Overview:
Data Risk PM
Must have worked in data warehouse/data lake as data analyst, creating data mapping, data extraction logic from source systems to target data platform.
Using automated tools to extract data from primary and secondary sources
Removing corrupted data and fixing coding errors and related problems
Performing analysis to assess the quality and meaning of data
Using statistical tools to identify, analyze, and interpret patterns and trends in complex data sets could be helpful for the diagnosis and predictio
Preparing final analysis reports for the stakeholders to understand the data-analysis steps, enabling them to take important decisions based on various facts and trends.
Another integral element of the data analyst job description is EDA or Exploratory Data Analysis Project. In such data analyst projects, the analyst needs to scrutinize data to recognize and identify patterns. The next thing data analysts do is use data modeling techniques to summarize the overall features of data analysis.
Essential Data Analyst Skills
Data analysts need a mix of technical, analytical, and soft skills to effectively analyze data and communicate their findings. Here are some essential skills for data analysts:
1. Data Cleaning and Preparation
Data analysts should know how to clean and prepare data for analysis. This includes removing errors, identifying outliers, and transforming data into a format that can be analyzed.
2. Data Analysis and Exploration
Data analysts need to be able to analyze data and explore it for insights. This includes using statistical methods to test hypotheses, identify trends, and make predictions.
4. Programming
Knowledge of programming languages, especially:
Python: Libraries like pandas, numpy, and scikit-learn are essential for data manipulation and analysis.
R: Another powerful language for statistical analysis and data visualization.
5. Database Management
The ability to query databases using SQL is essential for extracting data. Knowledge of database systems like MySQL, PostgreSQL, Oracle, or MS SQL.
7. Data Visualization
Using tools and libraries like Tableau, Power BI
12. Communication
Clearly conveying findings, both written and orally, to non-technical stakeholders. This includes creating reports and presentations that gives the insights from the data.
13. Problem-Solving
Coming up with solutions to business problems using data-driven approaches.
14. Teamwork
Collaborating with other departments or teams, understanding their needs, and providing them with relevant data insights.
Responsibilities:
To work closely with source system team, business analyst, data modeler to understand the underlying data structure and create data mappings from source system to data models to data marts and reports.
Experience:
10-12years
