Big Data Basics
The term Big Data is a buzzing term which is evolving rapidly and it deals with heavy volume of unstructured, semi structured as well as structured data that needs to be cultivated (which is called mining in technical terms) in order to extract meaningful information.
The application of Big Data has raised exponentially because of the evolving business and their huge amount of data that is getting generated on a day to day basis. But the main focus is not in the amount of data for an organization. What the organization focuses on is what needs to be done with such data, how to process it and where it can be used further.
Big Data learning along with data mining techniques can help analyze for insights which can lead to improved decision and strategy with data for organization and how business or firm will move.
Big Data is commonly termed with its mirror-term 3Vs. Since the term “Big Data” is comparatively new, the act of accumulating large quantity of information for ultimate analysis is very old. The concept of enormous amount of data storage drove into action around the year 2000 with the evolution of characteristics of three Vs in data:
Volume: Different organizations are collecting enormous extent of data from different sources such as business transactions and deals, social media information and private data, information from sensors & machine-to-machine data, statistical data from various business and marketing software and lots more. In the earlier days, storing and management would have been a serious concern – but with the evolution of new languages and technologies like Hadoop, the burden and concern got minimized.
Velocity: Streaming of data needs to be done with exceptional swiftness and speed. So they must be compactly sent in a fixed time period. The new technological gadgets like RFID tags, detectors and sensors, smart metering and smart wearable gadgets needs smooth flow of data in near-real time to be usable.
Variety: Today’s databases store diverse forms and types of data. Also data that gets generated from business, social networking sites and other sources arrives in a wide range of formats – from structured type such as: numeric data, employee data that can be stored in traditional databases to unstructured data which contains varieties ranging from multimedia such as documents, video, audio, images of statistical plots to stocks data and email attachments as well as financial transactions and deals.
Big Data also deals with things like complexity in data. As discussed, now-a-days all data arrives from diverse sources resulting in inefficient crafting and leads to difficulty in linking, matching, cleansing and transforming these data over various systems, making it incompatible to use on different systems. However, with the help of Big Data, it becomes easy and to connect and associate relationships as well as hierarchies between compound data.
There are wide usages and importance of big data right from how to store data in a manageable way to how you use these data. Some of the key importance of Big Data are –
Reduction in maintenance cost.
Reduction in maintenance time.
Helps in smart decision making.
Optimizing data analysis and mining for product development
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