Big data means a large amount of data which comes from various data sources which has different format. Big data is more collection of different data sets. It is an important assets which can be used to obtain enumerable benefits.
Three formats of Big data:
There are three formats of big data. They are:
- Structured: fully organised data format with a fixed schema.
- Semi-structured: partly organised data which does not have a fixed format.
- Unstructured data: unorganised data without known format.
Characteristics of Big data:
1. Validity: It corrects data
2. Variability: It has dynamic behaviour
3. Volatility: Tendency to change in time
4. Vulnerability: it is vulnerable to breach the attacks.
5. Visualisation: it is about using the data.
Big data analytics is largely used by companies to improve the growth and development. There are multiple tools for big data processing such as Hadoop, Pig, hive, Cassandra, HCatalog etc. Data is mostly produced by people in organisations. The data usually has a specified structure. It is nothing but basis of records on money paid, deliveries made and employees hired etc.
Here the data processing must manage lots of data, speed of data arriving, many different sources of data arriving in different formats. The more data you have, more is the chance of getting insights from it. The size of big data makes it impossible to use the manual and conventional computing methods. Big data analytics is based on data mining to shift through data with different patterns and different relationships, machine learning can handle to change new data, to adapt and enrich models, text analytics and natural language processing to analyze free form text speech.
Big data analytics tools:
The Big data analytics tools can be grouped as:
Descriptive analytics for finding what happened,
Diagnostic analytics for explaining,
Predictive analytics to suggest what will likely to happen and
Prescriptive analytics to tell users what to do.
An example of big data analytics:
Consider a company runs big data on its past sales data. It sees a demand has been rising in certain regions for one of its product lines. From social data and CRM company also find that customers are buying products by marketing data and analytics the sales potential prediction in each region where the customer might replace current productivity.
Big data benefits:
Big data has various benefits like:
- It can utilise outside intelligence while taking important decisions.
- Access to social data from various search engines is making organisations to fine tune their business strategies.
- Improved customer service
- Traditional customer feedback systems are getting replaced by new systems which are designed with big data technology.
- Big data and available all natural language processing technologies are being used to read and evaluate consumer responses.
- They have ability to identify early risk of the product.
- And also can identify better operational efficiency.
For example, big data is used in many companies which provides valuable insights to their customers that can be used to improve marketing campaigns and techniques in order to increase customer engagements and conversion rates. Furthermore, Big data can be used by medical researchers to identify disease risk factors and by doctors to diagnose the illness and conditions in individual patients.
In the energy industry, big data is used which helps oil and gas companies to identify potential drilling and observe the pipeline operations. Financial services companies use Big data systems for risk management and for real time analysis of market data. Manufacturers and also transportation companies rely on big data to manage their supply chain.
Volume is the major characteristics of big data. A big data environment doesn’t necessarily have to contain large amount of data contain but most will have because of the nature of the data being collected and stored. Big data applications usually include multiple data sources which may not be integrated.
