Databases and Big Data - Training Course Package

  • ID: 3301790
  • Training
  • Packt Publishing
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This course packs forms an expert introduction to understanding key modern databases for storage, querying and processing data, whether big or small. Essential knowledge for anyone who works with processes, analyses, or manages data. 

This pack includes:

- Learning MongoDB:

Businesses now have access to more data than ever before, and a key challenge is how to ensure that data can be easily accessed and used efficiently. MongoDB makes it possible to store and process large sets of data in ways that drive up business value. The flexibility of unstructured storage, combined with robust querying and post processing functionality, make MongoDB a compelling solution for enterprise big data needs.

- Building Databases with Redis

Redis has been used as a supportive database management system for years, although it is capable of being used as a type of main storage managing data consistency and high-load resilience. It is a simple-to-use database management system with transparent data structures and commands that predict queries, and extremely fast execution time.

- Building a Search Server with ElasticSearch

As the amount of available data continues to grow worldwide, successful search experiences are increasingly becoming a major competitive advantage. The best content in the world is useless if it isn’t easy to find. Elasticsearch is a powerful and well-designed search engine used to build custom search applications that allow users to quickly find the relevant information from their application or website.

- Rapid Redis

The days of having to rely only on a SQL database are gone. Now, you have a multitude of options for your data and you need to pick the right store for the right job. You may just need a simple, easy-to-use key-value store, or perhaps a blazing fast in-memory database; in comes Redis to your rescue. There is a whole world of excited developers discussing how Redis is making their lives simpler with its lightning-fast operations on in-memory datasets.

- Building Hadoop Clusters

Hadoop is an Apache top-level project that allows the distributed processing of large data sets across clusters of computers using simple programming models. It allows you to deliver a highly available service on top of a cluster of computers, each of which may be prone to failures. While Big Data and Hadoop have seen a massive surge in popularity over the last few years, many companies still struggle with trying to set up their own computing clusters.

- Rapid Cassandra

Cassandra is the leader of the NoSQL solutions, with plenty of supporting evidence. Its decentralized, fault-tolerant, scalable, and low-cost features make it a core component of the rapidly expanding cloud computing and big data systems. The recent versions also addressed the most criticized security concern, making it suitable for use in enterprise systems.
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Learning MongoDB:

1. Getting Started
2. JSON and Data Operations
3. Working with Databases
4. MapReduce
5. The Aggregation Framework
6. SSL Security and Programmatic Access
7. Replica Sets and Scaling
8. Advanced Topics and Hosting

Building Databases with Redis:

1. Developing Our First Application Using Redis
2. Administration and Security
3. Lists and Hashes
4. Sets, Sorted Sets, and HyperLogLog
5. Publishing/Subscribing
6. Scaling and High Availability
7. Transactions and Pipelining
8. Scripting Redis

Building a Search Server with ElasticSearch:

1. Getting Started with Elasticsearch
2. Data Ingestion
3. Querying ElasticSearch
4. Connecting ElasticSearch to Our Application
5. The Advanced Search Functionality
6. Adding the Autocomplete Functionality
7. Finishing Up

Rapid Redis:

1. Understanding Redis
2. Getting Started
3. Basic Data Storage and Retrieval
4. A Node.js Application

Building Hadoop Clusters:

1. Deploying Cloud Instances for Hadoop 2.0
2. Setting Up Network and Security Settings
3. Connecting to Cloud Instances
4. Setting Up Network Connectivity and Access for Hadoop Clusters
5. Setting Up Configuration Settings across Hadoop Clusters
6. Creating a Hadoop Cluster
7. Loading and Navigating the Hadoop File System (HDFS)
8. Hadoop Tools and Processing Files

Rapid Cassandra:

1. Building the Foundation
2. Designing the Data Model
3. Developing the Application
4. Deploying to Production
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Note: Product cover images may vary from those shown