What is Big Data Analytics?

What is Big Data Analytics

What is Big Data Analytics?

Big data analytics examines large amounts of data to discover hidden patterns, correlations and other perceptions. Big Data Analytics is the process of collecting, organizing and analyzing large data sets (called Big Data) to discover patterns and other useful information. Big Data analytics can help organizations better understand the information contained in the data and will also help identify the most important data for business and business decisions. Analysts who work with Big Data usually want the knowledge resulting from the analysis of the data.

Importance of Big Data Analytics

The analysis of Big Data is, in fact, a revolution in the field of Information Technology. The use of data analysis by companies is increasing every year. The main focus of the companies is on the customers. Thus, the field is flourishing in Business to Consumer (B2C) applications. We divide the analysis into different types according to the nature of the environment. We have three divisions of Big Data analysis: prescriptive analysis, predictive analysis, and descriptive analysis.

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Types of Big Data Analytics

There are four types:

Descriptive Analytics

It uses data aggregation and data mining to provide information about the past and respond: “What happened?” The descriptive analysis does exactly what the name implies that they “describe” or summarize raw data and make them interpretable by humans.

Predictive Analytics

Use statistical models and provide techniques to understand the future and answer: “What could happen?” Predictive analytics provides companies with useful information based on data. It provides estimates about the probability of a future result.

Prescriptive Analytics

It uses optimization and simulation algorithms to advise possible results and answers: “What should we do?” It allows users to “prescribe” a number of different possible actions and guide them to a solution. In summary, this analysis is all about providing advice.

Diagnostic Analytics

The diagnostic analysis is an investigation designed to study the effects and develop the right kind of reaction to the situation.

Big Data Analytics Tools

The analysis of big data has become so modern that almost all large technology companies sell a product labeled “big data analytics”, and a variety of startups also offers similar tools. Big data analysis based on the cloud has become particularly popular. In fact, the 2016 Big Data Maturity Survey conducted by AtScale found that 53% of respondents planned to use cloud-based, large-data solutions and 72% planned to do so in the future. Open source tools such as Hadoop are also very important, often providing the backbone for commercial solutions. The following lists are not exhaustive but include a sample of some of the best-known big data analysis solutions.

Big Data Analytics tools

  • open source
  • Hadoop
  • HPCC
  • Ignite
  • Lumify
  • Pandas
  • GemFire Pivotal, Greenplum database and HAWQ
  • spark
  • storm

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Big Data Analytics and Data Sciences

 The analysis involves the use of advanced techniques and analysis tools in the data obtained from different sources in different sizes. Big data has the properties of high variety, volume and speed. The data sets come from several online networks, web pages, audio and video devices, social media, records and many other sources. Big data analysis involves the use of analytical techniques, such as machine learning, mining of data, natural language processing and statistics. The data is extracted, prepared and combined to provide business analysis. Large companies and multinational organizations use these techniques widely today in different ways.

Data analysis involves qualitative and quantitative techniques to improve productivity and business benefits. Data analysis tools are used by researchers, analysts and engineers for commercial organizations to access data efficiently. There are special analytical tools that use these techniques to analyze data sources for new ideas. The data is generally real-time data produced on a large scale. These data are not structured and the tools help capture this data and store it for analysis.

Real-time Benefits of Big Data Analytics

There was enormous growth in the field of Big Data analysis with the benefits of technology. This led to the use of big data in several sectors, from

  • Banking
  • Health care
  • energy
  • Technology
  • Consumer
  • Manufacturing

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