Big data 319-18 group Kurbonov Bekzod What is Big data ?

how big data is used by organizations

• In the energy industry, big data helps oil and gas companies identify potential drilling locations and monitor pipeline operations; likewise, utilities use it to track electrical grids.
• Financial services firms use big data systems for risk management and real-time analysis of market data.
• Manufacturers and transportation companies rely on big data to manage their supply chains and optimize delivery routes.
• Other government uses include emergency response, crime prevention and smart city initiatives.

Advantages and Disadvantages of Big Data
The increase in the amount of data available presents both opportunities and problems. In general, having more data on customers (and potential customers) should allow companies to better tailor products and marketing efforts in order to create the highest level of satisfaction and repeat business. Companies that collect a large amount of data are provided with the opportunity to conduct deeper and richer analysis for the benefit of all stakeholders.
With the amount of personal data available on individuals today, it is crucial that companies take steps to protect this data; a topic which has become a hot debate in today's online world, particularly with the many data breaches companies have experienced in the last few years.
While better analysis is a positive, big data can also create overload and noise, reducing its usefulness. Companies must handle larger volumes of data and determine which data represents signals compared to noise. Deciding what makes the data relevant becomes a key factor.
Furthermore, the nature and format of the data can require special handling before it is acted upon. Structured data, consisting of numeric values, can be easily stored and sorted. Unstructured data, such as emails, videos, and text documents, may require more sophisticated techniques to be applied before it becomes useful.
As big data is huge different strategies are used in order to analysis the data generated from the big data. We can, not only find the customer wish product but also predict the market demand and many more. Big data has changes the horizon of ecommerce industry getting more and more customer. If proper analytics of big data is done, Ecommerce platform will be very much beneficial from the output of Big data. Different types of Big Data analytics frameworks which focused with Big Data analytics workloads are analysed to get proper result against set of criteria. In this report we identified that all existing framework lacks a single limitation. Due to which existing frameworks does not met the criteria to fulfil the attributes of Big Data together or they require high level of expert knowledge to work with. However, most of Big Data analytics lack the expertise to use the system. Therefore, a new approach is required to deal with new and new Big Data analytics problems.
Conclusion