Big Data Solution
When we hear the term “Big Data”, so many questions come in mind. What really is this “Big Data”, is it a product? Is it a kind of technology? Or it is just the huge volume of data? If it’s just volume then only big businesses have Big Data? Haven’t businesses always had Big Data, what’s new in it? What volume is really that makes it Big Data?
In this blog, I will try to answer most of these questions and help you understand how it can help your business. Kapital Pi has wide range of product and solutions that can benefit your business from Big Data.
What is Big Data?
There are a number of published Big Data definitions and just as many industry experts who believe that none of them are truly definitive. It’s no wonder that confusion swirls around the term Big Data. Here are couple of them that I will quote here:
Big data is high-volume, high-velocity and high-variety information assets that demand cost-effective, innovative forms of information processing for enhanced insight and decision making.
Big Data is a broad term for data sets so large or complex that they are difficult to process using traditional data processing applications. Challenges include analysis, capture, curation, search, sharing, storage, transfer, visualization, and information privacy.
So widely accepted Big Data definition relates to 3 Vs: Volume (The amount of Data), Velocity (The Speed of Data) and, Variety (Different type of data like structured or unstructured) .
As it sounds, we are talking about data that could be in high-volume, could come at high speed and it could be any type of data like, images, excel sheet, word documents, log files, sensor data, data from a database etc. Big Data solutions provide the tools, methods and technologies used to capture, curate, store, search and analyze the data to find new correlations, relationships and trends that were previously unavailable.
What qualify to be ingested as Big Data?
In Past, system were built to produce and store data in structured ways, and stored in system like Oracle, SAP, NetSuite etc. There has also been some other ways of producing data but that were only been used up to very minimal extent once first level use is completed i.e. email, instant messages, public websites, log, sensor data, audio, video etc. Some new sources of data have emerged in recent few years like social media, data from small devices like IoT etc.
All other data that is not stored in structured way qualify as unstructured data and it account for more than 90% of data produced today. Big Data provides option to store and process all types of data whether data is structured or unstructured.
Big Data- How to benefit?
So how are enterprises using big data today? Here are some popular big data usages:
- 360-degree view of your customer: Many enterprises are building system to create a dashboard to provide 360-degree view of a customer. i.e. Healthcare organizations can create a 360-degree view of patient care as the patient moves through various treatments and departments. A streaming company can build 360-degree view to understand what a customer is watching at particular time and location to understand and build suggestion. These systems pull together data from a variety of internal and external sources, analyze it and present it to customer service, sales and/or marketing personnel in a way that helps them do their jobs.
- Fraud Prevention: When it comes to security, it’s not just a few rogue hackers. Some financial services industry and others are using Big Data for Fraud Prevention. While security landscapes and compliance requirements are constantly evolving, companies can identify patterns that indicate fraud and aggregate large volumes of information to streamline regulatory reporting.
- Anti-Money Laundering: Financial services firms are under more pressure than ever before from governments passing anti-money laundering laws. These laws require that banks show proof of proper diligence and submit suspicious activity reports. In this extraordinarily complicated arena, big data analytics can help companies identify potential fraud patterns.
- Price Optimization: Both B2C and B2B enterprises are also using Big Data analytics to optimize the prices that they charge their customers. For any company, the goal is to set prices so that they maximize their income. If the price is too high, they will sell fewer products, decreasing their net returns. But if the price is too low, they may leave money on the table.
- Operational Efficiency: In addition to helping organizations optimize their pricing, big data analytics can also help companies identify other potential opportunities to streamline operations or maximize their profits.
Other benefits could be like Recommendation Engines, Security Intelligence, Data Warehouse Offload, Social Media Data Analysis and Response etc.