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Building Enterprise Solutions with MongoDB



Course Number



4 Days

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Table-based databases struggle to cope with an ever-growing variety of data, whereas the document-oriented nature of MongoDB allows developers to quickly build highly scalable applications. In this big data training course, you will gain the skills to develop, administer, secure, and scale MongoDB-based applications, and acquire low-cost, data-driven applications with MongoDB as the back-end database.

You Will Learn How To

  • Develop highly scalable and cost-efficient applications with MongoDB
  • Build efficient MongoDB data models for enterprise-scale applications
  • Enhance performance with indexing and sharding
  • Manage consistency with write concern and read preference
  • Process data and compute results with aggregation pipelines and MapReduce

Important Course Information

  • Recommended Experience

    • Knowledge of databases and SQL
    • Java programming

Course Outline

  • Setting the Stage

Recognizing the need for NoSQL data stores

  • Justifying non-relational data stores
  • Listing the categories of NoSQL Data Stores

Focusing on MongoDB

  • Defining the MongoDB architecture
  • Reviewing the JSON standard
  • Enumerating the MongoDB data types

Interacting with MongoDB

  • Querying at the Command Line Interface
  • Running Scripts
  • Manipulating MongoDB data from Python and Java
  • Installing MongoDB

Surveying Cluster Topology

  • Creating a standalone mongod
  • Achieving redundancy with replica sets
  • Replicating data with the oplog

Dissecting MongoDB Storage Strategies

  • Identifying storage engines
  • Improving data safety with journaling
  • Investigating record allocation strategies

Storing Large Files with GridFS

  • Weighing the advantages and disadvantages of GridFS
  • Leveraging the mongofiles utility tool
  • Compressing data for economy of drive space
  • Exploring the MongoDB Data and Query Model

Organizing Data

  • Storing data in Databases, collections and documents
  • Inserting and updating Documents
  • Running scripts from the Mongo Shell

Querying Documents

  • Restricting find() with a query document
  • Specifying keys for queries to return
  • Constraining the number of results with limit and skip

Modeling Relationships

  • Express relationships using references
  • Embedding sub-documents
  • Configuring Replication and Data Consistency

Configuring Read and Write Consistency

  • Reading from primary and secondary nodes
  • Setting the read preference level
  • Selecting the Appropriate Write Concern
  • Writing with a timeout

Customizing Write Concern and Read Preference

  • Applying tags to replicas
  • Adding logical names to write concerns
  • Reading from a tagged mongod
  • Tuning Performance with Indexes

Improving access speed with indexes

  • Investigating a query with the explain() function
  • Getting statistics from explain()
  • Choosing an index with the hint() function

Considering the cost and benefit of indexing

  • Designing a better index
  • Opting out of using an index
  • Profiling to identify slow queries

Taking advantage of indexes

  • Sorting and finding ranges with an index
  • Guaranteeing uniqueness with indexes
  • Skipping missing fields with a sparse index

Managing collections with special indexes

  • Aging data out of a capped collection
  • Searching for text fragments with $text
  • Deleting documents automatically using time to live indexes
  • Permitting queries by location
  • Utilizing the Aggregation Framework

Leveraging the different modes of the Aggregation Framework

  • Invoking single-purpose aggregation functions
  • Performing operations with the Aggregation Pipeline framework
  • Executing MapReduce on MongoDB
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Convenient Ways to Attend This Instructor-Led Course

Hassle-Free Enrolment: No advance payment required to reserve your seat.
Tuition due 30 days after you attend your course.

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Tuition — Standard: $3285   Government: $2890

Aug 13 - 16 ( 4 Days)
9:00 AM - 4:30 PM EDT
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Oct 8 - 11 ( 4 Days)
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Feb 11 - 14 ( 4 Days)
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Apr 7 - 10 ( 4 Days)
9:00 AM - 4:30 PM EDT
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Course Tuition Includes:

After-Course Instructor Coaching
When you return to work, you are entitled to schedule a free coaching session with your instructor for help and guidance as you apply your new skills.

After-Course Computing Sandbox
You'll be given remote access to a preconfigured virtual machine for you to redo your hands-on exercises, develop/test new code, and experiment with the same software used in your course.

Free Course Exam
You can take your Learning Tree course exam on the last day of your course or online any time after class.


Training Hours

Standard Course Hours: 9:00 am – 4:30 pm
*Informal discussion with instructor about your projects or areas of special interest: 4:30 pm – 5:30 pm

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