Basics of data modelling (Entities and Relations): Data modelling involves designing the structure of a database, identifying the entities (objects or concepts) and their relationships. This skill is measured in the test to evaluate the candidate's ability to organize and represent data effectively, ensuring data integrity and optimizing database performance.
Basics of data analysis (Aggregations and Statistics): Data analysis involves examining, cleansing, transforming, and modeling data to uncover meaningful insights. This skill is measured in the test to assess the candidate's familiarity with key concepts like aggregations (sums, averages, etc.) and statistical measures (mean, median, etc.), enabling them to explore, summarize, and interpret data accurately.
Business analysis fundamentals: Business analysis involves identifying business needs, recommending solutions, and facilitating the implementation of changes. This skill is measured in the test to gauge the candidate's understanding of essential techniques and tools used in business analysis, such as SWOT analysis, stakeholder analysis, and requirements elicitation, to ensure their proficiency in analyzing and solving business problems.
Data interpretation (Charts and Graphs): Data interpretation involves understanding and deriving insights from visual representations like charts and graphs. This skill is measured in the test to evaluate the candidate's ability to interpret and analyze data visually, enabling them to effectively communicate important findings and trends to stakeholders.
Data queries and databases (SQL): Data queries and databases involve using Structured Query Language (SQL) to retrieve, manipulate, and manage data in relational database systems. This skill is measured in the test to assess the candidate's proficiency in writing SQL queries, ensuring they can effectively extract and manipulate data to support various business requirements.
Data operations (Predictions and Anomalies): Data operations involve predicting future outcomes and identifying anomalies or outliers in data. This skill is measured in the test to ascertain the candidate's knowledge and ability in using statistical techniques, machine learning algorithms, and data mining methods to perform predictive modeling and anomaly detection for valuable data-driven insights.
Data investigations (Correlations and Ranking): Data investigations involve exploring relationships between variables, identifying correlations, and ranking data based on specific criteria. This skill is measured in the test to evaluate the candidate's capability to analyze and interpret statistical relationships, enabling them to uncover patterns, make informed decisions, and identify key factors influencing outcomes.
Popular data tools (Excel): Popular data tools include software applications like Microsoft Excel, which offer features for data analysis, manipulation, and visualization. This skill is measured in the test to determine the candidate's proficiency in using Excel's advanced functions, formulas, and features for data processing, analysis, and reporting, thereby assessing their ability to leverage this widely used data tool effectively.