dirty. The above graph shows different type of pollution in land surface with the ph value affecting the total area. The proper remedies should be taken and again the analysis is performed to find the calamities of the system. It may be from different sources it should be analyzed and predicted with some prediction tool

Other types of pollution include water, air, noise and soil which all causes toxins to humans and animals...Especially plastics play a major role in pollution because it can't be recycled in an easy manner. Only the usage should be banned in all the places to reduce the pollution. When the plastic is burnt it causes a major effect to the land surface by showing the air related infection to humans and animals. (Vresk, T. a, 2016)