Introduction to BigData and Cloud Technologies

BigData and Cloud explained with real-world examples in this intensive 1-day workshop

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1 day
Interactive presentations, Q&A panel
Not needed, no hands-on exercises
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Itamar Syn-Hershko Itamar Syn-Hershko
Itamar is a BigData and search technologies expert, and BigData Boutique's CTO. Equipped with many years of experience building and optimizing data platforms for organizations in various scales, Itamar's current job is to keep BigData Boutique's team engaged with the latest technologies and working with customers to optimize their journey in the world of BigData.
Vadim Solovey Vadim Solovey
Vadim is a cloud and architecture expert. He is the founding partner of DoIT International, and an AWS Certified Solutions Architect and a Google Developer expert. Over the last years, Vadim has helped countless companies to realize their cloud dreams into fully developed deployments based on cloud solutions. Vadim oversees technology and makes the hard stuff simple.
Demi Ben-Ari Demi Ben-Ari
Demi is the Co-Founder and VP R&D @ Panorays, with over 10 years of experience in building various systems both from the field of near real time applications and Big Data distributed systems. Holds a BS'c in computer science and Management from the Academic College of Tel-Aviv Yaffo. Co-Founder of the "Big Things" BigData Community and a software development groupie, Interested in tackling cutting edge technologies.

How can we store or process large volumes of data? how to deal with a massive stream of events coming at high velocity? what really is BigData? How does a BigData-ready system look like? and how can Clouds help?

The topics of BigData and Cloud technologoies are being mentioned a lot, but it's hard to know where to start or what technologies to use.

Join our internationally renowned instructors for a full day packed of knowledge sharing. Let us give you an overview with short deep-dives into the vast landscapes of BigData, everything you need to get started with the technologies that changed the world.


This course is aimed at giving a good overview for developers and decision-makers new to the field, as well as giving insights and valuable pointers to developers with practical experience.

  • Understanding the challenges with BigData, and approaches for solving them.
  • Storage, Compute and Stream Processing - and an overview of commonly used technologies.
  • Showcasing the characteristics and architecture of a BigData-ready system.
  • Using Cloud technologies, and overview of the notable ones.




  • What is BigData? and more importantly, what is not BigData?
  • Dealing with the challenges of Volume, Velocity and Variety of data.
  • The Hadoop ecosystem and it's current state
  • Why do we need new technologies?
  • Distributed file systems (HDFS, consistent hashing, and more)
  • File formats, and why they matter
  • NoSQL and the CAP Theorem
  • Properties of modern storage solution (Schemaless, redundancy, relaxed consistency)
  • Polyglot persistence
  • Overview of NoSQL technologies
  • Batch processing and why we can't do ad-hoc querying.
  • The Map/Reduce model and locality of data
  • Hadoop's MapReduce and YARN
  • Computation frameworks like Apache Spark and Flink
  • Monitoring of batch jobs and Spark computations
  • Machine learning
  • Distributed systems, microservices, containers and 'serverless'
  • Discovery, synchronization and configuration management
  • Queue systems and commit logs
  • Data workflows and pipelines
  • Design guidelines (explicit consistency expectations, idempotence, and more)
  • Monitoring and alerting (ELK, Graphite, Grafana, Graylog, Redash, Reimann and more)
  • Data warehousing
  • Micro batching
  • Stream processing (Apache Storm, Heron and similar technologies)
  • Lambda architecture
  • Why cloud?
  • Overview of Amazon Web Services
  • Overview of Google Cloud Platform
  • Overview of Microsoft Azure
  • Comparison and highlight of notable strengths of each
  • BigData on the cloud

Q&A panel with our experts - ask us anything.

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