Thread by @fadaresamuel_

It's important to have a roadmap for Data Science and Analysis before starting a career in this rapidly evolving field. In this thread,l'll share the roadmap that has helped me establish a solid foundation, comprehend the entire spectrum, & keep pace with the latest technologies.

Why is it important to have a roadmap?

- Clear understanding of the field: Data science & analysis is a multidisciplinary field encompassing statistics, machine learning, programming, & data visualization. It helps in understanding skills required for each domain, & how they fit

- Setting clear goals: Having a roadmap helps in setting clear goals & objectives for your career. It allows you prioritize the skills to learn & which projects to work on to achieve those goals. It also helps in defining a path to success & a timeline to reach those milestones.

Now that we've emphasized the significance of a roadmap in the interdisciplinary field of Data Science and Analysis, it's time to delve into these hacks or learning stops, and put them into practice to maintain success in this dynamic field.

Here are the roadmaps:
1. Learn Excel for Data Science & Analysis: It's widely acknowledged that 90% of individuals who use Excel don't utilize its capabilities. It's important to understand the distinction between learning Excel & learning Excel specifically for data science.

This is a very common misconception people tend to make.l have witnessed people creating multiple queries and using programming languages to execute various data manipulation tasks that could easily be accomplished in Excel without any hassle.
#Excel #DataAnalysis #Roadmap

Four reasons why you should learn excel as your first tool:

- Versatility: Excel offers a wide range of functionalities & features used for data manipulation, wrangling, & analysis for beginners. It handles large data and perform statistical & mathematical calculations.

- Accessibility: Excel is one of the most common tools for data analysis.
It has a very user-friendly and intuitive interface relatively easy to use and requires minimal setup, making it a great tool for beginners to start learning data science and analysis.

- Transferable skills: The skills learned in Excel are transferable to other data science and analysis tools, making it a great starting point for building a career in data science and analysis.

Overall, learning Excel as your first tool in data science and analysis is important due to its accessibility, versatility, visualization capabilities, and transferable skills. It provides a strong foundation for learning other more advanced data analysis tools & techniques.

2. Learn SQL: SQL is a programming language used to manage and manipulate relational databases, and is a key tool in data science and analysis. Here are some reasons why it is important to learn SQL as your first programming language for data science and analysis

- Data Querying: SQL is used to query & retrieve data from databases, allowing analysts to efficiently retrieve & analyse voluminous data

- Data Manipulation: SQL is also used to manipulate & transform data within databases, allowing users perform calculations & transformations

- Data modeling: SQL is used to create and modify database schemas and data models, which are essential for designing and optimizing databases for efficient querying and analysis.

- Data integration: SQL is used to integrate data from different sources and databases, allowing analysts to create a comprehensive view of an organization's data.

- Transferable skills: SQL is a foundational programming language that can be applied to a wide range of fields beyond data science and analysis, such as software development and data engineering.

In summary, learning SQL as your first programming language for data science and analysis can help you develop essential skills for querying, manipulating, and analyzing large volumes of data, and is an essential skill for any data professional.

3. Learn Power Bl: Power Bl is a powerful business intelligence and data visualization tool developed by Microsoft. Here are some reasons why it is important to learn Power Bl as your first visualization tool in the field of data science and analysis.

- Ease of Use: Power Bl is user-friendly and intuitive, making it easy to create engaging and interactive data visualizations

- Industry demand: Power Bl is in high demand in industry, and learning this tool can help you stand out & advance your career in data science & analysis

- Integration with other Microsoft tools:
Power Bl is tightly integrated with other Microsoft tools, such as Excel and SharePoint, making it easy to import data from these sources and create dynamic dashboards.

- Data connectivity: Power Bl allows you to connect to a wide range of data sources, including on-premises and cloud-based databases, allowing you to quickly and easily access and visualize data.

- Collaboration: Power Bl allows you to share your dashboards and reports with others, making it easy to collaborate and communicate insights with colleagues and stakeholders.

Overall, learning Power Bl as your first visualization tool in the field of data science and analysis can help you develop essential skills for creating engaging and informative dashboards, and is an important tool for data science and analysis professionals.

There are 2 more learning stops to add in this descriptive roadmap. However, I will be stopping at 3 steps because I wouldn't want to bore readers. I'll be unveiling the rest steps in this roadmap in my next tweet this week. Thank you for reading through.

Don't repeat my mistake - despite being on the cusp of having a Master’s degree in Data Science and proficient in various tools, I had to learn Excel for analysis. Learn from my experience and invest time in mastering essential tools early on.

There will be a time you will need to perform on demand data science tasks on systems (mostly excel) of people that are not data inclined. You can’t replicate these skills you have from other tools if you don’t know how to use excel to its full potential. START RIGHT!!!