This is a guest post by Khushbu Shah from DeZyre.com.
Internet today as a collective agency is creating 2.5 quintillion bytes of date on a daily basis and nearly 90% of all of our global data has emerged in the past 2 years.
Looking from an outsider’s perspective Big Data sounds like a good thing, which it is if we can manage to effectively handle it. For example, Atlantic Ocean stores around 100 billion billion gallons of water; if every gallon represented a byte of data, the Atlantic Ocean could only store data produced up to year 2010. From the analogy, it is clear that it is a lot of data. The tricky part is to find the useful information in this vast chunk of data. And we are creating far more data than what we were producing in 2010.
This article presents use cases of Big Data. Examples like analysing campaigns, diagnosing automotive traffic and smart news aggregation will be discussed in this article. Respective sections will discuss further details as in how big data is generated for this particular application and how is it used to generate required results.
Nowadays online promotional campaigns have become a key thing for marketing and growth ventures of any business. But it can be fruitless if done without real-time insight in to the campaign. Ideally the campaign should leverage Big Data generated from previous campaigns and decide upon features like keywords, graphic design, UI/UX, demographic, etc.
The sheer volume, velocity, variety and value that is being presented by Big Data can be used to understand the customer’s requirement, relevant market development and opportunities. To make the most out of the relevant Big Data for your campaign analytics; one needs to aggregate data efficiently, create a query response system with minimum latency to analyse the data and present visual aids for statistics generated from the Big Data.
Before you start any online campaign, you need to identify your objectives. This includes getting to know your desired customers, target audience, relevant market sections. Objectifying targetable results from the campaigns which can include goals of sales number, popularity index, visibility index and others. This is to be followed by aggregating relevant data for your campaign. Big Data relevant to your campaign can be sales report of market section, customer feedback, online engagement index with previous campaigns, etc.
Once the Big Data is aggregated and analysed, business insights are created which leads to impact on both future campaigns and desired objectives. All this needs to be done because conventional sources like sales figure are not enough to predict customer’s behaviour and therefore a Big Data solution is required which delivers a transparent metrics on global marketing activities by blending multiple sources of information.
Benefit of Big Data analysis for campaign analytics can be summarized as follows:
- Targeted Campaigns result in efficient allocation of marketing budget. Hence this is a smart way to boost sales without enhancing the customer acquisition cost.
- Monitoring Big Data in real-time provides a way for PR team to timely respond to negative feedback for the company and its products.
- Based on the response metrics, future marketing decision can be taken for better outputs.
Traffic and Diagnostics
Imagine being caught in terrible traffic on a rainy day while going to your office to attend an important meeting. You have a feeling that this will take at least couple of hours and you will miss your meeting and have serious consequences at office. Now that we have your attention, let us paint a picture where you will get live traffic diagnostics on your smart phone. You are being updated with short-cuts options which have less congested traffic and the entire fleet of city traffic is being evenly distributed in real-time to make sure that everybody reaches on time.
One of the prominent services provided in this discipline is offered by Google Maps. They predict the velocity of traffic by aggregating and averaging the velocity of individual android mobile users.
Currently this service is not very accurate because of the irregularity in vehicle sizes. This means that some android phone users may be driving a car and some may be driving a motorcycle and both of them affect the traffic in a different manner.
Efficient Fleet Management
This is a Big Data use case for delivery services who manage a large fleet of ground and air vehicles. The objective is to minimize the transportation cost and duration. This is done by analysing the data obtained from individual units of the fleet. Relevant data for efficient fleet management can be fuel-consumption metrics, data on shipment, speed data, road grades and flight routes metrics.
Transportation fleet management is required to reduce both the expenditure and their environmental footprint. Without a properly planned fleet, management will observe a climb in operations cost and decline in margin. This is why players in logistics industry have chosen to obtain insights for an efficient fleet operation. Data analysis provides actual operation assistance by avoiding empty truck and flight movement, reducing out of route miles and eradicating poorly coordinated shipments. Cherry on top is high fuel efficiency and minimized eco-footprint and all of this can be achieve by educating driving behaviour.
The Big Data for efficient fleet management is utilized by analysis done on frequently traveled. This will lead to pattern identification for routes and in turn lead to improvement in time and fuel efficiency of the fleet. With the volume of travel related data available to use, it is possible to evaluated non-congested and short routes for individual vehicles and even for entire fleet. Application like Google-Maps can be used as a visualization aid for fleet management.
One of the biggest problem for the logistics industry is empty truck or flight movement. It implied an additional cost of fuel with no logistical benefits. Proper planning of routes and shipments will eliminate this problem. Therefore to maximize the payload and efficiency, one needs to coordinates the consignments and it can be done by analysing the data in real-time which is being generated by distributed local logistical ground stations and mobile air and ground fleet.
To summarize the benefits of Big Data in this discipline:
- Real time data analysis from logistic ground centers and mobile fleets will lower emissions and fuel consumption.
- It will improve route planning and reduce the cases of empty truck movement.
- Visual assistance for the fleet.
Intelligent News Discovery
Currently there are various online applications available who cater to your news requirements by putting together relevant articles based upon your interest. In this section, we will explore the ideas for Big Data Analysis for media production, archiving and news aggregation.
Today we have at our disposal ever-increasing amount of data in various formats originating from diverse sources such as text, video and audio. Focusing on news related articles and items, petabytes of data is generated every day and the amount seems to be growing exponentially on an annual basis. On top of it various initiatives of digitizing the data adds up the trouble of querying the relevant information and fetching it to users. Big Data solution for intelligent news discovery aims to identify, index, structure, interpret, analyse and manage media content in real-time. The result obtained from this is a relevant news-feed catered specifically for each users based upon their interest.
Benefits of Intelligent News Discovery using Big Data Analysis:
- Efficient information management for online users for better and faster news aggregation.
- Complete visibility for latest topics, data and facts.
- Reduced cost of information management because of the automated searches and low-latency queries on complex and unstructured data.
There are various other big data use cases that can be viewed here and also all the companies that have been front runners in the space of using big data analysis to gain competitive edge in the market.