6 Vital Steps For Big Data Analysis
Big data is available at various storage places and the data is becoming numerous by the passage of time. Google can provide plenty of links for structured datasets. This data is pre-processed and is utilized in various studies therefore this is a verified form of data that can be used for analysis and learning. There are several steps to make the data ready for studies are research. It is therefore necessary to learn how to deal with big data if it is in unstructured form.
1. Extraction Of Data:
To start any sort of research, the main element to conduct the study is data for any sort of big data problem. Plenty of crawlers are available in the market that can be used for data extraction. Mostly researchers write the scripts in different programming languages to get the data form the online platforms. A traditional way to get the data via calling API of company services.
2. Data Storage:
Researchers face plenty of problems and one of the key issues in the field of data is how to store and manage the big data. The said problem can be resolved utilizing two major resources that are budget and expertise of the researcher. A decent provider ought to permit you a protected, straight-forward spot to store data.
3. Data Cleaning:
Before preparing a use-able dataset, data is processed through lot of stages, that can be utilized for machine learning algorithms. There are various processes like removal of raw data from the big data and saving the actual values that are required for further research. As data is in different forms like audio, video, text and image. According to the form of data, pre-processing techniques are adopted.
4. Data Mining:
Discovering insights from the stored database is the actual benefit of data mining. It makes decision as well as provide predictions on the basis of stored data.
5. Data Analysis:
Collected data is used for analyzing patterns and behaviors of the big data. An expert is one who can spot an ordinary thing or still not reported by any other researchers.
6. Data Visualization:
Data visualization is the actual requirement of whole the process, or it is the best format as a summary of the analyzed big data. Some experts use software such as Tableau and Weka. Programming languages also provide such type of support to visualize the results after writing the required script. Python, R, Plot.ly and D3.js provide best results in this process.
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