Security Course Flow

We are often asked what is the recommended sequence of classes.  Here is our recommended sequence of classes for The Security Field.

Certified Information Security Manager (CISM)

CT-325 CompTIA Security+ Arrowright TN-825 Certified Information Security Manager

Certified Information Systems Auditor(CISA)

CT-325 CompTIA Security+ Arrowright TN-425 Certified Ethical Hacker Arrowright TN-822: Certified Information Systems Auditor (CISA)

Certified Information Systems Security Professional(CISSP)

CT-325 CompTIA Security+ Arrowright TN-425 Certified Ethical Hacker Arrowright TN-815 CISSP Certification Prep Seminar

 

DP-201: Designing an Azure Data Solution

 

Course Overview:

In this course, the students will design various data platform technologies into solutions that are in line with business and technical requirements. This can include on-premises, cloud, and hybrid data scenarios which incorporate relational, NoSQL, or Data Warehouse data. They will also learn how to design process architectures using a range of technologies for both streaming and batch data. The students will also explore how to design data security, including data access, data policies, and standards. They will also design Azure data solutions, which includes the optimization, availability, and disaster recovery of big data, batch processing, and streaming data solutions.

TechNow has worked worldwide enterprise infrastructures for over 20 years and has developed demos and labs to exemplify the techniques required to demonstrate cloud technologies and to effectively manage security in the cloud environment.

Attendees to DP-201: Designing an Azure Data Solution will receive TechNow approved course materials and expert instruction.

Date/Locations:

No Events

Course Duration: 3 days

Course Outline:

  • Data Platform Architecture Considerations
  • Azure Batch Processing Reference Architectures
  • Azure Real-Time Reference Architectures
  • Data Platform Security Design Considerations
  • Designing for Resiliency and Scale
  • Design for Efficiency and Operations

Prerequisites :

      • In addition to their professional experience, students who take this training should have technical knowledge equivalent to the following courses:
      • AZ-900: Microsoft Azure Fundamentals
      • DP-200: Implementing an Azure Data Solution

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DP-200: Implementing an Azure Data Solution

 

Course Overview:

In this course, the students will implement various data platform technologies into solutions that are in-line with business and technical requirements, including on-premises, cloud, and hybrid data scenarios incorporating both relational and NoSQL data. They will also learn how to process data using a range of technologies and languages for both streaming and batch data.

The students will also explore how to implement data security, including authentication, authorization, data policies, and standards. They will also define and implement data solution monitoring for both the data storage and data processing activities. Finally, they will manage and troubleshoot Azure data solutions which includes the optimization and disaster recovery of big data, batch processing, and streaming data solutions.

TechNow has worked worldwide enterprise infrastructures for over 20 years and has developed demos and labs to exemplify the techniques required to demonstrate cloud technologies and to effectively manage security in the cloud environment.

Attendees to DP-200: Implementing an Azure Data Solution will receive TechNow approved course materials and expert instruction.

Date/Locations:

No Events

Course Duration: 4 days

Course Outline:

  • Azure for the Data Engineer
  • Working with Data Storage
  • Enabling Team Based Data Science with Azure Databricks
  • Building Globally Distributed Databases with Cosmos DB
  • Working with Relational Data Stores in the Cloud
  • Performing Real-Time Analytics with Stream Analytics
  • Orchestrating Data Movement with Azure Data Factory
  • Securing Azure Data Platforms
  • Monitoring and Troubleshooting Data Storage and Processing

Prerequisites :

      • In addition to their professional experience, students who take this training should have technical knowledge equivalent to the following courses:
      • AZ-900: Microsoft Azure Fundamentals

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TN-430: Elasticsearch Engineer (ELK)

Course Overview:

Getting started with the Elastic Stack (ELK), optimizing search performance and building efficient clusters. Ingest and process data, writing complex search requests and response utilization, scaling of clusters up or down, managing indices in large clusters and multiple clusters, management of clusters and troubleshooting recommendations.

Attendees to TN-430: Elasticsearch Engineer (ELK) will receive TechNow approved course materials, expert instruction, and prepare you to take ELK exam.

 

Document Flow Chart iconsm

Dates/Locations:

No Events

Duration: 5 Days

Course Outline:

Data Management

  • Define an index that satisfies a given set of requirements
  • Define and use an index template for a given pattern that satisfies a given set of requirements
  • Define and use a dynamic template that satisfies a given set of requirements
  • Define an Index Lifecycle Management policy for a time-series index
  • Define an index template that creates a new data stream

Searching Data

  • Write and execute a search query for terms and/or phrases in one or more fields of an index
  • Write and execute a search query that is a Boolean combination of multiple queries and filters
  • Write an asynchronous search
  • Write and execute metric and bucket aggregations
  • Write and execute aggregations that contain sub-aggregations
  • Write and execute a query that searches across multiple clusters
  • Write and execute a search that utilizes a runtime field

Developing Search Applications

  • Highlight the search terms in the response of a query
  • Sort the results of a query by a given set of requirements
  • Implement pagination of the results of a search query
  • Define and use index aliases
  • Define and use a search template

Data Processing

  • Define a mapping that satisfies a given set of requirements
  • Define and use a custom analyzer that satisfies a given set of requirements
  • Define and use multi-fields with different data types and/or analyzers
  • Use the Reindex API and Update By Query API to reindex and/or update documents
  • Define and use an ingest pipeline that satisfies a given set of requirements, including the use of Painless to modify documents
  •   Define runtime fields to retrieve custom values using Painless scripting

Cluster Management

  • Diagnose shard issues and repair a cluster’s health
  • Backup and restore a cluster and/or specific indices
  • Configure a snapshot to be searchable
  • Configure a cluster for cross-cluster search
  • Implement cross-cluster replication

 

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