Data management is a managerial process that involves obtaining, confirming, storing, protecting, and processing the required data to ensure adequate availability, reliability, and timely access to information to its end users. The computer system is a technological aspect that helps in simplifying data processing activities and improving reliance on modern technology in business and personal life affairs. Analyzing data and navigating the database software and database design and planning are the critical management skills essential for managing and using computer-based information. Understanding data and database analysis constitute an integral component of data management.
Is Big Data a Database?
Big data is a database that promotes the blending of data together by an organization that can be translated into the final information using computer learning languages and modeling procedures, and other advanced analytical applications. The systems which store data are the major components of data management platforms in various organizations (Bai, 2018). Big data can be divided into multiple categories depending on the environment and architectural media in which it is stored. Extensive data systems define the nature of the system in which that information is being held.
Organization prefers using large data hoarded in their systems to advance procedures, provide improved customer services and create better marketing platforms based on the client preferences aimed at improving company profitability (Yan et al., 2020). Big data can also hold a competitive advantage over the company lacking enormous data, thus promoting competitive advantages. It enables the company to make an informed decision, provided the data is being used effectively.
Big data is a different database from standard databases, and it is an advanced technology from the traditional standard database. The traditional Database is used for the storage and procession of structured data efficiently. The authoritative Relational Database uses tabular to store data and embrace the Structured Query Language (SQL) to access and retrieve the information (Tsou, 2019). Big data is a form of data that combines both unstructured and semi-structured data. It is also helpful for developing and embracing data-driven intelligent applications.
The world is changing at a very high speed such that companies are facing unprecedented time. There is a need to process an enormous amount of related information to scrutinize and forecast human and machine comportment. Big data embraces the fast growth of structured, unstructured, and semi-structured data. According to speed evaluation, it can generate more than 50,000GB of data per second; the data caused needs to be stored and processed efficiently at this speed.
Due to the nature of big data in terms of data management challenges, such as increased volume, velocity, and variety of data processed per second, it becomes difficult to solve those challenges using traditional databases. Much of enormous data processing took real time and produced on a considerable scale. As a result, there is always the need to incorporate modern storage platforms to cater to larger output. Therefore, Big data is a database that requires more sophisticated platforms for processing and storing the facts. It is more of a semi-structured and unstructured form than a standard Database.
The Relations Between Big Data and Database
The demand for accessing big data grows day by day because it provides a platform for businesses to have a competitive advantage. It comprises sensitive information and confidential organizational information, which can be used to analyze and maneuver around the dynamics of market strategies. Although big data and Databases have been around for a long time, the relationship between them is still a novelty. The need to process accurate, reliable, and better data requires a database that will minimize the high costs of data processing procedures.
A database is a storage of data, whether big or small; it stores data in a relational model with various entities normalized. A relational database encourages consistency rather than partitioning the thresholds needed on numerous parameters of data operations. Big data embraces technology that processes vast data without the use of database techniques and technological aspects. Big data and Databases are two different sets of technologies used to manage data, depending on the user’s decisions.
The Similarities and Differences Between A Big Data and Database
Both big data and Databases are used to manage data depending on the user decisions. They are the platforms used to ensure information is available for management to understand market volatility and gain a competitive advantage. Both Database and big data are used to promote operational efficiency, improve customer services, and allow modern businesses to utilize outside intelligence while making critical decisions. Big data is different from Databases as it applies data sets whose capabilities are beyond the traditional relational Database (Shaba, 2018). A database is an assemblage of organized data to be captured and managed efficiently and updated for business use.
Enormous data refers to modern technology and initiatives that involve information that is too diverse in terms of skills, conventional technologies and infrastructural considerations. A database management system generates data from the Database in retort to various inquiries but in a restricted manner. Data in big design has varied data that can be used differently; organizations can refer to the data generated through big data for comparison and elimination of unnecessary contexts while the Database can be defined through some schema.
Big data is challenging to store and process, while Databases can be easily stored and process. The nature of big data is enormous, focus on a variety of handling structured and unstructured data. Data processing should be done at a considerable speed, this promotes effective execution of varied activities within the organizations. For example, Facebook can generate a lot of materials per day while YouTube uploads videos quickly due to availability of adequate database. The Catalogue can be slow since the data is only stored and accessed for processing.
The Database Used for Big data
The database and data warehouse can be used to process information in the world of big data. The Database can be used to manage vast reservoirs of both structured and unstructured data. Some of the database use of data include the Cassandra, which is a NoSQL database. It is used by various organizations with more extensive data such as Twitter, Netflix, and Cisco. HBase is a database used for non-relational data for linear and modular scalability.
The other databases used for Big data includes MongoDB, which is designed for supporting humongous Database. The Riak is a database believed to be the most powerful in the production process (Amiriparian et al.,2017). Users of this Database include the Danish Government and Dot cloud. Hibari is another database used by telecom companies to store data with solid consistency and ensure high availability and past performances. The other databases include Flock DB, Territory, OrientDB, and CouchDB.
Data management is an essential aspect of the modern environment; it ensures the complete flow of information required by management for decision-making. Big data represents the technological aspect used by various institutions to ensure effective dissemination of information to the end-user. It is the type of Database that focuses on both semi-structured and unstructured information processes. It also uses various databases as are means of achieving the optimal goal of the information process.
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Shaba, N. J. S. (2018). Large Data Database: Loopholes regarding Ownership and Access to Data.
Tsou, M. C. (2019). Extensive data analysis of port state control ship detention database. Journal of Marine Engineering & Technology, 18(3), 113-121.
Yan, X., Sedykh, A., Wang, W., Yan, B., & Zhu, H. (2020). Construction of a web-based nanomaterial database by immense data curation and modeling friendly nanostructure annotations. Nature communications, 11(1), 1-10.