Big data has become the new normal. Every enterprise wants to know how to integrate this new type of data and the associated infrastructure changes that need to be implemented. The world of big data infrastructure changes by the day, with new innovations happening everywhere. There are a slew of new technologies—Hadoop, NoSQL, BigQuery, Tableau, Qliktech, R, and Drill.
There are new papers on emerging technologies, such as Spanner and Dremmel. The big question is: Which of these technologies does your organization need? How do we evaluate and integrate them? How will this impact your EDW strategy? This session will focus on these topics and more.
What You’ll Learn
- Big data: What is it? What will it solve?
- Business users and big data
- Building the business case
- Next generation of business intelligence
- Semantics, ontologies, and more
- Managing the business rules for processing
- Case studies
- Big data and the data warehouse: the new landscape
- Technology overview
- Hadoop, NoSQL, Cassandra, Big Query, Drill, Redshift, AWS (S3, EC2)
- Programming with MapReduce
- Understanding analytical requirements
- Self-service discovery platforms
- The challenges of data processing
- Workloads
- Data management
- Infrastructure limitations
- Next-generation data warehouse
- Solution architectures
- The three S's: scalability, sustainability, and stability
- People skills
- Critical success factors
Who Should Attend
Enterprise architects and data warehouse architects; developers; anyone who wants to learn about big data technologies.
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Prerequisites
There are no prerequisites for this course.
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Outline
Module 1: Big Data and Business Case
- What is Big Data? – Creating a definition
- What will it solve? – Potential solutions for an organization (this will be specific for onsite courses)
- Business Users and Big Data
- Understanding Roles and Skiils – What does the business user bring to the table? Why should IT look to getting the business users own and drive the initiative?
- Business User Ownership – What does this entail?
- Challenges – Issues and Risks
- Building the Business Case
- Components of Big Data Business Case
- How to build the Appropriate Business Case
- Next Generation of Business Intelligence
- Analytics and Metrics – What do we derive new?
- Visualization Requirements – What are the changes and associated challenges?
- Mashups – Understading multi-dimensional data management. Metadata is critical and why?
Module 2: Semantics and Ontologies
- Introduction to Semantic Frameworks – Future of Visualization and Analytics
- Understanding Semantic integration for Big Data – Where and How? Business Benefits.
- Using Ontologies for Metadata Management – Case Study
- Managing Business Rules for Processing - Case Study
Module 3: Big Data and the Data Warehouse
- The New Landscape
- What Can We Solve
- How to Assess and Manage Data For Today and Future
- Technology overview
- Hadoop, NoSQL, Cassandra, Big Query, Drill, Redshift, AWS (S3, EC2)
- Programming with MapReduce
- Understanding analytical requirements
Module 4: Self-Service Discovery Platforms
- Challenges of Data Management and Processing
- MDM, Metadata and More – Have we moved over this?
Module 5: Workloads
- Data Management
- Infrastructure Limitations
Module 6: Next-generation data warehouse
- Solution architectures
- The three s’s: scalability, sustainability, and stability
- People skills
- Critical success factors
Module 7: Big Data Road map
- Building A Road map
- Risks and Mitigations
- Business Driven Objectives
- Solving A Million Dollar Puzzle
- Readying The Organization
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A. B. - kıdemli uzman
Türk Telekom
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D. Y. - İşgücü Yönetimi Uzmanı
Türk Telekom
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L. G. - Enterprise Architect
Türk Telekom
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Ö. Y. - IT Quality Assurance
Türk Telekom
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Ü. E. - BT KALİTE Kıdemli Mühendisi
Türk Telekom
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Y. E. - Müşteri Cihazları ve Yönetimi Uzmanı
Türk Telekom
Rated the training 5 stars.
M. A. - IT MAN.
Altınbaş Kuyumculuk
Rated the training 5 stars.