Big data in customer software development

Big Data is structured or unstructured large quantities of data. They are processed with special automated tools to be used for statistics, analysis, predictions, and decision making.

The very term was proposed by the editor of the journal Nature Clifford Lynch in a special issue of 2008. He talked about the explosive growth in the world. Lynch attributed any collection of heterogeneous data more than 150 GB per day, but there is still no single criterion.

Until 2011, big data software development was analyzed only within the framework of scientific and statistical research. But by the beginning of 2012, the volumes which had grown to a huge scale, and there was a need for their systematization and effective application.

Since 2014, the world’s leading universities paid attention to Big Data, where they teach applied engineering and IT specialties. Then IT corporations joined in the collection and analysis – such as Microsoft, IBM, Oracle, EMC, and then Google, Apple, Facebook, and Amazon. 

How Big Data works: how is big data gathered and saved?

It is needed to analyze all the relevant factors and make the right decision. With the help of it, simulation models are built to test a special solution, idea, or product.

The main sources:

  • Internet of Things (IoT) and appliances attached to it;
  • social networks, blogs, and tools;
  • company data: transactions, orders for goods and services, taxi rides and car-sharing, customer profiles;
  • instrument readings: meteorological stations, meters of the composition of air and water bodies, from satellites;
  • statistics of cities and states: data on movements, births, and deaths;
  • medical: analyzes, diseases, diagnostic images.

Since 2007, PRISM has appeared at the disposal of the FBI and the CIA – one of the most advanced settings that collect personal data about all users of social networks, as well as services from Microsoft, Google, Apple, Yahoo, and even telephone recordings.

Modern computing systems provide instant access to huge quantities of data. To store them, they use special data centers with the most powerful servers.

How is it Analyzed?

With high-performance technologies such as grid computing or in-memory analytics, firms may leverage any amount of big data for analysis. Sometimes it is first structured, selecting only those that are needed for analysis. 

There are four principal ways of analysis in big data analytics Company:

1. Descriptive analytics is the most common. It explains the topic “What occurred?”, Studies the data coming in real-time and actual data.

2. Sinister analytics – helps to foretell the most suitable way of issues based on the open source. To do this, use ready-made templates based on any purposes or events with a related assortment of things. Applying predictive analytics, you may, for instance, determine the failure or change in values in the stock exchange. Or assess the possible borrower’s capacity to pay the mortgage.

3. Prescriptive analytics – the following level related to imminent analytics. With the guidance of Big Data and developed technologies, it is possible to recognize query features in marketing or any other action and determine in which situation they may be withdrawn in the future.

4. Diagnostic analytics – practices data to examine the cause of what occurred. That serves to distinguish oddities and random links within functions and actions.



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