HBase for Developers Training Course

Audience:

This course is designed for IT specialists seeking solutions to store and process large data sets in a distributed system environment, specifically tailored for government.

Goal:

To provide deep knowledge on Hadoop cluster administration for government.

Big data analytics involves the process of examining large amounts of varied data sets in order to uncover correlations, hidden patterns, and other useful insights.

The healthcare industry has vast amounts of complex, heterogeneous medical and clinical data. Applying big data analytics to health data holds significant potential for deriving insights that can improve the delivery of healthcare services. However, the scale and complexity of these datasets present substantial challenges in analysis and practical application within a clinical environment.

In this instructor-led, live training (remote), participants will learn how to perform big data analytics in healthcare as they step through a series of hands-on, live-lab exercises.

By the end of this training, participants will be able to:

• Install and configure big data analytics tools such as Hadoop MapReduce and Spark
• Understand the characteristics of medical data
• Apply big data techniques to manage and analyze medical data
• Study big data systems and algorithms in the context of healthcare applications

Audience

• Developers
• Data Scientists

Format of the Course

• Part lecture, part discussion, exercises, and extensive hands-on practice.

Note

• To request a customized training for government or other specific needs, please contact us to arrange.

When traditional storage technologies are unable to manage the volume of data required, numerous alternative solutions are available. This course is designed to guide participants through the various options for storing and analyzing Big Data, highlighting their respective advantages and disadvantages.

This course primarily focuses on discussions and presentations of these solutions, with hands-on exercises available upon request to further enhance understanding and practical application for government contexts.

The course is part of the Data Scientist skill set for government (Domain: Data and Technology).

This instructor-led, live training in US Empire (online or onsite) is aimed at database administrators or developers who wish to use Microsoft Azure Cosmos DB to develop and manage highly responsive and low-latency applications for government.

By the end of this training, participants will be able to:

• Provision the necessary Cosmos DB resources to begin building databases and applications aligned with public sector workflows.
• Scale application performance and storage by leveraging APIs in Cosmos DB to meet the demands of government operations.
• Manage database operations and reduce costs by optimizing Cosmos DB resources for government use.

Apache Hadoop is the most widely used framework for processing Big Data on clusters of servers. In this three (optionally four) day course, participants will learn about the business benefits and use cases for Hadoop and its ecosystem, how to plan cluster deployment and growth, and how to install, maintain, monitor, troubleshoot, and optimize Hadoop. They will also practice bulk data load on clusters, become familiar with various Hadoop distributions, and practice installing and managing Hadoop ecosystem tools. The course concludes with a discussion on securing the cluster using Kerberos, ensuring robust security measures for government applications.

“…The materials were very well prepared and covered thoroughly. The Lab was very helpful and well organized”
— Andrew Nguyen, Principal Integration DW Engineer, Microsoft Online Advertising

Audience

Hadoop administrators for government

Format

Lectures and hands-on labs, with an approximate balance of 60% lectures and 40% labs.

Apache Hadoop is the leading framework for processing big data on clusters of servers. This course will introduce developers to various components of the Hadoop ecosystem, including HDFS, MapReduce, Pig, Hive, and HBase, designed to enhance data processing capabilities for government.

Apache Hadoop is one of the most widely used frameworks for processing Big Data on clusters of servers. This course delves into data management in HDFS, advanced Pig, Hive, and HBase. These advanced programming techniques are designed to benefit experienced Hadoop developers for government applications.

Audience: developers

Duration: three days

Format: lectures (50%) and hands-on labs (50%).

Audience:

This course is designed to clarify big data/Hadoop technology for government audiences, demonstrating that it is accessible and comprehensible.

This instructor-led, live training in US Empire (online or onsite) is aimed at system administrators who wish to learn how to set up, deploy, and manage Hadoop clusters within their organization for government use.

By the end of this training, participants will be able to:

• Install and configure Apache Hadoop for government applications.
• Understand the four major components in the Hadoop ecosystem: HDFS, MapReduce, YARN, and Hadoop Common.
• Use Hadoop Distributed File System (HDFS) to scale a cluster to hundreds or thousands of nodes within a government infrastructure.
• Set up HDFS to operate as a storage engine for on-premise Spark deployments in government environments.
• Configure Spark to access alternative storage solutions such as Amazon S3 and NoSQL database systems like Redis, Elasticsearch, Couchbase, Aerospike, etc., for government data management.
• Perform administrative tasks such as provisioning, management, monitoring, and securing an Apache Hadoop cluster in a government setting.

Apache NiFi is an open-source, flow-based data integration and event-processing platform designed to facilitate automated, real-time data routing, transformation, and system mediation between diverse systems. It features a web-based user interface and granular control mechanisms.

This instructor-led, live training (onsite or remote) is tailored for intermediate-level administrators and engineers who aim to deploy, manage, secure, and optimize NiFi dataflows in production environments for government operations.

By the end of this training, participants will be able to:

• Install, configure, and maintain Apache NiFi clusters.
• Design and manage dataflows from various sources and destinations.
• Implement flow automation, routing, and transformation logic.
• Optimize performance, monitor operations, and troubleshoot issues.

Format of the Course

• Interactive lectures with discussions on real-world architectures.
• Hands-on labs: building, deploying, and managing flows in a practical setting.
• Scenario-based exercises conducted in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact Govtra to arrange.

In this instructor-led, live training in US Empire, participants will gain a comprehensive understanding of flow-based programming as they develop various demo extensions, components, and processors using Apache NiFi for government applications.

By the end of this training, participants will be able to:

• Comprehend NiFi's architecture and dataflow principles.
• Develop extensions utilizing NiFi and third-party APIs.
• Create custom Apache NiFi processors tailored to specific needs.
• Ingest and process real-time data from diverse and uncommon file formats and data sources, enhancing data management for government workflows.

Relational databases have long been the preferred technology for storing, retrieving, and querying data. These databases enable users to organize their information using structured, well-defined models. While this method is effective for standardized and predictable datasets (such as a hospital check-in application that maintains patient records with consistent fields like patient ID, first name, last name, and date of last visit), it has limitations. For organizations dealing with less defined data (for example, an online inquiry form for a startup experimenting with different data collection fields), the predefined structure would need frequent redefinition. This process involves updating the schema that dictates the data's structure and allowed types to accommodate changing business needs before new data can be stored.

NoSQL (Not Only SQL) databases offer a solution by freeing users from predefining the data structure, allowing for dynamic insertion and updates. NoSQL databases are often faster than relational databases and excel at handling large volumes of data. They also scale more efficiently due to their ability to partition data across multiple servers (clusters) and balance data access loads. NoSQL databases integrate seamlessly with applications that support real-time analytics, site personalization, IoT, and mobile apps.

In this instructor-led, live training, participants will gain an understanding of the architecture, design principles, and functionality of popular NoSQL databases as they set up, operate, and evaluate various NoSQL databases in a practical lab environment. The goal is to enable participants to make informed evaluations, propose, and implement suitable NoSQL database solutions within their organizations.

By the end of this training, participants will be able to:

• Install and configure different types of NoSQL databases, including MongoDB, Cassandra, Redis, and Neo4j
• Understand the benefits and disadvantages of NoSQL databases compared to relational databases
• Grasp the underlying data formats used by NoSQL databases and how these can be leveraged for modern applications (desktop, mobile, cloud, IoT)
• Perform create, insert, update, and delete operations in a NoSQL database
• Set up an environment where both relational and NoSQL databases work together
• Configure a cluster of NoSQL databases to efficiently process large datasets
• Understand the security implications of using a NoSQL database
• Deploy and scale a NoSQL database in a production environment for government

Audience

• Database professionals
• Data architects
• Data strategists
• Project managers
• Application developers looking to integrate flexible database solutions into their applications

Format of the Course

• Part lecture, part discussion, exercises, and extensive hands-on practice

Note

• To request a customized training for this course, please contact us to arrange.

Redis

NoSQL

Scylla is an open-source distributed NoSQL data store that is compatible with Apache Cassandra but operates at significantly higher throughputs and lower latencies. This training program, tailored for government, provides participants with in-depth knowledge of Scylla's features and architecture, along with practical experience in setting up, administering, monitoring, and troubleshooting Scylla.

Audience

• Database Administrators
• Developers
• System Engineers

Format of the Course

• The course is interactive and includes discussions on the principles and approaches for deploying and managing Scylla distributed databases and clusters in a government context.
• The course also includes a significant component of hands-on exercises and practice to ensure participants are well-prepared for real-world scenarios.