Job Description

SQL Must have all of the Beginner SQL Skills Familiar with MS SQL Do a basic SELECT to extract data from a single table Add a filter with a WHERE clause Understand the difference between a LEFT JOIN and an INNER JOIN Apply sorting with an ORDER BY clause Do some basic aggregation, the GROUP BY command and a SUM or COUNT Understand the basics of date and time functions - GETDATE() at least At the very least understand the challenges presented by NULL values in data Moderate SQL Skill - Minimum String handling and data type conversions The CASE statement Combining datasets with UNION and UNION ALL Numeric calculations and number wrangling with +, -, * and / (that s plus, minus, subtract and divide to the layperson) Subqueries and deriver tables CTEs and temp tables Window functions Advanced SQL Skills - Desired Data manipulation with INSERT, UPDATE and DELETE Correlated subqueries Views and stored procedures The MERGE statement User defined functions The APPLY command Indexing and performance Loops and dynamic SQL PowerBI: Moderate to advanced Power BI skills include: complex data modeling with relationships and hierarchies, advanced DAX calculations, creating interactive dashboards with dynamic filtering, intricate data visualizations, efficient data transformation using Power Query, integrating data from diverse sources, and applying data analysis techniques to extract deep business insights. Key elements of moderate to advanced Power BI skills: SQL Skills Beginner SQL Skills + Moderate SQL Skills from the list above Data Modeling: Building intricate data models with multiple tables, relationships, and hierarchies. Utilizing advanced data modeling techniques like date tables, virtual tables, and calculated columns. DAX Calculations: Mastering complex DAX functions like time intelligence, custom aggregations, and iterative calculations. Optimizing DAX formulas for performance. Data Visualization: Creating highly customized and interactive visualizations beyond basic charts and graphs. Implementing advanced visual elements like tooltips, drill-downs, and slicers. Power Query Transformation: Advanced data cleaning and manipulation using Power Query with complex transformations, conditional logic, and data merging. Data Integration: Connecting to diverse data sources, including APIs, cloud databases, and flat files. Handling data refreshes and data quality checks. Dashboard Design: Designing intuitive and user-friendly dashboards with effective storytelling elements. Incorporating dynamic elements like real-time data updates. Data Analysis: Performing in-depth data analysis using advanced filtering, segmentation, and trend analysis. Interpreting data insights and communicating key findings effectively.