Big data analytics?
Big data analytics is the process of observation data to reveal hidden patterns unidentified contacts and other useful data to make better decisions. Big data analytics can analyze square the size of the data analysis and business intelligence solutions that can not be touched. It is made mostly from sensors, video / audio, social media networking websites, a large log file format.
Your organization could add billions of rows of data with various combinations of data in multiple data stores. Big data allows you to drive innovation and decision-making possible. To process the data to figure out what is important and what is not a high-performance analytics are required. You can use high-performance analytics for easy and rapid processing of sensitive data. Shapes are the sole property of machine learning to address the needs of their data in new ways.
Big data is useful if you can do something with it. Amazon and Google subsequently used the knowledge to enhance their competitiveness and they are the leaders in the data analysis.
Let's talk about the Amazon, its data analysis made it successful. All it takes history and buying patterns of your people as you can come up with some good suggestions.
The data provides a unique opportunity for your organization to analyze. Analyzed data that is challenging and use more detailed data and wide for analysis.
Strategy Analytics drives will provide useful results with data. When it comes to analysts consider a range of possible:
Simple analyzed for insight
It describes the data sharing of the game and sees the simple, basic monitoring and reporting.
Advanced analytics for insight
It described the difficulties, such as modeling analysis and pattern matching techniques forecast.
Analysis process
It describes the analytical methods as part of business processes.
Scan
It describes the analytical methods that are used to drive revenues directly.
Reactive and proactive approaches:
Reactive approach:
In response method, Business Intelligence provides ad hoc reports alarms based business reporting and analysis standard. But when reports of giant data set, it means it is performing large BI data.
Methods:
Inactive approach, analytical methods as large mining projects, predictive modeling, statistical analysis and optimization allow you to view or identify weaknesses tend to make decisions about the future. In data analysis, you can remove the data from petabytes = exabytes terabytes. Becoming practice with data analysis is not a big effort.
The benefits of big data analysis
Data analysis allows business users and analysts to develop an understanding of the available data has resulted in many business benefits. Detailed analysis of the data and analysis arrow key. Some of the standard features are as follows:
Ad targeting is analyzed about a wide disparity of data or events and recommend better to users when they browse the shopping areas, hotels, travel portal or flight searches.
They provide better recommendations to users regarding discounts, deals, and offers based on historical products and discover its history.
If customers are changing from one service provider to another service provider, followed by the analysis of the problems faced by customers due to record large data can be found, in the telecom space.
Based on these issues, it will be known whether a telecom company is required to submit a new building in a particular area.
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