Some years back, analysts used to work on simple applications or basic scripting to process and visualize data. It was possible as data in hand was in small amounts coming from a single source in the specified format. Analysts need to learn one or two tools or scripting languages to analyze the data. Storage and processing power were not critical. Expectations from stakeholders were not high, and customers were easygoing in the absence of competition.
However, the world is changing rapidly now. Customers tend to be more aggressive due to the availability of more options. Organizations are working continuously to improve product quality and enhance their customer base. Everything is moving fast and being carried out at a larger scale. Companies are collecting a lot of data from various sources in a variety of formats to stay ahead of the competition. Therefore, once sufficient applications are now not capable of handling a massive amount of complex data from different sources. For managing such data, commonly referred to as Big data, specific applications and tools are developed by experts. Big tech companies are effectively utilizing all these tools for efficient data management.
According to a report from Allied Market Research, The global market size for big data and business analytics was approximately valued at a whopping $198.08 billion in 2020, which is expected to increase to $684.12 billion by 2030, projecting growth at a CAGR of 13.5% in decade-spanning 2021 to 2030. This indeed indicates that the big data analytics field will continue hiring more professionals, particularly big data developers, data analysts, and data architects. It is simply an excellent time for upskilling in big data analytics to enter into the space, start a successful, long-lasting career.
The current article will discuss various prominent online training platforms offerings to engage one’s precious time to learn using Big Data Tools. This will help one gain the essential skills to be a valuable and successful prominent Big Data Engineer.
Big Data Hadoop Certification Training Course – Simplilearn
This course can be accessed on Simplilearn, a leading and reliable online training provider platform, to prepare one to be a successful Big Data Developer. This course is designed to master the fundamentals of the Hadoop framework, big data tools, and its methodologies. Candidates looking to opt for this course should have a fundamental knowledge of Core Java and SQL. This program is intended to enhance key skills in tools such as Hadoop, Mapreduce, PIG, Apache HIVE, NoSQL, Scala, Spark, etc. This course is preferred for candidates working in the data analytics space or willing to achieve expertise in the big data Hadoop ecosystem. Ideal candidates are professionals working or aspiring to work in roles such as developer, architects, business intelligence, and data scientists.
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Python: Big Data Analytics and Data Science – Udemy
One can opt for this course on the Udemy platform. It is intended for candidates interested in beginning their career journey in big data analytics and data science. The course spanning 10.5 hours suggests candidates have basic scripting knowledge. It covers all the essential big data tools required for handling a large volume and variety of data. Candidates will learn tools such as Apache Hadoop, Apache Spark, NoSQL, NewSQL, MongoDB, MapReduce, YARN, Hadoop ecosystem, IoT, Python modules, Twitter API, and so on. Candidates looking to work in the roles such as data analysts, azure developers, cluster administrators, and data architects are recommended to opt for this course.
The Building Blocks of Hadoop – HDFS, MapReduce, and YARN – Pluralsight
This course, available on Pluralsight.com, aims to enable candidates to develop a deep understanding of distributed computing, particularly Hadoop. An in-depth understanding of Hadoop is essential for analyzing billions of records without much difficulty. Training focuses on building blocks of the Hadoop ecosystem, including HDFS used for storage, MapReduce used for processing, and YARN used for cluster management. The course is concise, spans for 2 hours 18 minutes, yet comprehensive, which starts with an overview of complete Hadoop architecture and then motivates candidates for some hands-on work such as setting up a pseudo-distributed Hadoop environment creating and monitoring tasks. At the end of the training, learn various configuration options for stability, reliability, and optimized task scheduling on your distributed system.
Introduction to Big Data Analysis – Coursera
This specialization is available on the Coursera platform and is one of the outstanding resources to dive into Big Data Online. The specialization is offered in collaboration with the University of California San Diego. Candidates opting for this specialization will develop an understanding of big data with hands-on experience on essential tools and systems used by data experts. Candidates will gain excellent skills on MapReduce, Spark, Pig, and Hive along with predictive modeling, graph analytics, essential data exploration of large complex datasets. The complete list of courses in the specialization is listed below.
- Introduction to Big Data
- Big Data Modelling and Management Systems
- Big Data Integration and Processing
- Machine Learning with Big Data
- Graph Analytics for Big Data
- Big Data — Capstone Project
SQL on Hadoop – Analyzing Big Data with Hive – Udemy
Apache Hive is a data warehouse application for reading large files in the Apache Hadoop Distributed file system. It provides an interface similar to SQL for summarization, query, and analysis of data stored in distributed file systems. The course begins with explaining key concepts of Apache Hadoop, MapReduce and then goes into advanced Apache Hive details. This course is ideal for candidates interested in learning Hadoop, Hive, and Hive query language. Prior knowledge in big data and SQL is recommended before opting for this 4 hours 16 minutes course. Some notable topics covered in the course are creating databases and tables with HiveQL, multi inserts and dynamic partition inserts, bucket and block sampling, storage, and the ecosystem. The best thing about this course is it provides some real-world examples to demonstrate how Hive makes that task easier to accomplish.
Conclusion
With the increase in data volume and variety, Big Data analytics plays a significant role in modern times. Big Data analytics help organizations manage large amounts of data and gather insights that may do wonders for organizations. All big tech companies are using big data analytics for research and development purposes. Learning big data analytics will enhance one’s chances to land a high-paying job in big organizations. Along with a high salary, big data analytics is a highly valued and stable career option.
