The 3 Main Challenges, Faced by Users in the Data Extraction

Data Extraction Challanges
The Digital World has opened a new forum to solve our problems by doing research. Now days, we heard a lot of people saying that they are doing research for their projects. For instance, primary and secondary companies (companies who are making and selling products) have research departments to improve their employees’ performance, existing products and to know what is the preference their consumer. Even, Tertiary companies (service providing companies) are also doing a lot research to improve their services. On the whole, we all are doing research to improve our business or ourselves.

By these researches, we get the data to solve our problems. Commonly, the process through which we get majority of data is called Data Extraction. Data Extraction is usually done from unstructured data sources and unstructured data can be in any format like tables, index etc.

From unstructured data resources, we faced 3 main challenges in extracting the data.
1) Identifying and Retrieving the Authentic Data
2) Storage and Privacy
3) Integration of data

Identifying and Retrieving the Authentic Data:

To answer any of our problems, we want to have reliable and accurate data. The data that have quality of information in the appropriate quantity. But world wide web, has made this a little difficult. On the World Wide Web (www), people use different browsers to find data, but that data can be outdated or misleading in understanding the main themes. To solve this challenge, we should use a user-friendly interface that can provide desired information. For example Data Extraction softwares and Data Extraction applications can help in this aspect.

Storage and Privacy:

From past few years, this problem has persisted to continue, which is affecting users badly. Impressive growth in storage capacity is leading to low guarantee of privacy. The social Media channels have taken a loins’ share in exploiting the personal information. So, the useful and important should handle carefully like cloud storage with security are much better option are this purpose.

Integration of data:

After collecting and retrieving the useful information, data integration is an important task that needs an advanced and secured database. Usually, people make several mistakes in the integration of large amount data and these errors leave their data useless or incomplete. To avoid these errors, we should try data extraction tools which can be helpful. As these tools can easily integrate the data into a presentable form of information.
So, in the end, these challenges can the biggest errors, which can make our efforts useless.