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A Data Analyst turns data into information, information into insight, and insight into business decisions. A Data Analyst conducts full lifecycle activities that include requirements analysis and design, develops business intelligence and reporting capabilities, and continuously monitors performance and quality control plans to identify improvements.
WHAT YOU WILL LEARN
- Business Intelligence/Visualization Tools
- Cloud Computing & Database Application
Snowflake, Microsoft Azure, AWS
- Modeling & Data Engineering
Data Modeling with Erwin, Data Warehousing, ETL with SSIS & Python
- Programming / Coding
SQL, Python, SAS
- Project Management & Agile Tools
The SwiftLearn Data Analyst and BI Training courses cover the following topics using a wide range of business intelligence and data analysis tools:
- Interpret business requirements, translate to data needs, analyze results using varied querying techniques and provide ongoing reports
- Develop and implement data collection systems and other strategies that optimize data efficiency and quality
- Acquire data from primary or secondary data sources and maintain databases/data systems
- Identify, analyze, and interpret trends or patterns in complex data sets
- Filter and “clean” data, review dashboards, and performance indicators to locate and correct code problems
The course also covers core concepts of databases including, business requirement analysis and gathering, SDLC methodologies, data warehousing, data modeling through the Conceptual, Logical and Physical modeling stages with industry leading tools such as Erwin Data Modeler, Oracle Data Modeler, Visio and ER Assistant.
The ability to Extract, Transform and Load (ETL) data from disparate sources into a centralized repository is key to any Business Intelligence project hence our training will equip you with thorough understanding and implementation of the ETL processes using tools such as SSIS and Informatica.
Modern Cloud computing and data engineering with AWS and Azure data tools such as S3, Blob Storage, Glue studio, DMS, Kinesis, Azure Data Factory, IAM, Lambda, Step function to architecting and building scalable cloud data infrastructure. No SQL databases and cloud data warehouse such as Snowflake, Athena and Azure database are also core components of our extensive Cloud Data Engineering training.
After completion of the training the following positions can be applied for: 1. Data Analyst 2. Technical Business Analyst 3. ETL Developer 4. Business Intelligence Developer 5. Data Scientist 6. Report Developer 7. Tableau Developer 8. Data Modeler/Architect 9. Data Engineer
The next training starts on September 05, 2022. Why wait any longer. Call the number at the contact page to register and enroll now!!!!!
Virtual live classroom:
yrs of Experience
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