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Building Streaming Data Analytics Solutions on AWS

Written by Gemma Corrado on . Posted in AWS Training, Training.

Building Streaming Data Analytics Solutions on AWS

current course dates can be found at the bottom of this page … company training available on request!

Course description

In this course, you will learn to build streaming data analytics solutions using AWS services, including Amazon Kinesis and Amazon Managed Streaming for Apache Kafka (Amazon MSK). Amazon Kinesis is a massively scalable and durable real-time data streaming service. Amazon MSK offers a secure, fully managed, and highly available Apache Kafka service. You will learn how Amazon Kinesis and Amazon MSK integrate with AWS services such as AWS Glue and AWS Lambda. The course addresses the streaming data ingestion, stream storage, and stream processing components of the data analytics pipeline. You will also learn to apply security, performance, and cost management best practices to the operation of Kinesis and Amazon MSK.

 

Course objectives

In this course, you will learn to:

  • Understand the features and benefits of a modern data architecture. Learn how AWS streaming services fit into a modern data architecture
  • Design and implement a streaming data analytics solution
  • Identify and apply appropriate techniques, such as compression, sharding, and partitioning, to optimize data storage
  • Select and deploy appropriate options to ingest, transform, and store real-time and near real-time data
  • Choose the appropriate streams, clusters, topics, scaling approach, and network topology for a particular business use case
  • Understand how data storage and processing affect the analysis and visualization mechanisms needed to gain actionable business insights
  • Secure streaming data at rest and in transit
  • Monitor analytics workloads to identify and remediate problems
  • Apply cost management best practices

Intended audience

This course is intended for:

  • Data engineers and architects
  • Developers who want to build and manage real-time applications and streaming data analytics solutions

Prerequisites

We recommend that attendees of this course have:

  • At least one year of data analytics experience or direct experience building real-time applications or streaming analytics solutions. We suggest the Streaming Data Solutions on AWS whitepaper for
    those that need a refresher on streaming concepts.
  • Completed either Architecting on AWS or Data Analytics Fundamentals
  • Completed Building Data Lakes on AWS

Activities

This course includes:

  • presentations
  • practice labs
  • discussions
  • class exercises

Course duration / Price

  • 1 Day
  • € 750.00 (excl. tax) per person (DE)

Course outline

This course covers the following concepts:

Module A: Overview of Data Analytics and the Data Pipeline

  • Data analytics use cases
  • Using the data pipeline for analytics

Module 1: Using Streaming Services in the Data Analytics Pipeline

  • The importance of streaming data analytics
  • The streaming data analytics pipeline
  • Streaming concepts

Module 2: Introduction to AWS Streaming Services

  • Streaming data services in AWS
  • Amazon Kinesis in analytics solutions
  • Demonstration: Explore Amazon Kinesis Data Streams
  • Practice Lab: Setting up a streaming delivery pipeline with Amazon Kinesis
  • Using Amazon Kinesis Data Analytics
  • Introduction to Amazon MSK
  • Overview of Spark Streaming

Module 3: Using Amazon Kinesis for Real-time Data Analytics

  • Exploring Amazon Kinesis using a clickstream workload
  • Creating Kinesis data and delivery streams
  • Demonstration: Understanding producers and consumers
  • Building stream producers
  • Building stream consumers
  • Building and deploying Flink applications in Kinesis Data Analytics
  • Demonstration: Explore Zeppelin notebooks for Kinesis Data Analytics
  • Practice Lab: Streaming analytics with Amazon Kinesis Data Analytics and Apache Flink

Module 4: Securing, Monitoring, and Optimizing Amazon Kinesis

  • Optimize Amazon Kinesis to gain actionable business insights
  • Security and monitoring best practices

Module 5: Using Amazon MSK in Streaming Data Analytics Solutions

  • Use cases for Amazon MSK
  • Creating MSK clusters
  • Demonstration: Provisioning an MSK Cluster
  • Ingesting data into Amazon MSK
  • Practice Lab: Introduction to access control with Amazon MSK
  • Transforming and processing in Amazon MSK

Module 6: Securing, Monitoring, and Optimizing Amazon MSK

  • Optimizing Amazon MSK
  • Demonstration: Scaling up Amazon MSK storage
  • Practice Lab: Amazon MSK streaming pipeline and application deployment
  • Security and monitoring
  • Demonstration: Monitoring an MSK cluster

Module 7: Designing Streaming Data Analytics Solutions

  • Use case review
  • Class Exercise: Designing a streaming data analytics workflow

Module B: Developing Modern Data Architectures on AWS

  • Modern data architectures

 

IMPORTANT: Please bring your notebook (Windows, Linux or Mac) to our trainings. If this is not possible, please contact us in advance.

Course materials are in English, on request also in German (if available).
Course language is German, on request also in English.

Building Batch Data Analytics Solutions on AWS

Written by Gemma Corrado on . Posted in AWS Training, Training.

Building Batch Data Analytics Solutions on AWS

current course dates can be found at the bottom of this page … company training available on request!

Course description

In this course, you will learn to build batch data analytics solutions using Amazon EMR, an enterprise-grade Apache Spark and Apache Hadoop managed service. You will learn how Amazon EMR integrates with open-source projects such as Apache Hive, Hue, and HBase, and with AWS services such as AWS Glue and AWS Lake Formation. The course addresses data collection, ingestion, cataloging, storage, and processing components in the context of Spark and Hadoop. You will learn to use EMR Notebooks to support both analytics and machine learning workloads. You will also learn to apply security, performance, and cost management best practices to the operation of Amazon EMR.

Course objectives

In this course, you will learn to:

  • Compare the features and benefits of data warehouses, data lakes, and modern data architectures
  • Design and implement a batch data analytics solution
  • Identify and apply appropriate techniques, including compression, to optimize data storage
  • Select and deploy appropriate options to ingest, transform, and store data
  • Choose the appropriate instance and node types, clusters, auto scaling, and network topology for a particular business use case
  • Understand how data storage and processing affect the analysis and visualization mechanisms needed to gain actionable business insights
  • Secure data at rest and in transit
  • Monitor analytics workloads to identify and remediate problems
  • Apply cost management best practices

Intended audience

This course is intended for:

  • Data platform engineers
  • Architects and operators who build and manage data analytics pipelines

Prerequisites

We recommend that attendees of this course have:

Activities

This course includes:

  • Training with instructor
  • Practical exercises

Course duration / Price

  • 1 day / € 795.00 (excl. tax) per person (DE)

Course outline

Module A: Overview of Data Analytics and the Data Pipeline

  • Data analytics use cases
  • Using the data pipeline for analytics

Module 1: Introduction to Amazon EMR

  • Using Amazon EMR in analytics solutions
  • Amazon EMR cluster architecture
  • Interactive Demo 1: Launching an Amazon EMR cluster
  • Cost management strategies

Module 2: Data Analytics Pipeline Using Amazon EMR: Ingestion and Storage

  • Storage optimization with Amazon EMR
  • Data ingestion techniques

Module 3: High-Performance Batch Data Analytics Using Apache Spark on Amazon EMR

  • Apache Spark on Amazon EMR use cases
  • Why Apache Spark on Amazon EMR
  • Spark concepts
  • Interactive Demo 2: Connect to an EMR cluster and perform Scala commands using the Spark shell
  • Transformation, processing, and analytics
  • Using notebooks with Amazon EMR
  • Practice Lab 1: Low-latency data analytics using Apache Spark on Amazon EMR

Module 4: Processing and Analyzing Batch Data with Amazon EMR and Apache Hive

  • Using Amazon EMR with Hive to process batch data
  • Transformation, processing, and analytics
  • Practice Lab 2: Batch data processing using Amazon EMR with Hive
  • Introduction to Apache HBase on Amazon EMR

Module 5: Serverless Data Processing

  • Serverless data processing, transformation, and analytics
  • Using AWS Glue with Amazon EMR workloads
  • Practice Lab 3: Orchestrate data processing in Spark using AWS Step Functions

Module 6: Security and Monitoring of Amazon EMR Clusters

  • Securing EMR clusters
  • Interactive Demo 3: Client-side encryption with EMRFS
  • Monitoring and troubleshooting Amazon EMR clusters
  • Demo: Reviewing Apache Spark cluster history

Module 7: Designing Batch Data Analytics Solutions

  • Batch data analytics use cases
  • Activity: Designing a batch data analytics workflow

Module B: Developing Modern Data Architectures on AWS

  •  Modern data architectures

IMPORTANT: Please bring your notebook (Windows, Linux or Mac) to our trainings. If this is not possible, please contact us in advance.

Course materials are in English, on request also in German (if available).
Course language is German, on request also in English.

AWS Security Essentials

Written by wamrhein on . Posted in AWS Training, Training.

  • Aws Advanced Training Partner

  • Aws Premium Consuting Partner

AWS Security Essentials

current course dates can be found at the bottom of this page … company training available on request!

Course description

This course covers fundamental AWS cloud security concepts, including AWS access control, data encryption methods, and how network access to your AWS infrastructure can be secured. Based on the AWS Shared Security Model, you learn where you are responsible for implementing security in the AWS Cloud and what security-oriented services are available to you and why and how the security services can help meet the security needs of your organization.

Course objectives

In this course, you will learn to:

  • Assimilate Identify security benefits and responsibilities of using the AWS Cloud
  • Describe the access control and management features of AWS
  • Explain the available methods for providing encryption of data in transit and data at rest when storing your data in AWS.
  • Describe how to secure network access to your AWS resources
  • Determine which AWS services can be used for monitoring and incident response

Intended audience

This course is intended for:

  • Security IT business-level professionals interested in cloud security practices
  • Security professionals with minimal to no working knowledge of AWS

Prerequisites

We recommend that attendees of this course have:

  • Working knowledge of IT security practices and infrastructure concepts, familiarity with cloud computing concepts

Activities

This course includes:

  • presentations
  • hands-on labs

Course duration / Price

  • 1 Day
  • € 895.00 (excl. tax) per person (DE)
  • CHF 900.00 (excl. tax) per person (CH)

Course outline

Day 1

  • Module 1: Security on AWS
    • Security design principles in the AWS Cloud
    • AWS Shared Responsibility Model
  • Module 2: Security OF the Cloud
    • AWS Global Infrastructure
    • Data center security
    • Compliance and governance
  • Module 3: Security IN the Cloud – Part
    • Identity and access management
    • Data protection essentials
    • Lab 01 – Introduction to security policies
  • Module 4: Security IN the Cloud – Part 2
    • Securing your infrastructure
    • Monitoring and detective controls
    • Lab 02 – Securing VPC resources with Security Groups
  • Module 5: Security IN the Cloud – Part 3
    • DDoS mitigation
    • Incident response essentials
    • Lab 03 – Remediating issues with AWS Config Conformance Packs
  • Module 6: Course Wrap Up
    • AWS Well-Architected tool overview
    • Next Steps

IMPORTANT: Please bring your notebook (Windows, Linux or Mac) to our training. If this is not possible, please contact us in advance.

Course materials are in English, on request also in German (if available).
The course language is German, on request also in English.

Neue Termine in Planung!

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Quantum Computing Essentials

Written by wamrhein on . Posted in tecRacer Trainings, Training.

Quantum Computing
Essentials

Quantum technology has had a strong media presence even before Europe’s first quantum computer went into operation in Ehningen on June 15, 2021. Being one of the most important technological fields of the future, a huge amount of money is currently being invested in this field. It is therefore worthwhile to look at what added value this technology can create in the future. From an IT perspective, but also from a business analytics perspective.

  • Aws Advanced Training Partner

  • Aws Premium Consuting Partner

Objective

In a four-hour course, we will focus on the practical part of quantum technology. We will teach just as much theory as necessary to quickly compute practical examples of quantum algorithms on our own. To do this, we will take advantage of the AWS Cloud to book the necessary hardware on a short-term and temporary basis. In the process, you will learn what is already possible with the technology today, what potential it has and how it can be used productively.

All you need for the course is a laptop with free internet access. Please study the links below in advance if you would like to familiarize yourself more intensively with the mathematical-physical theory of quantum computation.

Quantum-safe encryption

Are you already using quantum-safe encryption? How long do you estimate it would take to convert all your current TLS-based encryption and which consequences this would have? Did you know that the National Institute for Standards and Technology (NIST) has been publicly soliciting standardization for quantum-safe Pulic key exchange methods since 2016?

AWS is also participating in this and you can already try out so-called post-quantum encryption methods today. It is expected that the search for a stable standard will be completed in 2024. Start preparing for the future today.

  • Quantum Computing

    13 September 2021

    A quantum computer is a processor that uses the laws of quantum mechanics. The principles of superposition and entanglement ensure that, compared to computers with electrically stored information, certain problems can be calculated much more efficiently.

    Read More

  • AWS Braket

    04 September 2021

    Amazon Braket is a fully managed quantum computing service. Self-developed quantum algorithms can be tested on quantum circuit simulators and executed on various quantum hardware technologies.

    Read More

  • Amazon SageMaker

    31 August 2021

    Amazon SageMaker is a fully managed service to work with machine learning in the cloud. Models can be developed, trained, refined, and deployed productively, including using built-in pipelines. No on-premises hardware is required.

    Read More

Facts and figures

Course Duration / Price
  • 0,5 days / € 650.00 (excl. tax) per person (DE)
Intended Audience
  • Technically interested roles that want to see today what the future has in store

Course Outline

  • Introduction

    • What is QC actually?
    • Physical basics of quantum computing and introduction to the theory of quantum computing.

  • AWS Introduction

    • What are the capabilities of AWS for QC?
    • How can AWS be used for your own purposes?
    • What are the things to consider when thinking from PoCs to MVPs to production workloads?

  • Pre- and debriefing

    • Necessary theory to be able to perform the following lab variants

  • HandsOn – Exercise 1

    • Getting started with QC in AWS.
    • Getting to know a working environment

  • HandsOn – Exercise 2

    • Graph theoretic problem with DWave or simulation problem with Rigettit/IonQ

  • HandsOn – Exercise 3

    • Practical exercise for selection: Simulation problem with Rigettit/ gate creation with IonQ.

  • WrapUp, NextSteps, Discussion

    • What have we learned?
    • How could we generate added value in the future?

IMPORTANT:

For the course you only need a laptop with free internet access.
Please study the above links in advance if you would like to familiarize yourself more intensively with the mathematical-physical theory of quantum computation

Next Quantum Computing Essentials dates:

DatumKursPreis pro TN
30.09.2026 Quantencomputing Workshop
Online in - Virtual Classroom		650,00 EUR zzgl. MwSt.Buchen

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AWS Well-Architected Best Practices

Written by wamrhein on . Posted in AWS Training, Training.

AWS Well-Architected Best Practices

current course dates can be found at the bottom of this page … company training available on request!

Course description

The AWS Well-Architected Best Practices course will help you learn a consistent approach to evaluate architectures and implement designs from a live instructor. You’ll learn how to use the Well-Architected Review process and the AWS Well-Architected Tool to conduct reviews to identify high risk issues (HRIs). In this 1-day, classroom training course, you’ll learn to apply the five pillars of the AWS Well-Architected Framework—operational excellence, security, reliability, performance efficiency, and cost optimization—to understand the impact of design decisions. You’ll apply what you’ve learned during the course to each pillar of the Well-Architected Framework through tutorials, hands-on labs, discussions, demonstrations, presentations, and group exercises.

Course objectives

In this course, you will learn to:

  • Identify the Well-Architected Framework features, design principles, design pillars, and common uses
  • Apply the design principles, key services, and best practices for each pillar of the Well-Architected Framework
  • Use the Well-Architected Tool to conduct Well-Architected Reviews

Intended audience

This course is intended for:

  • Technical professionals involved in architecting, building, and operating AWS solutions.

Prerequisites

We recommend that attendees of this course have:

Activities

This course includes:

  • Training with instructor
  • Practical exercises

Course duration / Price

  • 1 day / € 750.00 (excl. tax) per person (DE)

Course outline

Module 1: Well-Architected Introduction

  • History of Well-Architected
  • Goals of Well-Architected
  • What is the AWS Well-Architected Framework?
  • The AWS Well-Architected Tool

Module 2: Design Principles

  • Operational Excellence
  • Lab 1: Operational Excellence
  • Reliability
  • Lab 2: Reliability
  • Security
  • Lab 3: Security
  • Performance Efficiency
  • Lab 4: Performance Efficiency
  • Cost Optimization
  • Lab 5: Cost Optimization

 

IMPORTANT: Please bring your notebook (Windows, Linux or Mac) to our trainings. If this is not possible, please contact us in advance.

Course materials are in English, on request also in German (if available).
Course language is German, on request also in English.