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Authoring Visual Analytics Using Amazon QuickSight

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

Authoring Visual Analytics Using Amazon QuickSight

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

Course description

In this course, you will build a data visualization solution using Amazon QuickSight. QuickSight allows everyone in your organization to understand your data by exploring through interactive dashboards, asking questions in natural language, or automatically looking for patterns and outliers powered by machine learning. This course focuses on connecting to data sources, building visuals, designing interactivity, and creating calculations. You will learn how to apply security best practices to your analyses. You will also explore the machine learning capabilities built into QuickSight.

Course objectives

In this course, you will learn to:

  • Explain the benefits, use cases, and key features of Amazon QuickSight
  • Design, create, and customize QuickSight dashboards to visualize data and extract business insights from it
  • Select and configure appropriate visualization types to identify, explore, and drill down on business insights
  • Describe how to use one-click embed to incorporate analytics into applications
  • Connect, transform, and prepare data for dashboarding consumption
  • Perform advanced data calculations on QuickSight analyses
  • Describe the security mechanisms available for Amazon QuickSight
  • Apply fine-grained access control to a dataset
  • Implement machine learning on data sets for anomaly detection and forecasting
  • Explain the benefits and key features of QuickSight Q to enhance the dashboard user experience

Intended audience

This course is intended for:

  • Data and business analysts who build and manage business analytics dashboards

Prerequisites

Students with a minimum one-year experience authoring visual analytics will benefit from this course. We recommend that attendees of this course have:

  • Completed Data Analytics Fundamentals

Activities

This course includes:

  • presentations
  • demonstrations
  • group exercises
  • practice and challenge labs

Course duration / Price

  • 2 days
  • € 1,295.00 (excl. tax) per person (DE)

Course outline

This course covers the following concepts:

Day 1:

Module 1: Introduction and Overview of Amazon QuickSight

  • Introducing Amazon QuickSight
  • Why use Amazon QuickSight for data visualization

Module 2: Getting Started with Amazon QuickSight

  • Interacting with Amazon QuickSight
  • Loading data into Amazon QuickSight
  • Visualizing data in Amazon QuickSight
  • Demonstration: Walkthrough of Amazon QuickSight interface
  • Practice Lab: Create your first dashboard

Module 3: Enhancing and Adding Interactivity to Your Dashboard

  • Enhancing your dashboard
  • Demonstration: Optimize the size, layout, and aesthetics of a dashboard
  • Enhancing visualizations with interactivity
  • Demonstration: Walkthrough of dashboard interactivity features
  • Practice Lab: Enhancing your dashboard

Module 4: Preparing Datasets for Analysis

  • Working with datasets
  • Demonstration: Transform your datasets for analysis
  • Practice Lab: Preparing data for analysis

Module 5: Performing Advanced Data Calculations

  • Transform data using advanced calculations
  • Practice Lab: Performing advanced data calculations
  • Activity: Designing a Visual Analytics Solution

Day 2:

Module 6: Overview of Amazon QuickSight Security and Access Control

  • Overview of Amazon QuickSight security and access control
  • Dataset access control in Amazon QuickSight
  • Lab: Implementing access control in Amazon QuickSight visualizations

Module 7: Exploring machine learning capabilities

  • Introducing Machine Learning (ML) insights
  • Natural Language Query with QuickSight Q
  • Demonstration: Using QuickSight Q
  • Lab: Using machine learning for anomaly detection and forecasting

End of day challenge labs

  • Join data sources together
  • Create a dashboard
  • Enhance the dashboard and add interactivity
  • Perform advanced data calculations
  • Integrate machine learning tools into the dashboard

 

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 Best Practices

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

AWS Security Best Practices

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

Course description

Currently, the average cost of a security breach can be upwards of $4 million. AWS Security Best Practices provides an overview of some of the industry best practices for using AWS security and control types. This course helps you understand your responsibilities while providing valuable guidelines for how to keep your workload safe and secure. You will learn how to secure your network infrastructure using sound design options. You will also learn how you can harden your compute resources and manage them securely. Finally, by understanding AWS monitoring and alerting, you can detect and alert on suspicious events to help you quickly begin the response process in the event of a potential compromise.

Course objectives

In this course, you will learn to:

  • Design and implement a secure network infrastructure
  • Design and implement compute security
  • Design and implement a logging solution

Intended audience

This course is intended for:

  • Solutions architects, cloud engineers, including security engineers, delivery and implementation engineers, professional services, and Cloud Center of Excellence (CCOE)

Prerequisites

We recommend that attendees of this course have completed the following:

Activities

This course includes:

  • Training with instructor
  • Practical exercises

Course duration / Price

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

Course outline

This course covers the following concepts:

Module 1: AWS Security Overview

  • Shared responsibility model
  • Customer challenges
  • Frameworks and standards
  • Establishing best practices
  • Compliance in AWS

Module 2: Securing the Network

  • Flexible and secure
  • Security inside the Amazon Virtual Private Cloud (Amazon VPC)
  • Security services
  • Third-party security solutions

Lab 1: Controlling the Network

  • Create a three-security zone network infrastructure.
  • Implement network segmentation using security groups, Network Access Control Lists (NACLs), and public and private subnets.
  • Monitor network traffic to Amazon Elastic Compute Cloud (EC2) instances using VPC flow logs.

Module 3: Amazon EC2 Security

  • Compute hardening
  • Amazon Elastic Block Store (EBS) encryption
  • Secure management and maintenance
  • Detecting vulnerabilities
  • Using AWS Marketplace

Lab 2: Securing the starting point (EC2)

  • Create a custom Amazon Machine Image (AMI).
  • Deploy a new EC2 instance from a custom AMI.
  • Patch an EC2 instance using AWS Systems Manager.
  • Encrypt an EBS volume.
  • Understand how EBS encryption works and how it impacts other operations.
  • Use security groups to limit traffic between EC2 instances to only that which is encrypted.

Module 4: Monitoring and Alerting

  • Logging network traffic
  • Logging user and Application Programming Interface (API) traffic
  • Visibility with Amazon CloudWatch
  • Enhancing monitoring and alerting
  • Verifying your AWS environment

Lab 3: Security Monitoring

  • Configure an Amazon Linux 2 instance to send log files to Amazon CloudWatch.
  • Create Amazon CloudWatch alarms and notifications to monitor for failed login attempts.
  • Create Amazon CloudWatch alarms to monitor network traffic through a Network Address Translation (NAT) gateway

 

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 Cloud for Finance Professionals

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

AWS Cloud for Finance Professionals

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 how finance professionals can use Amazon Web Services (AWS) to adopt cloud in a fiscally responsible manner. You will gain foundational knowledge to help you manage, optimize, and plan cloud spend. You will learn how to influence your organization’s builders to be more accountable and cost conscious. Finally, you will consider how you can use AWS to innovate in your finance organization.

Course objectives

In this course, you will learn to:

  • Define cloud business value
  • Estimate costs associated with current and future cloud workloads
  • Use tools to report, monitor, allocate, optimize, and plan AWS spend
  • Optimize cloud spending and usage through pricing models
  • Establish best practices with Cloud Financial Management (CFM) and Cloud Financial Operations (Cloud FinOps)
  • Implement financial governance and controls
  • Drive finance organization innovation

Intended audience

This course is intended for:

  • enterprise finance stakeholders who want to learn how to maximize cloud business value, use CFM best practices, and help finance teams innovate with AWS.

Prerequisites

We recommend that attendees of this course have:

Activities

This course includes:

  • presentations
  • hands-on labs
  • demonstrations

Course duration / Price

  • 2 days / € 1,250.00 (excl. tax) per person (DE)

Course outline

Day 1
Module 1: Introduction

  • Cloud spending decisions
  • AWS pricing
  • Cost drivers
  • AWS Well-Architected Framework
  • AWS Cloud Value Framework
  • Activity 1.1: Cloud value metrics
  • Cloud Financial Management
  • Activity 1.2: Cloud Financial Management outcomes

Module 2: Planning and Forecasting

  • Estimate cloud workload costs
  • Activity 2.1: Build and refine a cost estimate
  • Budget and forecast cloud costs
  • Improve cloud financial predictability

Module 3: Measurement and Accountability

  • KPIs and unit metrics
  • Cost visibility and monitoring
  • Demonstration 3.1: Tools for cost visibility, tools for cost monitoring
  • Cost allocation and accountability
  • Cost allocation building blocks

Day 2
Module 4: Cost Optimization

  • Usage optimizations
  • Commitment-based purchase options
  • Activity 4.1: Cost optimization

Module 5: Cloud Financial Operations

  • Organizational change for CFM
  • Organization models for CFM
  • Activity 5.1: Organizational models
  • Establish a cost-aware organizational culture
  • Governance, control, and agility
  • AWS governance and control building blocks
  • Automated-based governance using AWS services

Module 6: Financial Transformation and Innovation

  • Keys to financial innovation
  • Financial transformation
  • Activity 6.1: Solutions for financial innovation

Module 7: Resources and Next Steps

  • Module resources
  • Next steps

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.

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