Practical Application of Data Management Tools There is an array of tools that are needed in the work of data management. These include tools to assist in data discovery, data integration, data...

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Practical Application of Data Management Tools
Introduction
Data management is an administrative process that includes acquiring, validating, storing, protecting, and processing required data to ensure the accessibility, reliability, and timeliness of the data for its users (Galetto, 2016). Data Management itself is an enormous topic covering data access, data quality, data preparation, data integration, master data management and even more (Svitla Team, 2019). In this article, we aim to look at the practical side of data management which involves the tools used from the start to the end of the data lifecycle.
The data lifecycle starts from data creation, and then moves on to data storage, usage, archival and then destruction (Stobierski, 2021). We shall analyse each of these steps and the tools which aid in each of these steps.
The Data Management Lifecycle
Data Creation:
The data lifecycle starts with data creation, which includes data generation as well as data collection by the organization in question. This means it would include everything from manual data entry, acquiring data from outside the organization to capturing data from other sources or devices.
The data creation step can be performed in a myriad of ways. Survey tools include SoGoSurvey, Survey Monkey, Google Forms, Qualaroo etc. These are all online questionnaires which can be used to collect data volunteered by participants. Data crawlers and data scrapers are usually pieces of code (written in either R, Python or Java) that can collect data by going through webpages. Data Repositories are simply data that has been stored by a third party and access to it can be bought or might even be free of charge.
Data storage:
Data storage is not just about keeping the databases somewhere, but also about the security of that...