HBase for Developers Training Course

Audience:

This course is designed for IT professionals seeking solutions to store and process large datasets within a distributed system environment.

Goal:

To develop in-depth knowledge of Hadoop cluster administration.

Big data analytics is the process of examining vast volumes of diverse datasets to uncover correlations, hidden patterns, and other valuable insights.

The healthcare sector generates massive amounts of complex, heterogeneous medical and clinical data. Applying big data analytics to this information holds immense potential for deriving insights that improve healthcare delivery. However, the sheer scale of these datasets presents significant challenges for analysis and practical implementation in clinical environments.

In this instructor-led, live remote training, participants will learn how to perform big data analytics in healthcare by progressing 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 handle medical data
• Study big data systems and algorithms within the context of health applications

Audience

• Developers
• Data Scientists

Format of the Course

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

Note

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

When conventional storage systems cannot manage the volume of data required, numerous alternative technologies are available. This course guides participants through the various options for storing and analyzing Big Data, highlighting their respective advantages and disadvantages.

The course primarily emphasizes discussion and the presentation of solutions, with hands-on exercises available upon request.

This instructor-led, live training in Italy (online or onsite) is aimed at beginner-level and intermediate-level professionals who wish to use big data and database concepts to understand modern data platforms and make better technology and business decisions.

By the end of this training, participants will be able to: explain core database and big data concepts, compare major data platform options, describe how data is stored and processed, and identify practical use cases and governance needs.

This instructor-led, live training in Italy (online or onsite) is designed for database administrators and developers who want to utilize Microsoft Azure Cosmos DB to develop and manage highly responsive, low-latency applications.

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

• Provision the necessary Cosmos DB resources to start building databases and applications.
• Scale application performance and storage by utilizing APIs in Cosmos DB.
• Manage database operations and reduce cost by optimizing Cosmos DB resources.

Apache Hadoop stands as the leading framework for processing Big Data across server clusters. This intensive three-day course (with an optional fourth day) equips attendees with a deep understanding of the business value and practical use cases of Hadoop and its surrounding ecosystem. Participants will learn how to plan for cluster deployment and scalability, as well as master the installation, maintenance, monitoring, troubleshooting, and optimization of Hadoop systems. The curriculum includes hands-on practice with bulk data loading, exploration of various Hadoop distributions, and the management of ecosystem tools. The course concludes with an in-depth discussion on securing clusters using Kerberos.

\u201c\u2026The materials were exceptionally well-prepared and thoroughly covered. The lab sessions were very helpful and meticulously organized.\u201d
\u2014 Andrew Nguyen, Principal Integration DW Engineer, Microsoft Online Advertising

Audience

Professionals serving as Hadoop administrators.

Format

A blend of lectures and hands-on laboratories, maintaining an approximate split of 60% theoretical instruction and 40% practical labs.

Apache Hadoop stands out as the leading framework for processing Big Data across server clusters. This course serves as an introduction for developers to the key components of the Hadoop ecosystem, including HDFS, MapReduce, Pig, Hive, and HBase.

Apache Hadoop stands out as one of the most widely adopted frameworks for managing Big Data across server clusters. This course explores data management within HDFS, alongside advanced applications of Pig, Hive, and HBase. The sophisticated programming strategies covered here are particularly advantageous for seasoned Hadoop developers.

Audience: developers

Duration: three days

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

Target Audience

This course aims to demystify big data and Hadoop technologies, demonstrating that they are accessible and straightforward to grasp.

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

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

• Install and configure Apache Hadoop.
• Understand the four key components of the Hadoop ecosystem: HDFS, MapReduce, YARN, and Hadoop Common.
• Utilize the Hadoop Distributed File System (HDFS) to scale a cluster to hundreds or thousands of nodes.
• Configure HDFS to serve as the storage engine for on-premise Spark deployments.
• Configure Spark to access alternative storage solutions, such as Amazon S3, and NoSQL database systems like Redis, Elasticsearch, Couchbase, Aerospike, and others.
• Perform administrative tasks, including provisioning, management, monitoring, and securing an Apache Hadoop cluster.

Apache NiFi is an open-source platform designed for flow-based data integration and event processing. It facilitates the automated, real-time routing, transformation, and mediation of data between diverse systems, supported by a web-based interface that offers granular control.

This instructor-led live training, available both onsite and remotely, is tailored for intermediate-level administrators and engineers aiming to deploy, manage, secure, and optimize NiFi dataflows within production environments.

Upon completion of this training, participants will be equipped to:

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

Format of the Course

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

Course Customization Options

• For information on arranging customized training for this course, please contact us.

In this instructor-led, live training in Italy, participants will learn the fundamentals of flow-based programming as they develop a number of demo extensions, components and processors using Apache NiFi.

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

• Understand NiFi's architecture and dataflow concepts.
• Develop extensions using NiFi and third-party APIs.
• Custom develop their own Apache Nifi processor.
• Ingest and process real-time data from disparate and uncommon file formats and data sources.

Relational databases have long been the preferred technology for storing, retrieving, and querying data. They enable users to organize information using a structured and well-defined pattern or model. While this approach is highly effective for standardized data that is understood in advance—for instance, a hospital check-in application managing patient records with consistent fields such as patient ID, first and last names, and date of the last visit—it has limitations. For organizations dealing with undefined incoming data, such as a startup's online inquiry form that constantly experiments with adding and removing fields to adapt to business needs, rigid pre-defined structures become problematic. Such scenarios require frequent redefinition of data schemas, including structures and allowed data types, before any new data can be stored.

This is where NoSQL (Not Only SQL) databases come into play. They liberate users from the need to predefine data structures, allowing for the insertion and updating of new data in real time. NoSQL databases typically offer greater speed than relational databases and can manage vast amounts of data effortlessly. Thanks to their ability to efficiently partition data across multiple servers (clusters) and balance the load, they also scale more effectively. Additionally, NoSQL databases integrate particularly well with applications supporting real-time analytics, site personalization, IoT, and mobile platforms.

In this instructor-led live training, participants will gain a comprehensive understanding of the architecture, design principles, and functionality of the most popular NoSQL databases. Through a live lab environment, participants will set up, operate, and assess various NoSQL databases. The primary goal is to empower participants to intelligently evaluate, propose, and implement a suitable NoSQL database solution within their organization.

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

• Install and configure various types of NoSQL databases, including MongoDB, Cassandra, Redis, and Neo4j
• Evaluate the benefits and disadvantages of NoSQL databases compared to relational databases
• Understand the underlying data formats used by NoSQL databases and how to leverage these formats when developing modern applications (desktop, mobile, cloud, IoT)
• Perform create, insert, update, and delete operations within a NoSQL database
• Set up a hybrid environment where relational and NoSQL databases work in tandem
• Configure a NoSQL database cluster to distribute the processing of large datasets
• Understand the security implications of using NoSQL databases
• Deploy and scale a NoSQL database in a production environment

Audience

• Database professionals
• Data architects
• Data strategists
• Project managers
• Application developers seeking to integrate a flexible database solution into their applications

Format of the Course

• A mix of lectures, discussions, exercises, and extensive hands-on practice

Note

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

redis

nosql

Scylla is an open-source, distributed NoSQL database that offers compatibility with Apache Cassandra while delivering significantly higher throughput and lower latency.

This course provides participants with a comprehensive understanding of Scylla’s features and architecture, alongside hands-on experience in setting up, administering, monitoring, and troubleshooting the system.

Target Audience

• Database Administrators
• Developers
• System Engineers

Course Format

• The course is interactive, featuring discussions on the principles and strategies for deploying and managing Scylla distributed databases and clusters.
• It includes extensive hands-on exercises and practical training.