Data Science Portfolio
This is a simple page to showcase links to different projects using a variety of tools. Such as SQL, R and Tableau.
Name - Nava Ajay Shankar A
Skills - R, SQL, Tableau, Quarto, Excel
Languages - English, Telugu, Kannada, Hindi
Visit my blog to see end to end projects with R
Below is a short note on how the tools can help the analysts with the data analysis there are other tools such as Google Sheets, Excel and Power BI which are also popular in data analytics.
1. SQL
- Most of the SQL portfolio is based on the problems and exercises from different mediums.
Click on the image to see github repository of SQL
Analysts leverage SQL (Structured Query Language) to extract actionable insights from vast datasets. They craft precise queries to retrieve and manipulate data, enabling effective analysis. SQL’s power lies in its ability to filter, aggregate, and join tables, facilitating comprehensive exploration of relationships within the data.
Analysts utilize SQL for data cleansing, transforming raw information into meaningful metrics. This language is integral for constructing reports, dashboards, and visualizations, enhancing decision-making processes. SQL proficiency empowers analysts to navigate complex databases, ensuring accurate and timely reporting. Overall, SQL serves as a cornerstone for analysts to unravel patterns, trends, and valuable business intelligence from diverse datasets.
2. R
Click on the image to see Data science projects with R
Analysts harness the versatility of R, a statistical programming language, to derive actionable insights from data. R empowers analysts to conduct robust statistical analyses, predictive modeling, and data visualization. Its extensive library ecosystem, such as ggplot2 and dplyr, streamlines complex data manipulation and visualization tasks.
Analysts leverage R’s scripting capabilities to automate repetitive processes, enhancing efficiency. With seamless integration with databases and data sources, R becomes a go-to tool for exploratory data analysis and hypothesis testing. Its open-source nature fosters collaboration, and analysts can deploy R for tasks ranging from data cleaning to advanced machine learning, solidifying its role as a powerful analytical tool.
3. Tableau
Click on the image to see Dashboards created with Tableau Desktop
Tableau empowers data analysts by simplifying complex data into interactive visualizations. Its user-friendly interface allows seamless exploration, analysis, and presentation of insights. With drag-and-drop functionality, analysts quickly transform raw data into compelling visuals, facilitating effective communication. Tableau’s real-time collaboration and dashboard sharing streamline teamwork, fostering data-driven decision-making.
In summary, Tableau empowers data analysts by providing a versatile platform for visualizing and analyzing data, fostering effective communication of insights, and enhancing overall decision-making processes.