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We offer students innovative, competent, and professional Data Analytics homework Help services. Our professionals conduct in-depth research to help you with your data analytics homework. If finishing your data analysis homework presents a difficult problem for you, our specialists offer live, one-on-one sessions to share assignment tips and help you grasp the material. We offer an extensive and well-structured homework outline that provides a clear understanding of the task's requirements and how to approach it. Our experts also deliver meticulous, step-by-step guidance for data interpretation and analysis. Furthermore, we provide comprehensive assistance in selecting the appropriate statistical tools for your data analytics project. Our seasoned team of specialists is proficient in various data analysis techniques, including but not limited to regression analysis, time-series analysis, text analysis, cluster analysis, factor analysis, decision tree analysis, and more. You can count on our experts for valuable insights into data interpretation and presentation. They will also assist you with writing the data analysis report.
Companies gather huge chunks of information and this data would be raw. There comes the role of data analytics which would analyse the raw data thoroughly and then extract meaningful insights from it. These insights are considered to take informed business decisions. A data analyst would extra raw information, organise the data and analyse the information besides transforming this raw information into intelligent details. The data analyst would pass on the findings that are in the recommendation and suggestion form to let the company know what to do next. Data analytics would help you predict the future trends and behaviour of customers easily.
The following are the four different types of data analytics you can use:
Descriptive analytics
It is a simple type of analytics that would take a look at what happened previously. It uses two techniques, which include data aggregation and data mining. The analyst would collect information and would present this in a summarised way and later mine the data for finding out patterns. The data portrayed will be easily understood by the whole set of audience. This type of analytics will explain what.
Diagnostic analytics
The diagnostic analytics will explore why data analysts would find out anomalies in the data. For instance, if the data shows there is a drop in sales for a particular month, then the analyst will take a look at the reason for it. The analyst will try to correlate the reason for the drop in sales. They will use regression analysis and probability theory, filtering as well as time-series analysis to do these analytics.
Predictive analytics
Predictive analytics would help you learn what would happen in the future. Analysts will come up with actionable insights to help the company learn the next steps of action. Predictive analytics would help you learn the outcome based on past data and probability theory. The analytics will help you get forecasts like the products that will be popular at certain times in a year, how much revenue is to increase or decrease at a particular time and so on.
Prescriptive analytics
It will help you know the actions and decisions to be taken. In this type of analytics, you would know how you can take advantage of the outcome you have predicted. There are different scenarios and actions a company would take to perform these analytics. Doing effective prescriptive analytics will help companies take the right decisions.
Here is a list of tools you must be proficient enough to perform data analysis:
Microsoft Excel
It is a tool that allows you to organize, format and do the calculations with the help of formulas in the spreadsheet. It is used by data analysts to run queries and to create pivot tables, graphs and different charts. Excel also comes with the macro programming language known as VBA (Visual Basic for Applications).
Tableau
It is a business intelligence and data analytics software that would be used for doing data visualization. Data analysts would use this software to filter out the raw data into maps, charts, worksheets and dashboards. It allows you to understand the data and let analysts share insights.
SAS
It is a software package that allows you to perform advanced statistical analysis as well as data visualization. It offers you different statistical methods and algorithms. There are also customizable options available for doing analysis. SAS is a widely used software package.
RapidMiner
It is a software package that is used for performing data mining, text mining, machine learning and predictive analysis. It is used widely by data analysts and scientists. It comes with a lot of features such as data modelling, validation as well as automation.
Power BI
It enables you to visualize the information and share insights throughout the organization. It is widely used for data visualization.
KNIME
It is an open-source tool that is used for data analytics and reporting and for the integration platform built for doing analytics.
Apache spark
This is an open-source tool utilized for real-time data processing.
QlikView
It is a versatile tool that empowers users to engage in data visualization, data analytics, and business intelligence.
Here are some of the commonly addressed topics in Data Analytics by our assignment and homework experts on a regular basis:
| Prescriptive Analytics | Financial Data Analytics |
| Predictive Analytics | The business problem |
| Descriptive Analytics | Diagnostic Analytics |
| Data Analytics using Pig & Hive | Managerial Analytics |
| Marketing Data Analytics | Data Summarization |
| Admin Data Analytics | Multimodal Database |
| Healthcare Data Analytics | Apache Spark |
| Environmental Data Analytics | Qlik |
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