Data Analyst by Ali Hassan

Data Analyst by Ali HassanData Analyst by Ali Hassan

Data Analyst

Ali Hassan

Starting at

/hr

About this service

Summary

As a data analyst, I provide a wide range of services targeted at assisting clients in gaining important insights from their data and making educated decisions. Here is a complete list of the services I offer:

Data Exploration and Collection:

Collaborate with customers to understand their data sources, goals, and needs.

Data may be collected and consolidated from a variety of sources, including databases, APIs, spreadsheets, and external datasets.

Conduct data quality checks and fix any issues with data completeness, correctness, or consistency.

Data Cleaning and Preprocessing:

Remove duplicates, handle missing numbers, and fix problems in the data.

Standardise and normalize data formats to guarantee consistency and compatibility across several sources.

As needed, transform and reorganize data by aggregating or disaggregating data to the appropriate degree of granularity.

Data Analysis and Modeling:

Analyze the data using statistical techniques and algorithms to derive useful insights.

Analyse exploratory data to find patterns, trends, correlations, and outliers.

To develop data-driven predictions or classifications, create predictive models such as regression, classification, or clustering models.

Data Visualization and Reporting:

To successfully communicate data insights, create visualizations like charts, graphs, or interactive dashboards.

Create and provide reports that summarise the results, important metrics, and visual representations of the data.

Customise visualizations and reports to meet the client's individual needs and preferences.

Statistical Analysis and Hypothesis Testing:

To generate statistically significant inferences from data, use statistical tests and procedures such as hypothesis testing, ANOVA, or chi-square tests.

To find links or patterns in the data, use statistical modeling techniques such as regression analysis, time series analysis, or factor analysis.

Interpret the outcomes of statistical analysis to give relevant insights and effective suggestions.

Data-Driven Decision-Making:

Work with customers to understand their company goals and translate them into data analysis objectives.

Provide analysis-based insights and suggestions to enhance evidence-based decision-making.

Assist with the identification of key performance indicators (KPIs) and the development of metrics to track and assess progress toward company objectives.

Data Strategy and Planning:

Assist customers in developing data strategies and roadmaps that are in line with their company goals.

Identify ways to improve data collecting, storage, integration, and analysis procedures.

Provide guidance on best practices for data governance, data privacy, and data security.

Ongoing Support and Monitoring:

Maintain continuing customer assistance by checking data quality, analyzing trends, and upgrading models as appropriate.

Conduct regular evaluations to evaluate the efficacy of implemented solutions and suggest areas for improvement.

Keep current on industry trends, new technologies, and best practices in data analysis, and provide recommendations for innovation and optimization.

It should be noted that the services supplied by a data analyst may differ based on the individual demands and requirements of each customer. The outputs are tailored to the project's specific issues and objectives, ensuring that the customer obtains meaningful insights and effective suggestions based on their data.

What's included

Data analysis report
This report will provide a summary of the data analysis performed, including key findings, trends, and insights.
Visualizations and dashboards
Create visualizations such as charts, graphs, and tables to help the client understand the data and the insights that can be gleaned from it. These visualizations may be presented as a dashboard, which allows the client to interact with the data and explore it further.
Data cleaning and preprocessing documentation
If the client has provided the data to be analyzed, provide documentation on the steps taken to clean and preprocess the data to ensure accuracy and consistency.
Predictive models or algorithms
If the project incorporates predictive analytics, supply trained models or algorithms that may be used to create predictions or classifications based on fresh data. This might take the form of code, scripts, or a model that has been deployed.
Data-driven insights and recommendations:
Based on the analysis, deliver actionable insights. Identifying patterns, correlations, or anomalies in data, as well as recommendations for company strategies, process changes, cost optimization, or focused marketing activities, are examples of these insights.
Documentation of methodology and assumptions
Give documentation that explains the methodology and assumptions utilized throughout the study. This aids the client's understanding of the strategy while also ensuring transparency and repeatability.
Technical documentation
Provide technical documentation to help the client understand the methodology used for data analysis and the tools used to perform the analysis.
Presentation and communication materials
To successfully convey the essential results, insights, and suggestions to the client or other stakeholders, develop presentations, slide decks, or summaries. These resources are often utilized in meetings, seminars, and executive briefings.

Example projects

Hotel Booking Project

HR Analytics

Skills and tools

Data Scientist

Data Visualizer

Data Analyst

Microsoft Excel

Microsoft Power BI

Python

SQL

Tableau

More services

Business Analyst/Consultant

Example projects

STARTING AT

$30/hour

hourly rate

Data Analyst

Ali Hassan

Starting at

/hr

About this service

Summary

Data Exploration and Collection:

Collaborate with customers to understand their data sources, goals, and needs.

Data may be collected and consolidated from a variety of sources, including databases, APIs, spreadsheets, and external datasets.

Conduct data quality checks and fix any issues with data completeness, correctness, or consistency.

Data Cleaning and Preprocessing:

Remove duplicates, handle missing numbers, and fix problems in the data.

Standardise and normalize data formats to guarantee consistency and compatibility across several sources.

As needed, transform and reorganize data by aggregating or disaggregating data to the appropriate degree of granularity.

Data Analysis and Modeling:

Analyze the data using statistical techniques and algorithms to derive useful insights.

Analyse exploratory data to find patterns, trends, correlations, and outliers.

To develop data-driven predictions or classifications, create predictive models such as regression, classification, or clustering models.

Data Visualization and Reporting:

To successfully communicate data insights, create visualizations like charts, graphs, or interactive dashboards.

Create and provide reports that summarise the results, important metrics, and visual representations of the data.

Customise visualizations and reports to meet the client's individual needs and preferences.

Statistical Analysis and Hypothesis Testing:

To generate statistically significant inferences from data, use statistical tests and procedures such as hypothesis testing, ANOVA, or chi-square tests.

To find links or patterns in the data, use statistical modeling techniques such as regression analysis, time series analysis, or factor analysis.

Interpret the outcomes of statistical analysis to give relevant insights and effective suggestions.

Data-Driven Decision-Making:

Work with customers to understand their company goals and translate them into data analysis objectives.

Provide analysis-based insights and suggestions to enhance evidence-based decision-making.

Assist with the identification of key performance indicators (KPIs) and the development of metrics to track and assess progress toward company objectives.

Data Strategy and Planning:

Assist customers in developing data strategies and roadmaps that are in line with their company goals.

Identify ways to improve data collecting, storage, integration, and analysis procedures.

Provide guidance on best practices for data governance, data privacy, and data security.

Ongoing Support and Monitoring:

Maintain continuing customer assistance by checking data quality, analyzing trends, and upgrading models as appropriate.

Conduct regular evaluations to evaluate the efficacy of implemented solutions and suggest areas for improvement.

Keep current on industry trends, new technologies, and best practices in data analysis, and provide recommendations for innovation and optimization.

What's included

Data analysis report
This report will provide a summary of the data analysis performed, including key findings, trends, and insights.
Visualizations and dashboards
Create visualizations such as charts, graphs, and tables to help the client understand the data and the insights that can be gleaned from it. These visualizations may be presented as a dashboard, which allows the client to interact with the data and explore it further.
Data cleaning and preprocessing documentation
If the client has provided the data to be analyzed, provide documentation on the steps taken to clean and preprocess the data to ensure accuracy and consistency.
Predictive models or algorithms
If the project incorporates predictive analytics, supply trained models or algorithms that may be used to create predictions or classifications based on fresh data. This might take the form of code, scripts, or a model that has been deployed.
Data-driven insights and recommendations:
Based on the analysis, deliver actionable insights. Identifying patterns, correlations, or anomalies in data, as well as recommendations for company strategies, process changes, cost optimization, or focused marketing activities, are examples of these insights.
Documentation of methodology and assumptions
Give documentation that explains the methodology and assumptions utilized throughout the study. This aids the client's understanding of the strategy while also ensuring transparency and repeatability.
Technical documentation
Provide technical documentation to help the client understand the methodology used for data analysis and the tools used to perform the analysis.
Presentation and communication materials
To successfully convey the essential results, insights, and suggestions to the client or other stakeholders, develop presentations, slide decks, or summaries. These resources are often utilized in meetings, seminars, and executive briefings.

Example projects

Hotel Booking Project

HR Analytics

Skills and tools

Data Scientist

Data Visualizer

Data Analyst

Microsoft Excel

Microsoft Power BI

Python

SQL

Tableau

More services

Business Analyst/Consultant

Example projects

STARTING AT

$30/hour

hourly rate