This is an open source library of data science, data analytics and data engineering resources. Wether you are breaking into the field or you are an expert you can find resouces here and also contribute resources. All I ask is consume as much information as you can to aid you in your career but remember you also have somthing to contribute, identify a gap in the information or a typo, you have something to contribute.
The following folders have sub folders.
A data scientist might do the following tasks on a day-to-day basis:
- Find patterns and trends in datasets to uncover insights
- Create algorithms and data models to forecast outcomes
- Use machine learning techniques to improve quality of data or product offerings
- Communicate recommendations to other teams and senior staff
- Deploy data tools such as Python, R, SAS, or SQL in data analysis
- Stay on top of innovations in the data science field
You can expect the following sub folders
- 1.1 Python
- 1.2 R
- 1.3 SQL
Data analysis is a process of inspecting, cleansing, transforming, and modelling data with the goal of discovering useful information, informing conclusions, and supporting decision-making
Data analysis is the process of gleaning insights from data to help inform better business decisions. The process of analyzing data typically moves through five iterative phases:
- Identify the data you want to analyze
- Collect the data
- Clean the data in preparation for analysis
- Analyze the data
- Interpret the results of the analysis
You can find the follwoing sub folders
- 2.1 Power BI
- 2.2 Tableau
BAs engage with business leaders and users to understand how data-driven changes to process, products, services, software and hardware can improve efficiencies and add value. They must articulate those ideas but also balance them against what’s technologically feasible and financially and functionally reasonable. Depending on the role, you might work with data sets to improve products, hardware, tools, software, services or process.
- Creating a detailed business analysis, outlining problems, opportunities and solutions for a business
- Budgeting and forecasting
- Planning and monitoring
- Variance analysis
- Pricing
- Reporting
- Defining business requirements and reporting them back to stakeholder
Data engineering enables data-driven decision making by collecting, transforming, and visualizing data. A data engineer designs, builds, maintains, and troubleshoots data processing systems with a particular emphasis on the security, reliability, fault-tolerance, scalability, fidelity, and efficiency of such systems.
When you are working on an offline study with an excel that is a few megabytes you can get away with seeking advacement computing resources, however eventually you will need to deploy your dashboard or model for the organisation to use and that is where you will need to acquire cloud computing services from one of the following providers. Find the information you need to start under each sub folder depending on the service provider of your company's choice.
- 5.1 AWS
- 5.2 Azure
- 5.3 GCP
- 5.4 IBM
Project management is key to successful project execution and value and delivery in the data role. So in this folder you can expect to see the following resources to enable proper project documentation.
- Project management Template
- Project Charter Framework
- Canva framework
- Business Requirements Templates
- Project Memo
- Pitch decks templates
Data governance persona is concerned with the following
- Data Quality
- Data Ownersip
- Data Security and
- Data accessibility
This folder is for resources for data leads, data managers and senior roles in the data profession. You can expect to find the following material
- Project Management Frameworks
- Jargon Explainers
- Business opportunities and Trends in the data universe
Clone the repo add more resources you have.
- Business Analyst : https://www.cio.com/article/276798/project-management-what-do-business-analysts-actually-do-for-software-implementation-projects.html#:~:text=Business%20analysts%20(BAs)%20are%20responsible,reports%20to%20executives%20and%20stakeholders.
- Data Analyst: https://www.coursera.org/articles/what-does-a-data-analyst-do-a-career-guide
- Data Scientist: https://www.coursera.org/articles/what-is-a-data-scientist
- R Cheatsheets: https://www.rstudio.com/resources/cheatsheets/