Advance Your Big Data Career with Best MongoDB Certifications

Author Image

Vrutti Tanna

06 June 2023

Add To Wishlist

Advance Your Big Data Career with Best MongoDB Certifications

Big Data career is one of the most rewarding. Find out more about the Big Data industry and how to break into it with the help of MongoDB certifications.

Features

Table of Contents

  • Description

  • Growth in Big Data

  • Importance of Big Data Certification for Advancement in Career

  • Top 5 Best MongoDB Certifications on Careervira

  • Job Opportunities Post Completion of All Above Certificates

  • Conclusion

Big Data career is one of the most rewarding. Find out more about the Big Data industry and how to break into it with the help of MongoDB certifications.

Description

Big data refers to massive and complex data sets that are challenging to manage or analyze using traditional data processing techniques. The importance of big data arises from its ability to provide important insights and guide decision-making processes across a wide range of industries, including industry, healthcare, research, and government. Big data careers are abundant in today's data-driven world, with the demand for skilled professionals exceeding supply. In this article, we will talk about all necessary details required for starting a career in Big Data, and various MongoDB certifications that help in this career.

Here are some of the most important big data applications:

  • Big data provides valuable insights that may be utilized to inform better decision-making. Organizations may uncover patterns and trends in massive amounts of data and make intelligent decisions based on the insights gained from data analysis.
     
  • Big data may help businesses understand consumer behavior and preferences, allowing them to customize their offerings and increase customer satisfaction.
     
  • Big data may help businesses uncover places where they can save expenses and enhance operations. By studying operational efficiency data, businesses may identify areas for development and reduce waste.
     
  • Big data may be used to examine patient data, identify trends in disease outbreaks, and steer healthcare policy, all of which lead to better healthcare outcomes. This can lead to improved healthcare outcomes and patient care. 
     
  • Big data may be used in scientific research to uncover new insights, produce new ideas, and put theories to the test. This has the potential to lead to new scientific discoveries and achievements.

Big data has the potential to transform many industries and spur innovation. Using the power of big data, organizations may get considerable insights for enhanced decision-making, operational efficiency, and customer experience. With its immense potential and exciting prospects, big data is definitely a good career choice for those with a passion for data analytics and problem-solving.

Growth in Big Data

Big data growth has been exponential in recent years, and it shows no signs of slowing down anytime soon. This also increases the number of individuals interested in making it big in Big Data.

The importance of Big Data lies in its ability to help organizations make better decisions, gain valuable insights, and drive business growth. Several causes have led to its expansion:

  • Increase in Data Generation
    As digital technologies and the Internet of Things (IoT) proliferate, more and more data is created every day. From social media posts to sensor readings from linked gadgets, a vast quantity of data is continually being created.
     
  • Data Storage and Processing Advancements
    The advent of cloud computing and big data technologies has made it easier and less expensive to store and process enormous volumes of data. This has resulted in the development of gigantic data warehouses, as well as the capacity to analyze large data sets in real-time.
     
  • The Importance of Data-Driven Decision-Making
    Organizations are recognizing the importance of data-driven decision-making and are investing in big data analytics to gather insights that may shape their plans. As a result, there is a greater need for big data analytics tools and services.
     
  • AI and Machine Learning
    To learn and increase their accuracy, AI and machine learning algorithms require huge volumes of data. As a result, the rise of AI and machine learning has aided the rise of big data.
     
  • Integration with Business operations
    Big data is no longer considered as a separate project but rather as an essential component of business operations. It is being incorporated into numerous sectors, such as marketing, supply chain, and customer service, propelling the industry forward.

Overall, technical developments, greater data collection, and the necessity of data-driven decision-making have all contributed to the emergence of big data. Big data is projected to play an increasingly crucial role in determining the future of numerous businesses as it continues to expand and innovate in this field. In today's digital age, the need for big data has become increasingly important as organizations collect vast amounts of data from various sources.

Big data growth has been exponential in recent years, and it shows no signs of slowing down anytime soon. This also increases the number of individuals interested in making it big in Big Data.

The importance of Big Data lies in its ability to help organizations make better decisions, gain valuable insights, and drive business growth. Several causes have led to its expansion:

  • Increase in Data Generation
    As digital technologies and the Internet of Things (IoT) proliferate, more and more data is created every day. From social media posts to sensor readings from linked gadgets, a vast quantity of data is continually being created.
     
  • Data Storage and Processing Advancements
    The advent of cloud computing and big data technologies has made it easier and less expensive to store and process enormous volumes of data. This has resulted in the development of gigantic data warehouses, as well as the capacity to analyze large data sets in real-time.
     
  • The Importance of Data-Driven Decision-Making
    Organizations are recognizing the importance of data-driven decision-making and are investing in big data analytics to gather insights that may shape their plans. As a result, there is a greater need for big data analytics tools and services.
     
  • AI and Machine Learning
    To learn and increase their accuracy, AI and machine learning algorithms require huge volumes of data. As a result, the rise of AI and machine learning has aided the rise of big data.
     
  • Integration with Business operations
    Big data is no longer considered as a separate project but rather as an essential component of business operations. It is being incorporated into numerous sectors, such as marketing, supply chain, and customer service, propelling the industry forward.

Overall, technical developments, greater data collection, and the necessity of data-driven decision-making have all contributed to the emergence of big data. Big data is projected to play an increasingly crucial role in determining the future of numerous businesses as it continues to expand and innovate in this field. In today's digital age, the need for big data has become increasingly important as organizations collect vast amounts of data from various sources.

Importance of Big Data Certification for Advancement in Career

Big data is a powerful tool that can help organizations improve customer experiences, optimize operations, and uncover new business opportunities, highlighting its importance in today's business landscape. Big data certification is crucial for professional progression since it displays a high degree of experience and understanding in the field of big data.

Here are some of the primary advantages of obtaining a big data certification:

  • Recognition of Competence
    A big data certification shows companies that a person has the requisite abilities and competence to work with big data technology, which may lead to more career prospects and greater pay.
     
  • Career Advancement
    Earning a big data certification may help people stand out from their colleagues and qualify for higher-level jobs like data analyst, data scientist, or big data engineer.
     
  • Continued Learning
    Big data certifications encourage individuals to keep current on the newest innovations and technology in the field of big data, which may assist individuals in remaining relevant in their employment and continuing to learn and grow.

According to the IT skills and salary report 2022, Big data certification is amongst the top paying certifications with a salary of around $134,793, and it is the hardest position to fill with a vacancy of about 28%. Furthermore, the survey discovered that qualified IT experts earn more than non-certified specialists.

It is safe to argue that possessing a certification gives people an advantage over others who do not. With the growing need for big data specialists, holding a certification may help people stand out and establish their knowledge in a competitive employment market.

Big data is a powerful tool that can help organizations improve customer experiences, optimize operations, and uncover new business opportunities, highlighting its importance in today's business landscape. Big data certification is crucial for professional progression since it displays a high degree of experience and understanding in the field of big data.

Here are some of the primary advantages of obtaining a big data certification:

  • Recognition of Competence
    A big data certification shows companies that a person has the requisite abilities and competence to work with big data technology, which may lead to more career prospects and greater pay.
     
  • Career Advancement
    Earning a big data certification may help people stand out from their colleagues and qualify for higher-level jobs like data analyst, data scientist, or big data engineer.
     
  • Continued Learning
    Big data certifications encourage individuals to keep current on the newest innovations and technology in the field of big data, which may assist individuals in remaining relevant in their employment and continuing to learn and grow.

According to the IT skills and salary report 2022, Big data certification is amongst the top paying certifications with a salary of around $134,793, and it is the hardest position to fill with a vacancy of about 28%. Furthermore, the survey discovered that qualified IT experts earn more than non-certified specialists.

It is safe to argue that possessing a certification gives people an advantage over others who do not. With the growing need for big data specialists, holding a certification may help people stand out and establish their knowledge in a competitive employment market.

Top 5 Best MongoDB Certifications on Careervira

Acquiring MongoDB skills has many benefits for Big Data professionals, one of which includes competitive salary benefits. Take a look at these MongoDB certifications on Careervira for Big Data Career Opportunities.

MongoDB Certification Training Course by Edureka

  • Overview
    MongoDB is used for storing and managing large volumes of unstructured or semi-structured data, such as social media posts, sensor data, and product catalogs. MongoDB is, at its heart, a distributed database. Thus high availability, horizontal scaling, and global dispersion are all built-in and simple to use. Using real-life case studies, this program will help you grasp the premier document-oriented NoSQL database, MongoDB Architecture, CRUD, Schema Design, Data Modelling, and Indexing. MongoDB careers offer exciting opportunities for professionals looking to work with cutting-edge technology that is rapidly gaining popularity in the industry. 
     
  • Why we have chosen it
    There is no prerequisite for this course, and the duration is 5 weeks with lifetime access. The cost is $356.

    It includes following chapters
    • Introduction to MongoDB - Architecture and Installation
    • Schema Design and Data Modelling
    • CRUD Operations
    • Indexing and Aggregation Framework
    • MongoDB Administration
    • Scalability and Availability
    • MongoDB Security
    • Application Engineering and MongoDB Tools
    • MongoDB on the Cloud
    • Diagnostics and Fixes
       
  • Importance, Relevance, and Future of this Certificate
    Edureka's MongoDB Certification Training Course may be quite advantageous for students seeking to create professions in database management and development. The course covers all aspects of MongoDB, including its architecture, data modeling, indexing, and aggregation framework, as well as advanced subjects like replication, sharding, and security.

    This certification training course's value in today's work economy cannot be emphasized. MongoDB is one of the most prominent NoSQL databases in use today, and there is an increasing demand for MongoDB expertise. In a competitive employment market, the certification can help you stand out and demonstrate your skills to potential employers.

    MongoDB's future prospects are promising as more firms use NoSQL databases for their scalability and flexibility. According to a Digital Journal report, the NoSQL database market accounted for $5.7 billion in sales globally in 2021. Over the next six years, the group said the NoSQL market would increase to $29.3 billion, representing a compounded annual growth rate (CAGR) of 31.3%, and MongoDB remains the most used NoSQL database. This points to increased demand for MongoDB specialists in the coming years. MongoDB projects can range from small-scale applications to enterprise-level solutions that require advanced data modeling and management capabilities.

    The importance of MongoDB certification training is set to expand in the next years, as organizations increasingly rely on NoSQL databases for data management. Furthermore, as the MongoDB database evolves and new features are added, experts will need to keep up with the current advances in order to remain competitive in the job market. The certification training can assist you in staying current with MongoDB and positioning yourself for career success.

 

Data Wrangling with MongoDB by Udacity

  • Overview
    In this course, we'll look at how to get data from various sources and shape it so that it can be used in data-driven applications. Some data scientists devote the majority of their time on this! 

    Students will learn how to collect and extract data from common data types. They will learn how to analyze data quality and best practises for data cleansing. We will also introduce students to MongoDB, covering the fundamentals of data storage as well as the MongoDB query language, as well as exploratory analysis utilizing the MongoDB aggregation architecture. 

    This is an excellent course for people seeking entry-level data science careers, as well as current business/data analysts hoping to expand their knowledge of big data, and managers working with data professionals or looking to exploit big data.

    This course is also part of Nanodegree in Data Analyst.
     
  • Why we have chosen it
    The course duration is 2 months and is totally free and self-paced, but the prerequisite for this course is programming experience in Python and the ability to perform rudimentary system administrator on Windows or UNIX.

    The syllabus consists of following
    • Data Extraction Fundamentals
      • Data Quality Assessment, Introduction to Tabular Formats, CSV Parsing
    • Data in More Complex Formats
      • XML Design Principles,Parsing XML,Web Scraping
    • Data Quality
      • Sources of Dirty Data, A Cleaning Plan, and Data Auditing
    • Working with MongoDB
      • Data Modelling in MongoDB, PyMongo Introduction, Field Queries
    • Analyzing Data
      • Aggregation Framework Examples, The Aggregation Pipeline, and Aggregation Operators: $project, $match $group, $unwind
    • Case Study - OpenStreetMap Data
      • For huge datafiles, repeated parsing is used.Overview of OpenStreetMap XML, Exercising with OpenStreetMap data
         
  • Importance, Relevance, and Future of this Certificate
    Data Wrangling with MongoDB is a necessary ability in today's data professional job market. As data gets more complex and diverse, the capacity to handle and analyse huge amounts of data efficiently and effectively has become increasingly vital. MongoDB is a popular NoSQL database, and its flexibility and scalability make it an effective data wrangler. MongoDB is a NoSQL document-oriented database that is widely used in web applications, mobile applications, and Big Data solutions due to its scalability and flexibility.

    Udacity's Data Wrangling with MongoDB course gives a thorough overview of MongoDB's data wrangling features, such as data cleansing, data transformation, and data aggregation. It also covers advanced subjects like indexing and data modeling, which are critical for effective data processing.

    The growing demand for data professionals skilled in MongoDB highlights the importance of mastering Data Wrangling with MongoDB in today's job market. With the ever-increasing amount of raw data being generated, it is not surprising that employers are placing greater emphasis on data transformation capabilities. In fact, the demand for data wrangling skills has risen by 405% in 2022, placing it at the top of the list of fastest-growing technical skills. This trend indicates a rising need for MongoDB experts who possess strong data-wrangling abilities.

    The importance of Data Wrangling with MongoDB is projected to expand even more in the future years as organizations continue to utilize NoSQL databases for their data management needs. As data gets increasingly complex and diverse, the ability to manage and analyze huge amounts of data efficiently and effectively will remain a vital talent for data professionals. 

    To summarise, Data Wrangling with MongoDB is a necessary talent for data professionals in today's employment market, and its future prospects are bright. Udacity's course can help you build the skills and knowledge required to excel in your job and keep ahead of the curve as the area of data management evolves.

 

Introduction to MongoDB in Python by DataCamp

  • Overview
    Learn how to use MongoDB to alter and analyse flexible structured data. MongoDB is a database that allows you to examine data in any way you choose. As a NoSQL database, it does not adhere to SQL's rigid relational structure. It reduces complexity by giving features that would otherwise require additional layers to SQL.

    With dynamic schema, you may handle disparate data sets and consolidate insights. MongoDB's versatility allows you to keep developing and fixing problems as your needs change. This course will teach you the MongoDB language and how to use it for search and analytics. You will investigate and answer questions regarding Nobel Laureates and prizes using raw data from the official nobelprize.org API.
     
  • Why we have chosen it
    This course is beginner friendly and completely free, with duration of 4 hours and self-paced which only requires some prerequisite knowledge in Python data science toolbox and some understanding around data types for data science in python.

    The syllabus consists of the following chapters
    • Flexibly structured data
      This chapter is about having a bird's-eye view of the structure of the Nobel Prize data. MongoDB documents, collections, and databases will be linked to JSON and Python types. Substructure will then be explored using filters, operators, and dot notation.
       
    • Working with unique values and sets
      You can now see the data's structure. This chapter will introduce you to the pools of values for various fields. You will gather different values, test for set membership, and match values to patterns.
       
    • Get only what you need and fast
      You can now easily query collections and gather documents for Python to study and analyse. However, for huge collections and papers, this approach can be time-consuming and onerous. This chapter discusses numerous methods for expediting and simplifying that procedure.
       
    • Aggregation pipelines: let the server do it For You
      You've sped up data retrieval by using projection, sorting, indexing, and limitations. However, your analytical pipelines still have unpleasant performance constraints. You still need to retrieve a large amount of data. As a result, network bandwidth, downstream processing, and memory capacity continue to have an influence on performance. This chapter discusses utilising MongoDB to execute aggregations on the server for you.
       
  • Importance, Relevance, and Future of this Certificate
    In today's work market, data experts who are fluent in both MongoDB and Python are in high demand. Due to its scalability and versatility, MongoDB is extensively used across numerous sectors, and Python is a popular programming language for data analysis, making the combination of the two a formidable tool for data professionals.

    The future prospects for the Introduction to MongoDB in Python certificate are bright, as businesses increasingly rely on NoSQL databases for data management and Python remains a popular programming language for data analysis. In fact, MongoDB software engineers can earn an average salary of RS 15,11,111 in India and $1,40,568 in the USA, according to Glassdoor. This trend demonstrates a rising need for data professionals who possess both MongoDB and Python skills, making the certificate program a valuable asset in today's job market.

    The importance of the Introduction to MongoDB in Python certificate is projected to expand in the future years as the usage of NoSQL databases and the Python programming language in data management and analysis becomes more widespread. As a consequence, having this degree may assist data professionals to differentiate themselves in a competitive job market and demonstrate their knowledge to potential employers.

    Finally, the DataCamp Introduction to MongoDB in Python certificate is a must-have for data professionals seeking a career in database management and analysis. Its prospects for the future are excellent, and it is expected to stay relevant and in demand in the coming years.

 

Introduction to Mongoose for Node.js and MongoDB by Pluralsight

  • Overview
    Mongoose is an open-source Node.js library that offers object modeling and structure to MongoDB application data. Developers will learn how to include schema, models, and validation into their applications in this course.
     
  • Why we have chosen it
    You may learn how to include schema, models, and validation into your apps by using Mongoose, an open-source Node.js package. Fundamentals of Mongoose for Node and MongoDB will provide you a solid basis on which to build and become adept in designing apps that utilise Mongoose to connect with MongoDB. First, you'll learn how to create a Mongoose schema and a model based on that schema. Following that, you'll learn about the link between a Mongoose model and its document instance, as well as how to query for data using a range of helper methods and query conditions. Finally, you'll look at how to use built-in and custom validators to ensure that data provided to the database is correct. 

    When you finish this course, you will have mongoose skills and knowledge. JavaScript is required to begin developing your own Express API services to store and retrieve data from MongoDB using Mongoose. This is a self paced course for intermediate level with only $25/month and duration of 101 minutes.

    It covers the following topics
    • Overview of the Course
    • Introduction to the Course
    • Configuring the Demo Application
    • Installing MongoDB and Creating the Mongoose Schema
    • Making a Model
    • Using Validation Middleware, Retrieve Data Using Queries
    • Next steps
       
  • Importance, Relevance, and Future of this Certificate
    In today's employment market, data experts who are fluent in both Node.js and MongoDB are in high demand. Node.js is a popular runtime environment for developing scalable, high-performance applications, and MongoDB is a popular database for data storage and administration. Mongoose, as a Node.js and MongoDB-specific library, enables data professionals to utilize the capabilities of both technologies to create powerful, efficient applications.

    The future of the Introduction to Mongoose for Node.js and MongoDB credential looks bright as organizations continue to depend on Node.js and MongoDB for data management and application development. A report by SimilarTech highlights that Node.js is widely adopted by top companies like Twitter and Nike, and the leading countries that use Node.js are the USA, followed by Russia and India.

    Finally, the Pluralsight Introduction to Mongoose for Node.js and MongoDB credential is a significant asset for data professionals pursuing a career in application development and database administration. Its prospects for the future are excellent, and it is expected to stay relevant and in demand in the coming years.



CRUD Operations using MongoDB NoSQL by Coursera

  • Overview
    NoSQL databases, such as MongoDB, store data as collections of fields rather than rows and columns, as opposed to relational databases. It replicates how humans conceive of things and provides a seamless interface for object-oriented applications. Each 'object' is kept in a data structure called a Document in JSON format. For example, the Document may represent a single word and its meaning. A Document is kept in a Collection, which may include one or more Documents. The MongoDB database then includes one or more Collections.
     
  • Why we have chosen it
    In this course, you will develop a MongoDB database collection containing words and their meanings. You will next obtain data from the collection, update data, delete document data from the collection, and ultimately delete a document, a collection, and a database.

    The duration of the course is 1 hour for only $9 and is beginner friendly with self-pace teaching.

    It covers the following topics from the syllabus : 
    • Overview of MongoDB structure and MongoDB database
    • Use insert to import from a csv file to populate MongoDB collections
    • Read or query the collection using find with query parameters
    • Update one or many MongoDB documents in collection 
    • Delete a document in MongoDB collection and drop database
       
  • Importance, Relevance, and Future of this Certificate
    Because of its versatility, scalability, and ease of use, MongoDB is extensively utilized in today's market, and skill in CRUD operations is crucial for good data management. Furthermore, as firms handle more complex and diverse data sets, the ability to operate with NoSQL databases is becoming increasingly vital. In terms of future prospects, the significance of CRUD Operations utilizing MongoDB NoSQL is likely to expand as more businesses use NoSQL databases and require qualified employees to handle their data. The need for data experts with MongoDB abilities is currently strong, and it is expected to expand more in the future years.

    As previously mentioned, the strong demand for professionals with MongoDB skills underscores the value of holding the Certificate in CRUD Operations using MongoDB NoSQL in today's job market.

    Finally, Coursera's Certificate in CRUD Operations Using MongoDB NoSQL is an important credential for data professionals looking to further their careers. Its prospects for the future are excellent, and it is expected to stay important and in-demand in the coming years as businesses continue to deploy NoSQL databases and want experienced employees to handle their data.

Acquiring MongoDB skills has many benefits for Big Data professionals, one of which includes competitive salary benefits. Take a look at these MongoDB certifications on Careervira for Big Data Career Opportunities.

MongoDB Certification Training Course by Edureka

  • Overview
    MongoDB is used for storing and managing large volumes of unstructured or semi-structured data, such as social media posts, sensor data, and product catalogs. MongoDB is, at its heart, a distributed database. Thus high availability, horizontal scaling, and global dispersion are all built-in and simple to use. Using real-life case studies, this program will help you grasp the premier document-oriented NoSQL database, MongoDB Architecture, CRUD, Schema Design, Data Modelling, and Indexing. MongoDB careers offer exciting opportunities for professionals looking to work with cutting-edge technology that is rapidly gaining popularity in the industry. 
     
  • Why we have chosen it
    There is no prerequisite for this course, and the duration is 5 weeks with lifetime access. The cost is $356.

    It includes following chapters
    • Introduction to MongoDB - Architecture and Installation
    • Schema Design and Data Modelling
    • CRUD Operations
    • Indexing and Aggregation Framework
    • MongoDB Administration
    • Scalability and Availability
    • MongoDB Security
    • Application Engineering and MongoDB Tools
    • MongoDB on the Cloud
    • Diagnostics and Fixes
       
  • Importance, Relevance, and Future of this Certificate
    Edureka's MongoDB Certification Training Course may be quite advantageous for students seeking to create professions in database management and development. The course covers all aspects of MongoDB, including its architecture, data modeling, indexing, and aggregation framework, as well as advanced subjects like replication, sharding, and security.

    This certification training course's value in today's work economy cannot be emphasized. MongoDB is one of the most prominent NoSQL databases in use today, and there is an increasing demand for MongoDB expertise. In a competitive employment market, the certification can help you stand out and demonstrate your skills to potential employers.

    MongoDB's future prospects are promising as more firms use NoSQL databases for their scalability and flexibility. According to a Digital Journal report, the NoSQL database market accounted for $5.7 billion in sales globally in 2021. Over the next six years, the group said the NoSQL market would increase to $29.3 billion, representing a compounded annual growth rate (CAGR) of 31.3%, and MongoDB remains the most used NoSQL database. This points to increased demand for MongoDB specialists in the coming years. MongoDB projects can range from small-scale applications to enterprise-level solutions that require advanced data modeling and management capabilities.

    The importance of MongoDB certification training is set to expand in the next years, as organizations increasingly rely on NoSQL databases for data management. Furthermore, as the MongoDB database evolves and new features are added, experts will need to keep up with the current advances in order to remain competitive in the job market. The certification training can assist you in staying current with MongoDB and positioning yourself for career success.

 

Data Wrangling with MongoDB by Udacity

  • Overview
    In this course, we'll look at how to get data from various sources and shape it so that it can be used in data-driven applications. Some data scientists devote the majority of their time on this! 

    Students will learn how to collect and extract data from common data types. They will learn how to analyze data quality and best practises for data cleansing. We will also introduce students to MongoDB, covering the fundamentals of data storage as well as the MongoDB query language, as well as exploratory analysis utilizing the MongoDB aggregation architecture. 

    This is an excellent course for people seeking entry-level data science careers, as well as current business/data analysts hoping to expand their knowledge of big data, and managers working with data professionals or looking to exploit big data.

    This course is also part of Nanodegree in Data Analyst.
     
  • Why we have chosen it
    The course duration is 2 months and is totally free and self-paced, but the prerequisite for this course is programming experience in Python and the ability to perform rudimentary system administrator on Windows or UNIX.

    The syllabus consists of following
    • Data Extraction Fundamentals
      • Data Quality Assessment, Introduction to Tabular Formats, CSV Parsing
    • Data in More Complex Formats
      • XML Design Principles,Parsing XML,Web Scraping
    • Data Quality
      • Sources of Dirty Data, A Cleaning Plan, and Data Auditing
    • Working with MongoDB
      • Data Modelling in MongoDB, PyMongo Introduction, Field Queries
    • Analyzing Data
      • Aggregation Framework Examples, The Aggregation Pipeline, and Aggregation Operators: $project, $match $group, $unwind
    • Case Study - OpenStreetMap Data
      • For huge datafiles, repeated parsing is used.Overview of OpenStreetMap XML, Exercising with OpenStreetMap data
         
  • Importance, Relevance, and Future of this Certificate
    Data Wrangling with MongoDB is a necessary ability in today's data professional job market. As data gets more complex and diverse, the capacity to handle and analyse huge amounts of data efficiently and effectively has become increasingly vital. MongoDB is a popular NoSQL database, and its flexibility and scalability make it an effective data wrangler. MongoDB is a NoSQL document-oriented database that is widely used in web applications, mobile applications, and Big Data solutions due to its scalability and flexibility.

    Udacity's Data Wrangling with MongoDB course gives a thorough overview of MongoDB's data wrangling features, such as data cleansing, data transformation, and data aggregation. It also covers advanced subjects like indexing and data modeling, which are critical for effective data processing.

    The growing demand for data professionals skilled in MongoDB highlights the importance of mastering Data Wrangling with MongoDB in today's job market. With the ever-increasing amount of raw data being generated, it is not surprising that employers are placing greater emphasis on data transformation capabilities. In fact, the demand for data wrangling skills has risen by 405% in 2022, placing it at the top of the list of fastest-growing technical skills. This trend indicates a rising need for MongoDB experts who possess strong data-wrangling abilities.

    The importance of Data Wrangling with MongoDB is projected to expand even more in the future years as organizations continue to utilize NoSQL databases for their data management needs. As data gets increasingly complex and diverse, the ability to manage and analyze huge amounts of data efficiently and effectively will remain a vital talent for data professionals. 

    To summarise, Data Wrangling with MongoDB is a necessary talent for data professionals in today's employment market, and its future prospects are bright. Udacity's course can help you build the skills and knowledge required to excel in your job and keep ahead of the curve as the area of data management evolves.

 

Introduction to MongoDB in Python by DataCamp

  • Overview
    Learn how to use MongoDB to alter and analyse flexible structured data. MongoDB is a database that allows you to examine data in any way you choose. As a NoSQL database, it does not adhere to SQL's rigid relational structure. It reduces complexity by giving features that would otherwise require additional layers to SQL.

    With dynamic schema, you may handle disparate data sets and consolidate insights. MongoDB's versatility allows you to keep developing and fixing problems as your needs change. This course will teach you the MongoDB language and how to use it for search and analytics. You will investigate and answer questions regarding Nobel Laureates and prizes using raw data from the official nobelprize.org API.
     
  • Why we have chosen it
    This course is beginner friendly and completely free, with duration of 4 hours and self-paced which only requires some prerequisite knowledge in Python data science toolbox and some understanding around data types for data science in python.

    The syllabus consists of the following chapters
    • Flexibly structured data
      This chapter is about having a bird's-eye view of the structure of the Nobel Prize data. MongoDB documents, collections, and databases will be linked to JSON and Python types. Substructure will then be explored using filters, operators, and dot notation.
       
    • Working with unique values and sets
      You can now see the data's structure. This chapter will introduce you to the pools of values for various fields. You will gather different values, test for set membership, and match values to patterns.
       
    • Get only what you need and fast
      You can now easily query collections and gather documents for Python to study and analyse. However, for huge collections and papers, this approach can be time-consuming and onerous. This chapter discusses numerous methods for expediting and simplifying that procedure.
       
    • Aggregation pipelines: let the server do it For You
      You've sped up data retrieval by using projection, sorting, indexing, and limitations. However, your analytical pipelines still have unpleasant performance constraints. You still need to retrieve a large amount of data. As a result, network bandwidth, downstream processing, and memory capacity continue to have an influence on performance. This chapter discusses utilising MongoDB to execute aggregations on the server for you.
       
  • Importance, Relevance, and Future of this Certificate
    In today's work market, data experts who are fluent in both MongoDB and Python are in high demand. Due to its scalability and versatility, MongoDB is extensively used across numerous sectors, and Python is a popular programming language for data analysis, making the combination of the two a formidable tool for data professionals.

    The future prospects for the Introduction to MongoDB in Python certificate are bright, as businesses increasingly rely on NoSQL databases for data management and Python remains a popular programming language for data analysis. In fact, MongoDB software engineers can earn an average salary of RS 15,11,111 in India and $1,40,568 in the USA, according to Glassdoor. This trend demonstrates a rising need for data professionals who possess both MongoDB and Python skills, making the certificate program a valuable asset in today's job market.

    The importance of the Introduction to MongoDB in Python certificate is projected to expand in the future years as the usage of NoSQL databases and the Python programming language in data management and analysis becomes more widespread. As a consequence, having this degree may assist data professionals to differentiate themselves in a competitive job market and demonstrate their knowledge to potential employers.

    Finally, the DataCamp Introduction to MongoDB in Python certificate is a must-have for data professionals seeking a career in database management and analysis. Its prospects for the future are excellent, and it is expected to stay relevant and in demand in the coming years.

 

Introduction to Mongoose for Node.js and MongoDB by Pluralsight

  • Overview
    Mongoose is an open-source Node.js library that offers object modeling and structure to MongoDB application data. Developers will learn how to include schema, models, and validation into their applications in this course.
     
  • Why we have chosen it
    You may learn how to include schema, models, and validation into your apps by using Mongoose, an open-source Node.js package. Fundamentals of Mongoose for Node and MongoDB will provide you a solid basis on which to build and become adept in designing apps that utilise Mongoose to connect with MongoDB. First, you'll learn how to create a Mongoose schema and a model based on that schema. Following that, you'll learn about the link between a Mongoose model and its document instance, as well as how to query for data using a range of helper methods and query conditions. Finally, you'll look at how to use built-in and custom validators to ensure that data provided to the database is correct. 

    When you finish this course, you will have mongoose skills and knowledge. JavaScript is required to begin developing your own Express API services to store and retrieve data from MongoDB using Mongoose. This is a self paced course for intermediate level with only $25/month and duration of 101 minutes.

    It covers the following topics
    • Overview of the Course
    • Introduction to the Course
    • Configuring the Demo Application
    • Installing MongoDB and Creating the Mongoose Schema
    • Making a Model
    • Using Validation Middleware, Retrieve Data Using Queries
    • Next steps
       
  • Importance, Relevance, and Future of this Certificate
    In today's employment market, data experts who are fluent in both Node.js and MongoDB are in high demand. Node.js is a popular runtime environment for developing scalable, high-performance applications, and MongoDB is a popular database for data storage and administration. Mongoose, as a Node.js and MongoDB-specific library, enables data professionals to utilize the capabilities of both technologies to create powerful, efficient applications.

    The future of the Introduction to Mongoose for Node.js and MongoDB credential looks bright as organizations continue to depend on Node.js and MongoDB for data management and application development. A report by SimilarTech highlights that Node.js is widely adopted by top companies like Twitter and Nike, and the leading countries that use Node.js are the USA, followed by Russia and India.

    Finally, the Pluralsight Introduction to Mongoose for Node.js and MongoDB credential is a significant asset for data professionals pursuing a career in application development and database administration. Its prospects for the future are excellent, and it is expected to stay relevant and in demand in the coming years.



CRUD Operations using MongoDB NoSQL by Coursera

  • Overview
    NoSQL databases, such as MongoDB, store data as collections of fields rather than rows and columns, as opposed to relational databases. It replicates how humans conceive of things and provides a seamless interface for object-oriented applications. Each 'object' is kept in a data structure called a Document in JSON format. For example, the Document may represent a single word and its meaning. A Document is kept in a Collection, which may include one or more Documents. The MongoDB database then includes one or more Collections.
     
  • Why we have chosen it
    In this course, you will develop a MongoDB database collection containing words and their meanings. You will next obtain data from the collection, update data, delete document data from the collection, and ultimately delete a document, a collection, and a database.

    The duration of the course is 1 hour for only $9 and is beginner friendly with self-pace teaching.

    It covers the following topics from the syllabus : 
    • Overview of MongoDB structure and MongoDB database
    • Use insert to import from a csv file to populate MongoDB collections
    • Read or query the collection using find with query parameters
    • Update one or many MongoDB documents in collection 
    • Delete a document in MongoDB collection and drop database
       
  • Importance, Relevance, and Future of this Certificate
    Because of its versatility, scalability, and ease of use, MongoDB is extensively utilized in today's market, and skill in CRUD operations is crucial for good data management. Furthermore, as firms handle more complex and diverse data sets, the ability to operate with NoSQL databases is becoming increasingly vital. In terms of future prospects, the significance of CRUD Operations utilizing MongoDB NoSQL is likely to expand as more businesses use NoSQL databases and require qualified employees to handle their data. The need for data experts with MongoDB abilities is currently strong, and it is expected to expand more in the future years.

    As previously mentioned, the strong demand for professionals with MongoDB skills underscores the value of holding the Certificate in CRUD Operations using MongoDB NoSQL in today's job market.

    Finally, Coursera's Certificate in CRUD Operations Using MongoDB NoSQL is an important credential for data professionals looking to further their careers. Its prospects for the future are excellent, and it is expected to stay important and in-demand in the coming years as businesses continue to deploy NoSQL databases and want experienced employees to handle their data.

Job Opportunities Post Completion of All Above Certificates

The need of big data analytics is crucial for organizations to effectively manage and utilize their data, enabling them to make informed decisions and stay ahead of the competition. Completing a MongoDB course or certification program can lead to a variety of professional prospects in database management and development. Here are some possible employment roles for you to consider:

  • MongoDB Developer
    You will be responsible for designing and creating MongoDB-based apps as a MongoDB Developer. You will work with MongoDB's document-based data model, design apps utilizing MongoDB's programming interfaces, and create and optimize MongoDB queries.
     
  • MongoDB Database Administrator (DBA)
    A DBA is in charge of administering and maintaining MongoDB databases. Installation, configuration, backup, recovery, and performance adjustment are all included. MongoDB DBAs also oversee the database's security and scalability.
     
  • Big Data Analyst
    A Data Analyst utilizes MongoDB to handle and analyze massive amounts of data. They create data models, extract and convert data, and provide reports and visualizations to deliver insights to stakeholders.
     
  • Full Stack Developer
    You will be responsible for creating both front-end and back-end apps utilizing MongoDB as the database. You will construct and optimize queries using MongoDB's APIs and create user interfaces using web technologies such as HTML, CSS, and JavaScript.
     
  • Solutions Architect
    A MongoDB Solutions Architect Solutions Architects collaborate with customers to build and deploy MongoDB-based solutions that satisfy their business requirements. They assess needs, design and deliver ideas and presentations, and discover technological solutions. 
     
  • Data Engineer
    As a data engineer, you will be in charge of developing and constructing data pipelines that will transmit data from multiple sources to MongoDB databases. You will also be in charge of improving the performance of data pipelines and developing data models.
     
  • DevOps Engineer
    You will be responsible for automating the deployment and administration of MongoDB databases in production settings as a DevOps engineer. You should be familiar with tools like Docker, Kubernetes, and Ansible, as well as a solid grasp of MongoDB database administration.
     
  • Project Manager
    As a project manager, you will be in charge of managing the development of projects that use MongoDB as a database. To guarantee project success, you must have expertise with project management approaches and be able to collaborate closely with developers, business stakeholders, and other team members.
     
  • Cloud Architect
    As a cloud architect, you will be in charge of creating and deploying MongoDB cloud solutions. You should be familiar with cloud systems such as AWS, Azure, or Google Cloud Platform, as well as the MongoDB database architecture.
     
  • Business Intelligence analyst
    As a business intelligence analyst, you will be responsible for analysing data contained in MongoDB databases to assist organisations in making better decisions. You should be familiar with data visualisation tools such as Tableau or Power BI, as well as the data structure of MongoDB.

The need of big data analytics is crucial for organizations to effectively manage and utilize their data, enabling them to make informed decisions and stay ahead of the competition. Completing a MongoDB course or certification program can lead to a variety of professional prospects in database management and development. Here are some possible employment roles for you to consider:

  • MongoDB Developer
    You will be responsible for designing and creating MongoDB-based apps as a MongoDB Developer. You will work with MongoDB's document-based data model, design apps utilizing MongoDB's programming interfaces, and create and optimize MongoDB queries.
     
  • MongoDB Database Administrator (DBA)
    A DBA is in charge of administering and maintaining MongoDB databases. Installation, configuration, backup, recovery, and performance adjustment are all included. MongoDB DBAs also oversee the database's security and scalability.
     
  • Big Data Analyst
    A Data Analyst utilizes MongoDB to handle and analyze massive amounts of data. They create data models, extract and convert data, and provide reports and visualizations to deliver insights to stakeholders.
     
  • Full Stack Developer
    You will be responsible for creating both front-end and back-end apps utilizing MongoDB as the database. You will construct and optimize queries using MongoDB's APIs and create user interfaces using web technologies such as HTML, CSS, and JavaScript.
     
  • Solutions Architect
    A MongoDB Solutions Architect Solutions Architects collaborate with customers to build and deploy MongoDB-based solutions that satisfy their business requirements. They assess needs, design and deliver ideas and presentations, and discover technological solutions. 
     
  • Data Engineer
    As a data engineer, you will be in charge of developing and constructing data pipelines that will transmit data from multiple sources to MongoDB databases. You will also be in charge of improving the performance of data pipelines and developing data models.
     
  • DevOps Engineer
    You will be responsible for automating the deployment and administration of MongoDB databases in production settings as a DevOps engineer. You should be familiar with tools like Docker, Kubernetes, and Ansible, as well as a solid grasp of MongoDB database administration.
     
  • Project Manager
    As a project manager, you will be in charge of managing the development of projects that use MongoDB as a database. To guarantee project success, you must have expertise with project management approaches and be able to collaborate closely with developers, business stakeholders, and other team members.
     
  • Cloud Architect
    As a cloud architect, you will be in charge of creating and deploying MongoDB cloud solutions. You should be familiar with cloud systems such as AWS, Azure, or Google Cloud Platform, as well as the MongoDB database architecture.
     
  • Business Intelligence analyst
    As a business intelligence analyst, you will be responsible for analysing data contained in MongoDB databases to assist organisations in making better decisions. You should be familiar with data visualisation tools such as Tableau or Power BI, as well as the data structure of MongoDB.

Conclusion

There is no denying that Big Data has been revolutionising industries across the world, whether it is in the field of business or science. Even the growth in this field is unnoticeable, with increasing demand for Big Data professionals all over the world.

The career opportunities in Big Data are vast, with industries ranging from finance to transportation relying on data-driven insights. More businesses are understanding the importance of data-driven insights, which will eventually increase job opportunities. If you want to excel in this field, Big Data certifications are not just helpful, but also crucial for competitive pay and position.

There is no denying that Big Data has been revolutionising industries across the world, whether it is in the field of business or science. Even the growth in this field is unnoticeable, with increasing demand for Big Data professionals all over the world.

The career opportunities in Big Data are vast, with industries ranging from finance to transportation relying on data-driven insights. More businesses are understanding the importance of data-driven insights, which will eventually increase job opportunities. If you want to excel in this field, Big Data certifications are not just helpful, but also crucial for competitive pay and position.

Features

Table of Contents

  • Description

  • Growth in Big Data

  • Importance of Big Data Certification for Advancement in Career

  • Top 5 Best MongoDB Certifications on Careervira

  • Job Opportunities Post Completion of All Above Certificates

  • Conclusion