Right Time For You To Learn The Essentials Of Hadoop
With the growing importance of Hadoop, it is just the right time to add this skill to your resume. If you want to bag a better job, wait no further and consider learning Hadoop from a reliable source. There are some accredited institutions, offering aspirants with the latest norms and rules of Hadoop industry. It will not take long before you become a part of this sector. Some integrated facts and figures will help you to know more about the reasons, behind growing importance of Hadoop, these days.
Rise in Big data:
You cannot afford to miss out the growth in Big data, in recent times! Recent statistics from International Data Corporation have indicated that by the end of 2020, the number of Hadoop will reach to 40 Zettabytes. On the other hand, the information is being doubled every year. It means, by the end of 2020, there will be nearly 5200 GB of data, for a single person. Moreover, as the application of Big data is used in various systems, therefore; you cannot afford to miss out the importance of Hadoop.
Some basic examples to follow:
You might have heard a lot of auto-tagging feature in some of the social networking sites. Moreover, you cannot miss out the importance of surveillance cameras, which are used for generating impeccable images in low lights. All these are parts of Hadoop and some of the amazing abilities, which this segment holds. It helps in not just storing or processing data, but also used in retrieving data from this source. You can store data using a technique, but processing and even querying it can be a different story, altogether. For adding more power to Big Data, Hadoop seems to be the only option left.
Importance of Hadoop in social networking sites:
Nowadays, Facebook is considered the king of social networking sites. To add more value to this site, Hadoop is used. It is used for storing information about any person or points, within the same date and time of any activity on the profile. All these relevant information is termed as Big data and without Hadoop, it becomes really difficult to handle these situations.
The software development companies are now working hard to deal with the latest versions of Hadoop data storage services. During general instances, Hadoop data is mainly stored on HDFS, also termed as Hadoop Distributed File System. It houses both unstructured and structured data. There are some other competitors, who can also store structured data, but cannot afford to work on unstructured options. Therefore, Hadoop is considered as the best option for most of the users. It helps in processing data, whereas; the RDBMS helps in transferring the data over a network, with the help of I/O, for processing old data.
Predicting the outcome of the situation:
While you are working on Hadoop, there are certain questions, popping up in your mind. Can Hadoop be used to predict outcomes of situations in near future? Well, yes, it can, especially if the situation is mainly based on the current dataset. Online graphs are available to show exponential data growth over the period. A clearer look will help you to know that unstructured data is covering nearly 90% of global data. The more unstructured data is used, the higher will be the need of professionals. Therefore, if you want to bag a job within this sector to earn good money, you should start it right now!
Effectiveness of Hadoop in real life:
If you start browsing through the internet, you might come across two important names in this sector; Hadoop and RDBMS. Hadoop can turn out to be a straight winner and can knock others away from this section.
• RDBMS is quite worthwhile dealing with data management, but cannot manage if the numbers exceed few hundred sheets. Therefore, if you need to maintain 1000 sheets and even more than that, Hadoop is the only option left.
• When it comes to social networking websites, you cannot afford to store the valid information of FB user in excel. It is hard to store their historical data, which can date back to years. With the help of Hadoop, you can loosely structure your data.
• On the other hand, in RDBMS, data needs to be consistent and in a recognizable format, which makes the task more difficult. Therefore, people are inclining more towards Hadoop as the best example.
Different between Hadoop and RDBMS:
To know the importance of Hadoop, you need to compare it with RDBMS.
• In data types, Hadoop is unstructured and on multiple platforms, but RDBMS is structured
• In processing sector, Hadoop can process data, but there is a limitation with no data processing in RDBMS
• The governance remains loosely structured in Hadoop but standardized and rigid in RDBMS
• Scheme is required on read in Hadoop, but in writing in RDBMS
The Hadoop is best suited for data discovery, massive storage or processing value and in processing unstructured data, as some of the value-added options.
Hard to use Big data without Hadoop:
Without the proficient use of Hadoop, it is hard to operate Big data. As the structured data is exploding, therefore, using Hadoop is a must. Moreover, the organizations are inclining more towards fact-based decisions. The bigger data you can procure; the accurate decision will it be. Therefore, the use of big data is becoming necessary, which finally gives rise to Hadoop.
Best career options now:
With the help of Hadoop learning, you can bag the best job right now. Start as a developer or tester of Hadoop eco-system, Python, Java or even Ruby. Moreover, you can even work as a tester of NoSQL DB or Spark. Other than that, you can even try your hands in the role of administrators, in Cluster management, Linux administration, Virtualization and in Cluster Performance. The reliable aspirants can opt for the job role of Data Analyst in various MNCs. They will be judged based on machine learning, statistical skills, Expertise in R and with their knowledge in Hadoop Essentials. Therefore, for the best job, it is vital to incorporate Hadoop sessions in your learning kitty now.