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Big Data Architecture & Technology for Analytics
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OVERVIEW
This one-day course is aimed to get you up to scratch on big data technologies such as , Spark, Cloud Storage Data Lakes, Hadoop, Lakehouses (e.g., Databricks Lakehouse Platform, Apache Iceberg), Flink, Analytical SQL, NoSQL DBMSs, and Multi-Platform Analytics. What is big data? How can you make use of it? How does it integrate with a traditional analytical environment? How do you re-define your architecture to create a stronger analytical foundation for your company? What skills do you need to develop for big data analytics? All of these questions are addressed in this knowledge packed course.
AUDIENCE
IT directors, CIO’s, CDO’s, IT Managers, BI Managers, data warehousing professionals, data scientists, enterprise architects, data architects, data engineers
LEARNING OBJECTIVES
Attendees to this seminar will learn:
- How big data creates several new types of analytical workload
- Big data technology platforms beyond the data warehouse
- Big data analytical techniques and front-end tools
- Understand when to use what where – business use cases for different big data technologies
- How to create a stronger data and analytical architecture by integrating big data, data science, data warehouses and BI
- How to integrate real-time data into your data warehouse
- How to analyse un-modelled, multi-structured data using cloud storage, Spark and Hadoop
- How to leverage predictive analytics in BI reports & dashboards
MODULES
- Module 1: An Introduction to Big Data
- Module 2: Big Data Technology
- Module 3: Integrating Big Data Analytics into the Enterprise
- Module 4: Ingest, Prepare, Analyse and Govern Big Data