What is Data?
The quantities, characters, or symbols on which operations are performed by a computer, which may be stored and transmitted in the form of electrical signals and recorded on magnetic, optical, or mechanical recording media.
What is Big Data?
Big Data is also data but with a huge size. Big Data is a term used to describe a collection of data that is huge in volume and yet growing exponentially with time. In short such data is so large and complex that none of the traditional data management tools are able to store it or process it efficiently
Big data is a field that treats ways to analyze, systematically extract information from, or otherwise deal with data sets that are too large or complex to be dealt with by traditional data-processing application software.
Types Of Big Data
BigData’ could be found in three forms:
- Structured
- Unstructured
- Semi-structured
Structured
Any data that can be stored, accessed and processed in the form of fixed format is termed as a ‘structured’ data. Over the period of time, talent in computer science has achieved greater success in developing techniques for working with such kind of data (where the format is well known in advance) and also deriving value out of it. However, nowadays, we are foreseeing issues when a size of such data grows to a huge extent, typical sizes are being in the rage of multiple zettabytes.
Unstructured
Unstructured data is heterogeneous and variable in nature and comes in many formats, including text, document, image, video and more. Unstructured data is growing faster than structured data. According to a 2011 IDC study, it will account for 90 percent of all data created in the next decade. As a new, relatively untapped source of insight, unstructured data analytics can reveal important interrelationships that were previously difficult or impossible to determine. Big data analytics is a technology-enabled strategy for gaining richer, deeper, and more accurate insights into customers, partners and the business and ultimately gaining competitive advantage. By processing a steady stream of real-time data, organizations can make time-sensitive decisions faster than ever before, monitor emerging trends, course-correct rapidly and jump on new business opportunities.
Semi-structured
Semi-structured data can contain both the forms of data. We can see semi-structured data as a structured in form but it is actually not defined with e.g. a table definition in relational DBMS. Example of semi-structured data is a data represented in an XML file.
Big Data in Social Media
Facebook revealed some big, big stats on big data to a few reporters at its HQ today, including that its system processes 2.5 billion pieces of content and 500+ terabytes of data each day. It’s pulling in 2.7 billion Like actions and 300 million photos per day, and it scans roughly 105 terabytes of data each half hour.
Instagram, the social networking app for sharing photos and videos, launched in 2010. Today, it boasts 800 million monthly active users and is owned by Facebook. There are 70 million photos uploaded to Instagram every day. People interact with each of those posts by showing their love with a heart, commenting and using hashtags. What all of this activity does is create an enormous amount of data. Once analysed, by humans as well as increasingly through artificial intelligence algorithms, it can provide incredible business intel and insights into human behaviour causing Instagram CEO Kevin Systrom to say, “We’re also going to be a big data company.”
Netflix
Netflix has over 100 million subscribers and with that comes a wealth of data they can analyze to improve the user experience. … Big data helps Netflix decide which programs will be of interest to you and the recommendation system actually influences 80% of the content we watch on Netflix.
Characteristics Of Big Data
(i) Volume — The name Big Data itself is related to a size which is enormous. Size of data plays a very crucial role in determining value out of data. Also, whether a particular data can actually be considered as a Big Data or not, is dependent upon the volume of data. Hence, ‘Volume’ is one characteristic which needs to be considered while dealing with Big Data.
(ii) Variety — The next aspect of Big Data is its variety.Variety refers to heterogeneous sources and the nature of data, both structured and unstructured. During earlier days, spreadsheets and databases were the only sources of data considered by most of the applications. Nowadays, data in the form of emails, photos, videos, monitoring devices, PDFs, audio, etc. are also being considered in the analysis applications. This variety of unstructured data poses certain issues for storage, mining and analyzing data.
(iii) Velocity — The term ‘velocity’ refers to the speed of generation of data. How fast the data is generated and processed to meet the demands, determines real potential in the data.
Benefits of Using Big Data Analytics
- Identifying the root causes of failures and issues in real time.
- Fully understanding the potential of data-driven marketing.
- Generating customer offers based on their buying habits.
- Improving customer engagement and increasing customer loyalty.
- Reevaluating risk portfolios quickly.
