5 Steps to Collect Big Data
Thursday, December 22, 2016
(picture from databigandsmall.com)
We know most companies today collect big data to analyze and interpretate of daily transaction and traffic data for keeping track of the operations, forecasting needs or implementing new programs. It is in this way that we define big data as the capability allowing companies to extract value from large volumes of different kinds of data. But how to collect such capability of big data we want directly?
There may be a lot of data collection methods and you may feel quite confused. Here I will make a clarification of the general steps to collect big data.
- Gather data: This is the first step of gathering data from different data sources. Different methods are also provided in this step according to different data collection purposes, for example, census, buying data from the Data-as-Service companies or using the web scraping tool like Octoparseto get data from websites.
- Store data: After gathering the big data, you need to put the data into an appropriated databases or storage services for further professing. Usually this step requires the investment in physical foundation as well as the cloud services.
- Clean up data: Since there are many noisy information you don’t need, you need to pick up the one that meets your needs. This step is to sort the data, including cleaning up, concatenating and merging the data.
- Reorganize data: You need to reorganize the data after cleaning up the big data for further use. Usually you need to turn the unstructured or semi-unstructured formats into structured formats like Hadoop and HDFS.
- Verify data: To make sure the data you get is right and could make sense, you need to verify the data. Choose some samples to see whether it works. Make sure that you are inthe right direction so you can apply these techniques to your sourcing.
So these are the general steps to collect big data. However, to mine such capability of big data to glean insights into markets, investments in technologies, processes and governance are required. It’s not as easy as is mentioned above.
Author: The Octoparse Team
For more information about Octoparse, please click here.
Sign up today!
Most popular posts
- Related articles
- 88 Data Science Resources & Tools
- 10 Best Big Data Analytics Courses Online
- 27 Neural Network Explained in Graphics
- Data Mining Explained With 10 Interesting Sto...
- 8 Keywords Must Know for Machine Learning