Online NoSQL Training in US

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 (online or onsite) is designed for government database administrators or developers who wish to utilize Microsoft Azure Cosmos DB to develop and manage highly responsive and low-latency applications for government use. By the end of this training, participants will be able to: - Provision the necessary Cosmos DB resources required to start building databases and applications. - Scale application performance and storage by leveraging APIs in Cosmos DB. - Manage database operations and reduce costs by optimizing Cosmos DB resources for government workflows.

This course provides an introduction to HBase, a NoSQL database built on top of Hadoop. It is designed for developers who will be using HBase to build applications and administrators responsible for managing HBase clusters. The curriculum will guide developers through the architecture of HBase, data modeling, and application development. Additionally, it covers the integration of MapReduce with HBase and addresses performance optimization techniques relevant to administration. The course emphasizes practical learning with numerous hands-on lab exercises. Duration: 3 days Audience: Developers and Administrators for government use.

Relational databases have long been the preferred technology for storing, retrieving, and querying data. They enable users to organize their information using a structured, well-defined set of patterns (model). This approach is particularly effective for managing standardized and well-understood data, such as patient records in a hospital check-in application, which typically include fields like patient ID, first name, last name, and date of the last visit. However, this model has limitations, especially for organizations with less defined or evolving data requirements. For instance, an online inquiry form for a startup that is still experimenting with different data collection fields would require frequent redefinition of the data model (schema) to accommodate changes in business needs. Enter NoSQL (Not Only SQL) databases. These databases eliminate the need to predefine the structure of incoming data, allowing for dynamic insertion and updates on the fly. NoSQL databases are often faster than relational databases and can efficiently handle very large volumes of data. They also scale better due to their ability to partition data across multiple servers (cluster) and balance the load effectively. 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 a comprehensive understanding of the architecture, design principles, and functionality of popular NoSQL databases as they set up, operate, and assess various NoSQL databases in a live lab environment. The goal of this training is to equip participants with the knowledge to intelligently evaluate, propose, and implement suitable NoSQL database solutions within their organization for government. 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. - Recognize the underlying data formats used by NoSQL databases and leverage these formats for developing modern applications (desktop, mobile, cloud, IoT). - Perform create, insert, update, and delete operations in a NoSQL database. - Set up a mixed environment with both a relational database and a NoSQL database working together. - Configure a cluster of NoSQL databases to distribute the processing of very large datasets. - Understand the security implications of using a NoSQL database. - Deploy and scale a NoSQL database in a production environment. **Audience** - Database professionals - Data architects - Data strategists - Project managers - Application developers interested in integrating a flexible database solution 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.

Scylla is an open-source, high-performance NoSQL data store that is compatible with Apache Cassandra. It offers significantly higher throughput and lower latencies, making it an ideal solution for government agencies and other organizations requiring robust data management. This course is designed to provide participants with a comprehensive understanding of Scylla's features and architecture, along with practical experience in setting up, administering, monitoring, and troubleshooting Scylla environments. **Audience:** - Database Administrators - Developers - System Engineers **Format of the Course:** - The course is interactive, featuring discussions on the principles and best practices for deploying and managing Scylla distributed databases and clusters. - It includes a significant hands-on component to ensure participants gain practical skills in real-world scenarios.

Redis is an advanced key-value store that supports various data structures and is widely used for caching, messaging, and session management in diverse applications. As a NoSQL database, Redis provides high performance and scalability, making it particularly suitable for government agencies that require efficient data processing and real-time analytics to support mission-critical operations. The flexibility and robustness of Redis ensure that it can be effectively integrated into existing government IT infrastructures, enhancing data management capabilities while maintaining compliance with stringent security standards for government use.