How to Prepare for Learning Hadoop | iCert Global

Hadoop enables businesses to utilize plenty of data in order to make sound decisions and come up with new ideas. Currently, businesses produce more data than before, and therefore, businesses need individuals who can work with Hadoop.

What is Hadoop?

Hadoop is open-source software that enables the storage and processing of big data across numerous computers. It employs a paradigm known as MapReduce, which facilitates the processing of big data by breaking it into small tasks.

Hadoop has four major components:

• Hadoop Distributed File System (HDFS): It stores the data. It breaks large files into small fragments and stores them on numerous computers. Each fragment is duplicated numerous times so that the data is preserved, even if a computer crashes.

• MapReduce: That's how Hadoop handles data. First, it sorts the data in the "Map" process. Then the "Reduce" process adds up or pulls useful information out. It is rapid because it exploits many computers at the same time.

• Hadoop YARN (Yet Another Resource Negotiator): YARN is used to manage the computers in the Hadoop system. YARN makes sure that all tasks are given the appropriate amount of computer power and memory. It also enables multiple types of data to exist side by side—such as live data and stored data.

• Hadoop Common: These are the libraries and utilities that assist the other components of Hadoop. It gives the overall support and combines all the components together.

Benefits of Using Hadoop

Hadoop is an effective way to manage big data. The most significant reasons why individuals utilize it are:

• Grows with Your Data (Scalability): It is easy to add more computers to a Hadoop cluster when your data expands.

• Saves Money (Cost-Effective): Hadoop operates on basic, low-cost machines. You don't require fancy, high-end computers to implement it. Moreover, as it is free to use (open-source), you don't need to pay for a license.

• Flexible (Compatible with All Types of Data): Hadoop can process all types of data—words, images, videos, etc.

• Preserves Data Intact (Fault Tolerant): Hadoop creates duplicate copies of your data and stores them elsewhere. Therefore, even if a computer crashes, your data is still intact and the system keeps running.

• Quick and Efficient: Hadoop divides large jobs into small ones and runs them at the same time using a large number of computers.

• Holds a lot of raw data (Data Lakes): Hadoop is able to gather and store a lot of data in one location, even though you may not yet know how you will use it.

• Well-established Support System (Ecosystem)

Top Hadoop Skills

As big data keeps growing, Hadoop has become a vital resource for individuals who want to deal with large amounts of data. To understand Hadoop is to acquire a range of vital skills beyond the processing of simple data. The following are the most vital skills one needs to become a Hadoop and big data expert:

1. Hadoop Basics Understanding

Hadoop is free software that helps divide big tasks among many computers to make them faster. It keeps big files by dividing them into blocks and placing them on different computers. It then sends small pieces of code to all the computers so that they can work on their part of the data at the same time.

The two main constituents of Hadoop are:

• Hadoop Distributed File System (HDFS): It stores your data on numerous computers.

• MapReduce: This section assists in processing the data by dividing the task into pieces and running them simultaneously on other computers.

2. Hadoop Distributed File System (HDFS)

HDFS is Hadoop's storage mechanism. HDFS is designed to be robust and stable even in the case of low-cost computers. HDFS is suitable for applications dealing with extremely large data volumes.

3. Data Loading Tools

To utilize data in Hadoop, you must first load it into the system. That is where you need data loading tools. They assist you in loading data into HDFS or tools such as Hive and HBase.

Two popular tools are:

• Sqoop: Imports bulk data from regular databases into Hadoop.

• Flume: Gathers and shoves log information (e.g., from sites or servers) into HDFS.

4. HiveQL

HiveQL is a proprietary language that is utilized to query (termed as queries) in Apache Hive, a utility to facilitate working with data stored in Hadoop. HiveQL is very similar to SQL, the language utilized in conventional databases.

Although Hive runs on Hadoop, you do not need to write complex code. You can simply write simple HiveQL queries, and Hive will convert them into MapReduce jobs in the background. HiveQL also supports more complex data types such as lists and objects so that it can handle dirty or big data sets.

5. Apache HBase

HBase is a special kind of database that is HDFS-based. It is used to handle extremely large tables with millions of columns and billions of rows. HBase keeps data in columns rather than rows and is extremely simple to scale by just adding more machines.

Significance of Hadoop Skills

Information is growing faster today than ever before. Companies require smart means of storing, processing, and interpreting the data. Hadoop contributes to giving a strong foundation to big data. That is why it is essential to learn Hadoop:

• Working with Big Data: Hadoop is able to work with lots of data on many computers. Companies with petabytes of data find this useful. People who know Hadoop help with these large collections of data.

• Cost-Effective Expansion: With Hadoop, businesses are able to expand their data storage and processing capacity without breaking the bank. Individuals who understand Hadoop can help businesses expand their systems without exceeding their budget.

• Processing Any Type of Data: Hadoop can process any form of data, whether structured (such as numbers) or unstructured (such as images or text). This enables companies to comprehend and leverage various forms of data in a bid to make informed decisions.

• Data Security: The more companies are getting hacked, the more critical it is to safeguard data. Hadoop's security is good, and those who are able to use it can secure data and keep it confidential.

• Leveraging New Ideas: Hadoop also has other powerful tools (such as Apache Spark, Hive, and Pig) that enable individuals to analyze data in improved manners, even immediately. This might guide companies to make good choices and explore new business plans.

Career Development Prospects with Hadoop

Learning Hadoop and big data skills can open many great career doors. Because businesses create more data, they need people who can handle big, complicated datasets and deliver valuable information. That is how having Hadoop in your arsenal can propel your career:

1. Data Scientist

Hadoop professionals are highly sought-after data scientists. They use Hadoop to work with huge sets of data and use statistical models to find patterns, make predictions, and deliver meaningful information. Such a role generally requires proficiency in machine learning and data mining.

2. Big Data Engineer

Big data engineers create and manage data systems that handle big data, like Hadoop. They enable the unrestricted flow of data between systems so that businesses can analyze data efficiently.

3. Data Analyst

Data analysts use Hadoop to navigate through data and generate reports, visualizations, and business intelligence. They typically employ tools such as Hive or Pig to pose questions to large datasets and provide insightful data analysis.

4. Machine Learning Engineer

Big data, processed using Hadoop, is employed by machine learning engineers to train models and build data-driven decision systems. Huge quantities of data are processed and stored by Hadoop, making it a very valuable tool for machine learning practitioners.

5. Hadoop Developer

Hadoop developers develop applications to run data using Hadoop. They should be able to code in Java, Python, or Scala and understand the key parts of Hadoop.

Improving Your Career

To enhance your career in Hadoop, it's also necessary to pay attention to other aspects:

• Soft Skills: Communication, leadership, and project management skills are extremely important when you assume senior positions.

• Certifications: Hadoop and associated technologies certifications are helpful in proving your expertise and standing out in the job market.

How to obtain  Hadoop certification? 

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Conclusion

To be well-versed in Hadoop, one needs a number of skills like programming, data analysis, problem-solving, and communication. By learning these skills, one can fully utilize all the strengths of Hadoop's system and become highly valuable in the fast-growing field of big data analysis.

iCert Global provides a great Post Graduate Program in Data Engineering for people who want to start this valuable learning experience. This detailed course includes everything about Hadoop, like HDFS, MapReduce, YARN, Hive, Pig, Spark, and more. With practical projects, real-life examples, and expert help, learners get hands-on experience and build confidence in using Hadoop for big data solutions.

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