Big Data: Why Enterprises need to start paying attention to their Data sooner?
The awareness around Big Data is on the rise and is exciting!. As we all know in the technology space the word Big Data revolves around the 3 V’s, the Volume, Velocity and Variety of the data that is typically seen in all enterprises these days.
The blog on visualize the 3V concept is a good resource that provides a view into Big Data if you are not so familiar with have this question: “What is Big Data?.”
It’s 2013, the time is so right for all enterprises to pay more attention to their Big Data. With the right technology and processes around their Big Data, enterprises can now trigger new ideas around business growth in 2013.
Some of the exciting new strategies that enterprises should look at for their Big Data are:
1. Build advanced predictive models with the information that they already have around their customers and products to create new product and marketing services that will help to differentiate them from their competitors.
2. Data Mining that will help to understand their customers buying persona that will facilitate to capture new customers and markets.
3. Real-time analytics to understand the past behavior patterns of the customers which then will provide greater ability to satify the existing customers by providing personalized services that is relevant to meet their needs and wants.
Facebook hit the Big Data issues where they had to process huge amounts of structured ( ex. …)and unstructured ( ex. video, email, text) data half decade ago. Facebook joining forces with Yahoo then lead to the creation of Hadoop, a software platform for processing and analyzing epic amounts of data streaming across the modern web. These days the social media platforms like Twitter and LinkedIn have to deal with Big Data to keep their system operational. Guess what they are using to process and manage their Big Data. It is all done through Hadoop. Today we have eBay, and dozens of other high-profile web vendors are using Hadoop to analyzes their vast amounts of data generated during their online operations.
Reshaping the Business Model around Big Data
Most enterprise have Big Data that they have gathered in their data warehouses over the years. But they do not know how to use them nor do they know what the benefits that the various data that they have gathered over the years or the new data that they can collect will help. This is why business needs to spend more time to understand the importance of their existing data and think of ways that they can incorporate data which can help them to grow their revenue.
Let’s look at some examples to understand the value of Big Data in these specific markets. Mobile applications, tablets and smartphones are creating customers and services to consume and integrate structured and unstructured data from a variety of sources.
1. HealthCare Market:
Business objective: Providing, enhancing and streamlining how hospitals connect with and care for their patients. Develop and facilitate personalized therapies and diagnostics to the patients
Big Data opportunity : Incorporate a Big Data analysis engine to build predictive models against patients cynical history, genetics, blood work etc.models.
Why: This will facilitate the doctors to make best treatment recomendations in a timely fashion for their patients. This will help to offer the best care at the same time reducing the healthcare cost by avoiding unnecessary treatments to patients.
2. Retail Online Market :
Business objective: Revolves around connecting the merchants with the consumers in a more effective way such that the consumers can find what they want conveniently and effectively in a timely fashion. This would require merchants to know what the consumers are looking, when and where.
Big Data opportunity : Incorporate a Big Data analysis engine that builds predictive models that will help to make better decisions
- Build consumer models with their transactional history, buying pattern, interest in types of goods, browsing pattern, buying power pattern in $ amount etc.
- Generate a catalogue for the Merchants based on the type of goods, price, value and access.
Why: The predictive models will help to effectively connect the merchants with the consumer so its a win-win for all business entities.
3. Financial Market
Business objective: Provide a High-Performance Trading platform that is effective,accurate and reliable
Big Data opportunity : Advanced analytical engine that will allow for the analysis of complex data sets and the ability to connect patterns and relationships applied to analysing news, social media feeds, scanning incoming emails, or disecting company regulatory filings to generate predictable models
Why: This will facilitate the traders to make effective and accurate trading decisions that is profitable
Big Data Technology and Solutions:
With the 3 Vs around Big Data, enterprises will have to look at the technologies, solutions and data stores that will help them to be successful with Big Data.
Big Data Technology & Data Stores: There are lot of vendors that can offer products around Big Data software platforms and data stores. This was the first areas that got a lot of attention from vendors to address the Data management, processing and operational issues around Big Data. Machine Learning engines are still evolving which will help build accurate and a reliable predictive models . Because of the nature of volume, variety and the velocity with which Big Data has to processed it requires an accurate and a reliable model-building process which has to be automated through advanced algorithms to be effective.
Big Data Solutions: Right now most of enterprises are trying to build specific tailored solutions in-house to address their basic needs. The Big Data solution space is still a evolving and there is lot of opportunities for innovation and creativity The solution market for Big Data is still an untapped market.
The story is a bit different when it comes to realtime analytics. Enterprises clearly understand the importance of real-time analytics and how it provides a value to the current business. As a result there are vendors who have already built cool realtime analytical solutions that the market wants and that help enterprises reshape their existing business model.