Please enjoy this blog post authored by Navdeep Vohra, Senior Manager, Data Architect & Management at Borden Ladner Gervais LLP (BLG).
Data extraction can be defined as the process where data is retrieved from various data sources for further data processing and analysis to gather valuable business insights or storage in a central Data Warehouse. The data obtained from different sources can be unstructured, semi-structured, or structured.
Corporations, individuals, or companies frequently extract data to analyze it using Business Intelligence (BI) tools, migrate the data to a repository, or replicate data as a backup.
Data Extraction is the first step in the Extract, Transform, and Load (ETL) processes in the data ingestion paradigm. It helps in preparing data that would be cast to a required format for further analysis to gain useful insights. The data could be from multiple sources and types, therefore, there has to be a synchronised tool for effective analysis and this can be done using a Data Extraction Tool.
In the modern world today, companies can get data from diverse sources ranging from web pages, print media, documents, forums, blogs, videos, etc. Harnessing potential information from these data sources helps corporations make incisive and business improving decisions. The process involved in extracting valuable insights from multiple sources of data by companies is called Data Extraction and the tools they use to achieve this are called Data Extraction Tools.
Data Extraction can be quite a cumbersome process because any company will stutter in trying to make a valuable in-depth analysis of the data generated. Hence, to simplify the Data Extraction process, Data Extraction Tools were developed. Having the right Data Extraction Tool gives you an advantage as you can leverage on its offerings to draw useful and helpful conclusions about a lot of things like customer’s details, market research, prices of commodities, the state of your business as well as creating a backup or transfer of data to another location for storage.
Data Structures that are used in different data sources are commonly divided into 2 types:
- Structured Data: This type of data is already formatted in a way that fits the need of the project to be undertaken. It is arranged in a way whereby you do not have to manipulate or work on it before the extraction process.
- Unstructured Data: This refers to data that does not have a proper format and hence it needs to be prepared in a format that can be used for extraction. This involves the clean up of “noise” from the data by removing white spaces, deleting duplicate results, etc. Unstructured data can also be in the form of physical structures that may have a varying format. For example, trying to extract data from written notes by many sales representatives. This would mean that the data needs to be arranged in a unified way before Data Extraction.
In order to determine the best Data Extraction Tool for a company, the type of service the company provides and the purpose of Data Extraction is a very important parameter. In order to understand this all the tools are categorised into four categories and are given below:
1) Batch Processing Tools
There are times when companies need to transfer data to another location but encounter challenges because such data are stored in obsolete forms, or are legacy data. In such cases, moving the data in batches is the best solution. This would mean the sources may involve a single or few data units, and may not be too complex. Batch Processing can also be helpful when moving data within a premise or closed environment. To save time and minimize computing power, this can be done during off-work hours.
2) Open Source Tools
Open Source Data Extraction Tools are preferable when companies are working on a budget as they can acquire Open-Source applications to extract or replicate data provided. Company employees have the necessary skills and knowledge required to do this. Some paid vendors also offer limited versions of their products free; therefore, this can be mentioned in the same bracket as Open-Source tools.
3) Cloud-Based Tools
Cloud-Based Data Extraction Tools are the predominant extraction products available today. They take away the stress of computing your logic and discard the security challenges of handling data yourself. They allow users to connect data sources and destinations directly without writing any code making it easy for anyone within your establishment to have quick access to the data, which can then be used, for analysis. There are several Cloud-Based tools available in the market today.
4) Robotic Process Automation
Many enterprises are also moving toward Robotic Process Automation (RPA) solutions for data extraction mainly involving PDFs, scanned text, invoices etc. An automated process build using RPA can use OCR (Optical Character Recognition) to scan the different set of files; collect the information extracted and store the same in a central repository. BLG (Borden Ladner Gervais), one of the Canada’s biggest Law Firm did the same using a third-party tool for RPA: UiPath by building a process robot to scan IP related notice of actions, using OCR to scan the scanned text and follow pre-defined instructions based on the information extracted and collected.
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