In today’s digital world, big data is one of the major areas of focus for any organization. There is an enormous amount of data that is extracted from various user touch points and stored. These data repositories contain patterns and certain usage types that speak about how users are using your company services. If used correctly, these data patterns can be a source of practical insights that directly affect the organization’s revenue.

Considering how useful this data can be, it is evident that this data shouldn’t be discarded. However, there is a requirement of a mechanism which could differentiate the useful data set from the useless one and also identify the patterns from the data repositories. To carry out these processes, various platforms are available. Among them, the most popular is Hadoop.

With Hadoop, massive amounts of data can be stored, processed and analyzed efficiently. Over the years, Hadoop has proved to be successful for the big data ecosystem. Here are five reasons why every organization should use Hadoop for its big data management.

1. Data Exploration

Data scientists love working in a flexible environment. Irrespective of the language they use, data scientists require the system with lots of memory to analyze and build models. The usual systems are not enough for data scientists to carry out their usual tasks.

Usually, software developers use the largest dataset possible for the given memory. However, with Hadoop, you can run data analysis tasks on the full datasets without sampling. You just have to write a map-reduce job, PIG or HIVE script and launch in over the full dataset on Hadoop.

2. Mining Datasets

Machine learning algorithms work best when they have large data sets and can achieve better results when they have more data to learn from, specifically from the techniques such as clustering, outlier detection and product recommenders.

In previous times, large datasets were a rare thing. They were either expensive to acquire and store. Hence, machine learning app developers were required to find innovative ways to improve data models with limited data sets. Since Hadoop provides you with scalable storage and processing power, you have the option of storing the data in a RAW format. You also have the option the full dataset to build specific and accurate data models.

3. Large Scale Pre-Processing

If you already work with the big data, you must be familiar with the fact that 80 per cent of the data science work consists of data acquisition, transformation, and feature extraction. This pre-processing converts the raw data into a consumable format for the machine-learning algorithms.

Hadoop is a perfect platform to implement pre-processing steps. It can work efficiently work over large datasets, use map-reduce or tools like PIG, HIVE and working on scripting languages like Python. If your mobile apps development includes text processing, you’ll be required to represent the data in word-vector format which you can execute successfully with the help of map-reduce and Hadoop.

4. Data Agility

Oftentimes, Hadoop is considered as a “schema on reading”, as opposed to the traditional RDBMS systems that make schema definition a prerequisite before integrating any data into them.

For Hadoop, “schema on read” brings high data agility. For example, whenever you create a new field, you won’t be required to go through a lengthy process of schema redesigning and migration of data which possibly can last months. This benefit is one of the main reason why organizations are adopting Hadoop, especially to have the same level of agility and gain competitive advantage.

5. Security & Authentication

Hadoop provides you with the capability of restricting access to only the trustworthy employees of your organizations. This ensures that you have a comprehensive security system. It employs HBase security with HDFS & MapReduce.

Security parameters like these works as a shield against threats from the outsiders and hinders the unwanted access. This ensures that organizations who use Hadoop are always safe during their operations in comparison to other enterprises who use typical security methods.

Even after all these benefits, Hadoop might not come off as a complete out-of-the-box solution for big data management. However, Hadoop is still the best and most widely used system for managing huge amounts of data especially when you are running short on time and money. Having said that, Hadoop is still likely to be the elephant in the big data room for the upcoming time.

 

Author Bio:

Eric Smith is a Senior Project Manager with Rodeo Apps, an award-winning App Development Company in Los Angeles. He is extremely passionate about converting ideas into digital products. Connect with him on Twitter @Eric_Smith09