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Course Details

  • Course Overview
  • Workshop Overview
  • Prerequisites
  • Syllabus

BDAW is a 3-day learning event that addresses advanced big data architecture topics. BDAW brings together technical contributors into a group setting to design and architect solutions to a challenging business problem. The workshop addresses big data architecture problems in general, and then applies them to the design of a challenging system. Throughout the highly interactive workshop, participants apply concepts to real-world examples resulting in detailed synergistic discussions. The workshop is conducive for participants to learn techniques for architecting big data systems, not only from Cloudera’s experience but also from the experiences of fellow participants.

The Cloudera Big Data Architecture Workshop (BDAW) is a 3-day leaning event that addresses advanced big data architecture topics. BDAW brings together technical contributors into a group setting to design and architect solutions to a challenging business problem. The workshop addresses big data architecture problems in general, and then applies them to the design of a challenging system. Throughout the highly interactive workshop, participants apply concepts to real-world examples resulting in detailed synergistic discussions. 

The workshop is conducive for participants to learn techniques for architecting big data systems, not only from Cloudera’s experience but also from the experiences of fellow participants. More specifically, BDAW addresses advanced big data architecture topics, including, data formats, transformation, real-time, batch and machine learning processing, scalability, fault tolerance, security and privacy, minimizing the risk of an unsound architecture and technology selection. To gain the most from the workshop, participants should have working knowledge of technologies such as HDFS, Spark, Map-Reduce, Hive/Impala, Data Formats and relational database management systems. Detailed API level knowledge is not needed, as there will not be any programming activities.

The workshop will be divided into small groups to discuss the problems and develop solutions. Each group will select a spokesperson who will present the group’s findings to the workshop. There will not be any programming labs, but we will have solutions implemented and deployed in the cloud for demos during the workshop.

To gain the most from the workshop, participants should have working knowledge of technologies such as HDFS, Spark, MapReduce, Hive/Impala, Data Formats and relational database management systems. Detailed API level knowledge is not needed, as there will not be any programming activities.The workshop will be divided into small groups to discuss the problems and develop solutions. Each group will select a spokesperson who will present the group’s findings to the workshop. There will not be any programming labs, but we will have solutions implemented and deployed in the cloud for demos during the workshop.

1. Introduction

2. Workshop Application Use Cases

  • Oz Metropolitan
  • Architectural questions
  • Team activity: Analyze Metroz Application Use Cases

3. Application Vertical Slice

  • Definition
  • Minimizing risk of an unsound architecture
  • Selecting a vertical slice
  • Team activity: Identify an initial vertical slice for Metroz

4. Application Data

  • Three V’s of Big Data
  • Data Lifecycle
  • Data Formats
  • Transforming Data
  • Team activity: Metroz Data Requirements

5. Application Processing

  • Real time, near real time processing
  • Batch processing
  • Data access patterns
  • Delivery and processing guarantees
  • Machine Learning pipelines
  • Team activity: identify delivery and processing patterns in Metroz,
  • characterize response time requirements, identify Machine Learning
  • pipelines

6. Scalable Applications

  • Scale up, scale out, scale to X
  • Determining if an application will scale
  • Poll: scalable airport terminal designs
  • Hadoop and Spark Scalability
  • Team activity: Scaling Metroz

7. Fault Tolerant Distributed Systems

  • Principles
  • Transparency
  • Hardware vs. Software redundancy
  • Tolerating disasters
  • Stateless functional fault tolerance
  • Stateful fault tolerance
  • Replication and group consistency
  • Fault tolerance in Spark and Map Reduce
  • Application tolerance for failures
  • Team activity: Identify Metroz component failures and requirements

8. Security and Privacy

  • Principles
  • Privacy
  • Threats
  • Technologies
  • Team activity: identify threats and security mechanisms in Metroz

9. Deployment

  • Cluster sizing and evolution
  • On-premise vs. Cloud
  • Edge computing
  • Team activity: select deployment for Metroz

10. Technology Selection

  • HDFS
  • HBase
  • Kudu
  • Relational Database Management Systems
  • Map Reduce
  • Spark, including streaming, SparkSQL and SparkML
  • Hive
  • Impala
  • Cloudera Search
  • Data Sets and Formats
  • Team activity: technologies relevant to Metroz

11. High Level Architecture

  • Architecture artifacts
  • One platform or multiple, lambda architecture
  • Team activity: produce high level architecture, selected technologies,
  • revisit vertical slice
  • Vertical Slice demonstration

12. Project Organization

  • Skill sets
  • Development methodologies
  • Team organization and education
  • Team Activity: identifying skill sets, high level plan for Metroz

13. Wrap Up

Audience

  • Developer
  • Engineer

Public Program Schedule

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FAQ

  • Why should I choose RPS?
  • I am working, is it possible to arrange the classes on weekends?
  • Please confirm if your office is open on weekends?
  • Can I get the courseware in advance before start of training?
  • What are the timings (class hours)?
  • How can I make the payment?
  • What is the mode of payment?
  • Candidate authorized RPS to charge $200. But the bank has charged $208. Why is this?
  • If we need training on one of the modules only how does that work?
  • How long before do we need to book the exams?
  • Where are your training centers available?
  • Can I pay the fee in installments?
  • What are the refund policies? Can i get my money back in case i am unable to attend the training?
  • Do you provide a bank loan facility?
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Yes, we do offer weekend classes for professionals in group or 1-to-1 Training depending upon the technology.

The administrative and sales staff works on weekdays (Monday - Friday). System Admins and Operation team are available on all days.

Yes, after you have paid the booking amount (which will be non–refundable in this case). Booking amount depends on the technology selected.

Training timings are from 9 am to 5 pm.

You can send the deposit by any of the following methods:-

  • PayPal
  • Credit Card
  • Bank Transfer
  • Demand Draft
  • Cash
  • Purchase Order (in case of Corporates / Government).
  • If you are an International student, the registration amount of USD 200 can be paid by Bank Transfer or PayPal/PayUMoney . The balance amount has to be paid by traveler's cheque or cash after arrival in India. You can also pay the balance by PayPal. There is a surcharge of 4% in this case.
  • For Indian Resident students, the course fees including registration can be paid by Cash, Cheque, Demand Draft or Bank transfer.To Know more Please call +919883305050 or Email us at info@rpsconsulting.in for any of your queries.

Overseas credit card payments through PayPal involve a mark-up of up to 4% as surcharge.

We can provide customized 1-to-1 training for a technology as per your requirement.

Most exams can be booked once you are on the course (e.g. Microsoft, ITIL, VEEAM, EC-Council). Red Hat and some other exams have to be booked in advance.

Our training centers are available in Bangalore, Chennai, Hyderabad, Pune and Delhi.

We do not have facility to pay in installments

If the course fee has been paid for and RPS cancels the Course, a refund will be provided, else the courses are non-refundable.

We do not provide loan facility.

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