Midrand, South Africa | Posted on 18/12/2024
The Business Intelligence (BI) Specialist is responsible for transforming raw data into meaningful insights that drive informed decision-making across the organization. This role involves the end-to-end management of data, from warehousing and mining to analysis and reporting, ensuring data supports the strategic objectives of the CETA.
Key Responsibilities:
1. Data Warehousing :
- Centralize and consolidate data from CETA and stakeholders.
- Manage ETL (Extract, Transform, Load) processes to structure data into organized data marts.
- Ensure seamless integration of data into required systems and solutions.
2.
Data Mining :
- Identify patterns within large datasets to classify, cluster, and detect anomalies.
- Use advanced statistical and machine learning techniques for data exploration.
3.
Analytics: - Conduct data analysis through various methods, including:
- Descriptive Analytics: Summarize historical data to identify trends and patterns.
- Predictive Analytics: Use historical data to forecast future trends and outcomes.
- Prescriptive Analytics: Recommend actions based on predictive insights.
- Diagnostic Analytics: Investigate data anomalies and their underlying causes.
4.
Reporting :
- Design and generate actionable reports and dashboards.
- Distribute insights to CETA business areas and relevant stakeholders.
- Ensure reports are timely, accurate, and tailored to user needs.
5.
Performance Management :
- Monitor and evaluate Key Performance Indicators (KPIs) to measure organizational performance.
- Collaborate with teams to identify areas of improvement and develop performance-enhancing strategies.
Requirements
Qualifications and Experience :
- Bachelor’s degree in Computer Science, Information Systems, Data Science, or a related field.
- Proven experience in Business Intelligence, data warehousing, and analytics.
- Proficiency in BI tools such as Power BI, Tableau, or QlikView.
- Strong understanding of ETL processes and data integration.
- Experience with SQL and data modeling.
- Knowledge of statistical and machine learning techniques is an advantage.
Skills and Competencies: - Analytical mindset with strong problem-solving abilities.
- Excellent communication and presentation skills.
- Attention to detail and commitment to data accuracy.
- Ability to work collaboratively with cross-functional teams.
- Proactive in identifying and implementing process improvements.
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