‘Data is of course new oil’, especially for mobile app-enabled business owners. Data contains a few crucial information such as what a business owner sells, what people buy, who are those people, when they buy most, how they come across the sales cycle and many more. But the problem with data is ‘hidden meanings’. Without finding the ‘meaning’ from the data, a business owner can never know characteristics about his sales cycle and customers.
Luckily, there is a way to find the patterns (meanings) from the big data. For that, we first need to store the data and then process it with a few groundbreaking big data processing frameworks. Hadoop is one of those data processing frameworks which takes a large number of raw data as input and obtains meaningful relations between attributes of data, I.e, People live in A city, B neighborhood, buy C product most in D month.
Try to understand gravity here. If a business owner successfully stores the data (big data), processes that big data with the Hadoop framework and gets the critical business details, how well he can make their future decision regarding users and products?! It surely helps any business owners to double the revenue. And so does the profit and brand reputation!
Sensing the urgency, in this blog, I have covered everything about Hadoop and how an online business owner can derive many benefits from it. To make this understanding rational, I have also shared how Uber is ‘hogging’ big data and pushing the boundaries of an online business.
What is Hadoop?
In simple words, Hadoop is the ecosystem of open source projects which lets us deal with big data in a very affordable and easy way. In other words, it is a way of storing big data across distributed clusters of servers and then running analysis in each cluster to retrieve the understandable meaning from big data.
Thanks to its architecture (which we will discuss later in this blog), Hadoop is a robust, cost-effective, fast and reliable data processing framework. It even continues working even if a cluster fails.
Hadoop is open-source, yet it is a property of Apache. The first Hadoop version 0.1.0 was launched in April 2006 and the latest version of Hadoop, Apache Hadoop 3.2 was launched in January 2019. The founder of Hadoop decided to give this data processing framework name ‘Hadoop’ after a nickname of his son’s ‘Elephant toy’.
Architecture of Hadoop
The reason why I have just claimed that Hadoop is cost-effective and the fastest big data storing and processing framework is because of its architecture which gives it the unique ability to store the data and process the data at an exceptionally fast pace. Here is how.
The following photo illustrates the major components of the Hadoop runtime environment. All these components combined make Hadoop one of the best tools to process big data.
- As soon as data scientist uploads the data on Hadoop framework, the data gets divided and stored into clusters. For instance, if 4 TB of data is uploaded, the data gets automatically stored in 4 clusters and each cluster holds 1TB of data. That means, time taken to store 4 TB of data is the same as the time taken to store 1TB of data. For sometimes, clusters also get divided into ‘racks’.
- YARN infrastructure has a very critical job to do. It provides computational resources like CPUs and memory to the Hadoop program for application execution.
- The HDFS Federation handles the storage. It provides permanent, reliable and distributed storage to the big data. You can know more about it from here.
- MapReduce splits the input data into a number of different parts and executes a program on all data parts at once.
Properties of Hadoop, OR Advantages of Hadoop
After studying the architecture of Hadoop, let’s quickly understand what types of ability this robust architecture gives to Hadoop.
- Low capital investment
As discussed, Hadoop divided the big data into small parts and stores those parts in different clusters and different racks. This is how Hadoop is reducing the need for many servers with high storing and processing capacity.
- Fast execution
Hadoop divides the data, so does the time! If a data of 4TB is uploaded to Hadoop, it gets stored in 4 clusters with each cluster storing 1 TB of data. Now, whenever the program is executed, it is executed at each node at the same time. Meaning, (if the uploaded data is 4TB), Hadoop is 4 times faster than any conventional data processing system.
Hadoop builds a backup file at each level. Because of this, it can successfully prevent data loss in case of the program error or failure. Also, each cluster of the Hadoop works separately and continues working if any other cluster fails.
- Seamless execution
To actualize the Hadoop framework by writing custom-code and giving different queries to get the result from the big data is so painless. It enables users to code in any language. However, the user should know the working model of parallel processing.
So, now when you know all the major things about the Hadoop framework, let me answer a very anticipated question,
How Hadoop can be useful in online business?
The fusion of big data processing framework and big data has been doing wonders for many online business owners. According to many resources, 90% of the global data has been created in the last 10 years alone and IT services are more responsible for it than anything else. By 2020, IT companies will generate more than $80 billion of profit with the big data.
However, big data adoption rate is still low in many countries. People are still lacking the schooling of big data advantages in online business. If you are one of them, the following are the top advantages of storing data and processing that for your online business.
- It improves your pricing
Look around. All major companies are opting more for a dynamic pricing model. Their pricing model changes with respect to the time of the day and the demand. This dynamic pricing model doubles the revenue. But to have dynamic pricing model on-board, you have to rely on big data. By processing big data and applying several machine learning algorithms on it, you can know the historic pricing and relevant demand and sales. Based on this very important insight, you can fix your pricing model and gift yourself a sight of an ever-increasing revenue graph.
- It cuts down the cost
Big data contains all historic data of your cost. This means Hadoop lets you know where you are spending more and how much. Here, by applying machine learning algorithms, you can estimate the future demand and how much you have to spend to satisfy that demand. In this way, you can prevent yourself from spending unnecessarily on operational costs.
- It helps you to compete with big players
Big data processing tools make you and your business accessible to more user groups by identifying potential users and eliminating non-profitable users.
- It lets you offer an ultimate user experience
For an online service-providing company, user experience is very important. Many companies rely on big data and big data processing tools to understand the user behavior and their interests to offer the content which they are most interested in. Same way, you can know the right audience to target with the right content or service and price.
Now, let’s see how practically Uber is deriving benefits from big data and big data processing framework.
Big data and big data processing at Uber
Uber moves people and data moves Uber!
Uber which is having more than a billion users and providing 15 million rides per day, has taken the usability of big data quite seriously. Uber completes most of its business processes such as surge pricing, better cars, detecting fake rides and fake cards with the help of big data, big data processing framework and machine learning algorithms.
Talking about the surge pricing, Uber’s algorithms which simplify the big data with the help of data processing framework, predict how many riders will open the app in the next five minute and how many drivers will be available to satisfy that demand in the next five minute. To predict the demand and supply, Uber’s algorithms take real-time data such as city events, weather, and day time along with historic data into the account. After knowing the relativity degree between demand and supply, the algorithm changes the price and motivates the drivers to drive in surge-priced areas to earn more (and to satisfy the demand).
Another use of big data and big data processing framework at Uber is driver matching. When a user books the ride, the algorithm which learns itself from the historic big data and real-time data, do not find the nearest driver, but it finds the driver who can make it to the rider in the least possible time. For that, the algorithm employs historic data and real-time data such as traffic, one-way streets, bridges, and weather.
In fact, Uber has introduced a program called Uber Movement under which they share collected data with government authorities of many cities. The government then uses this data to improve city transportation and infrastructure.
(Uber movement shows the time it takes to travel between two points at a particular time and particular day in all major urban cities)
In the nutshell
Big data is undoubtedly the vitally important asset to run an online business in a profitable manner. But big data has certain limitations. To go beyond those limitations, data processing frameworks like Hadoop helps. It finds the meanings out of unstructured data and lets you make outstanding data-driven decisions rather than making a decision based on your gut feeling. Hadoop does not only reduce the infrastructure cost to operate big data, but it reduces the error-margin. So, if you are an online business owner or entrepreneur planning to start a new mobile app-enabled business, it is advisable to ask mobile app development company to create admin panel which stores the data and processes the data with the help of Hadoop. You will be amazed to see the results!