HBase for Developers Training Course

Audience:

This course is designed for IT professionals seeking solutions for storing and processing large-scale datasets within distributed system environments.

Goal:

To provide in-depth knowledge regarding the administration of Hadoop clusters.

Big data analytics is the process of scrutinizing extensive and diverse datasets to reveal correlations, latent patterns, and other valuable insights.

The healthcare sector generates vast volumes of complex, heterogeneous medical and clinical data. Leveraging big data analytics within this domain holds immense potential for deriving insights that enhance healthcare delivery. However, the sheer scale of these datasets presents significant challenges for analysis and practical implementation in clinical environments.

Through this instructor-led, live remote training, participants will learn how to conduct big data analytics in healthcare by completing a series of hands-on live-lab exercises.

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

• Install and configure big data analytics tools, including Hadoop MapReduce and Spark
• Comprehend the characteristics of medical data
• Apply big data techniques to manage medical data
• Explore big data systems and algorithms in the context of healthcare applications

Target Audience

• Developers
• Data Scientists

Course Format

• A blend of lectures, discussions, exercises, and intensive hands-on practice.

Note

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

When conventional storage technologies struggle to manage the volume of data you require to store, hundreds of alternative options become available. This course aims to guide participants through the various alternatives for storing and analyzing Big Data, while examining their respective advantages and disadvantages.

The course primarily focuses on discussion and the presentation of solutions, although hands-on exercises can be provided upon request.

This instructor-led, live training in Serbia (online or onsite) is aimed at beginner and intermediate professionals who wish to utilize 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 Serbia (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.

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. Over the course of three days (with an optional fourth day), participants will explore the business advantages and practical applications of Hadoop and its surrounding ecosystem. The training covers essential skills such as planning cluster deployment and scaling, installing, maintaining, monitoring, troubleshooting, and optimizing Hadoop environments. Attendees will also gain hands-on experience with bulk data loading, explore various Hadoop distributions, and learn to install and manage tools within the Hadoop ecosystem. The course concludes with a session on securing clusters using Kerberos.

“…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

Format

A combination of lectures and hands-on labs, with an approximate split of 60% instruction and 40% practical lab work.

Apache Hadoop stands out as the leading framework for processing Big Data across server clusters. This course offers developers a comprehensive introduction to key components within 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 provides an in-depth exploration of data management within HDFS, alongside advanced techniques in Pig, Hive, and HBase. These sophisticated programming methods are particularly valuable for seasoned Hadoop developers.

Audience: developers

Duration: three days

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

Target Audience:

This course is designed to demystify big data and Hadoop technologies, demonstrating that these concepts are accessible and easy to grasp.

This instructor-led live training in Serbia (online or onsite) is aimed at 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 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.
• Set up HDFS to operate as storage engine for on-premise Spark deployments.
• Set up Spark to access alternative storage solutions such as Amazon S3 and NoSQL database systems such as Redis, Elasticsearch, Couchbase, Aerospike, etc.
• Carry out administrative tasks such as provisioning, management, monitoring and securing an Apache Hadoop cluster.

Informatica with Big Data (BDM) is a program aimed at empowering data professionals to develop, manage, and analyze large datasets by leveraging the most advanced technologies and architectures in the Big Data sector. The curriculum covers the entire lifecycle, from data ingestion, integration, cleansing, and curation, to data analytics and the exposure and consumption of big data services.
Participants will explore solutions that process massive datasets using Big Data technologies and architectures such as Apache Hive, Apache Hadoop, and Apache Spark. The course also offers hands-on experience with Informatica tools like Bloombox, Big Data Management, and iData Fabric to deepen your understanding of big data technologies like MapReduce and Hadoop. Upon completion, learners will be equipped to create end-to-end data solutions using Informatica and its associated Big Data offerings.

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

This instructor-led training, available both onsite and remotely, targets intermediate-level administrators and engineers looking to deploy, manage, secure, and optimize NiFi dataflows within production environments.

Upon completion of this training, participants will be capable of:

• Installing, configuring, and maintaining Apache NiFi clusters.
• Designing and managing dataflows across various sources and sinks.
• Implementing logic for flow automation, routing, and data transformation.
• Optimizing performance, monitoring operations, and troubleshooting issues.

Course Format

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

Customization Options

• For customized training tailored to your needs, please contact us to arrange.

Relational databases have long been the preferred technology for storing, retrieving, and querying data. They enable users to organize information using a structured, well-defined model. While this approach is highly effective for standardized data that is understood in advance—such as patient records in a hospital check-in application with consistent fields like ID, name, and visit date—it has limitations. For organizations dealing with unstructured or evolving data, such as a startup’s online inquiry form that frequently changes, maintaining a rigid database schema becomes challenging. Every change would require redefining the schema to accommodate new data types before storage is possible.

NoSQL (Not Only SQL) databases address this by freeing users from the need to predefine data structures. This allows for dynamic insertion and updates of data. NoSQL solutions are often faster than relational databases and can handle massive volumes of data effortlessly. Additionally, they scale more effectively by partitioning data across multiple servers (clusters) and balancing load. NoSQL databases integrate seamlessly with applications requiring real-time analytics, site personalization, IoT connectivity, and mobile support.

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

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

• Install and configure various NoSQL databases, including MongoDB, Cassandra, Redis, and Neo4j.
• Comprehend the advantages and disadvantages of NoSQL databases compared to relational databases.
• Understand the underlying data formats used by NoSQL databases and leverage them for modern application development (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.
• Grasp the security implications associated with 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 flexible database solutions

Format of the Course

• A combination 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 data store. It maintains compatibility with Apache Cassandra while delivering significantly higher throughput and lower latency.

During this course, participants will explore Scylla's features and architecture, gaining practical experience in setting up, administering, monitoring, and troubleshooting the system.

Audience

• Database administrators
• Developers
• System Engineers

Course Format

• This interactive course covers the principles and strategies for deploying and managing Scylla distributed databases and clusters.
• It features extensive hands-on exercises and practice opportunities.