Use Multi Model DBMS Technology To Improve Data Quality In Essay.

Improving Data Quality in Large and Small Enterprises

Discuss about the Use Multi Model DBMS Technology.

Information is considered as a primary asset for any of the enterprises in the present scenario. An enterprise manages and handles information that is of varied type and also varies in terms of the volume. It becomes necessary for the organizations to manage the variety and volume of the information. Enterprise Data Management is a discipline that includes and involves a number of different technologies for the efficient and adequate management of information. Hype cycle that is presented by Gartner explains the EDM technologies in the form of a curve that shows the technologies that are trending, emerging and the ones that are less likely to be used and applied in the present times. Data quality is one of the most important properties and parameters that can be achieved using the technologies that are listed in the Gartner’s Hype cycle (Ronthal and Simoni, 2015). The report has been written on Multi-Model DBMS Systems as the technology.

Quality of data shall be maintained and managed in the enterprises irrespective of their size.

For the large scale enterprises there are several employees that are associated with the organization that can be 10,000 or more in numbers. These employees are spread over different office units and the non-human resources are also installed in various locations as per the office units. Enterprise data is transmitted in various human and non-human entities that are present at different locations and it therefore becomes necessary to ensure that proper standards are followed so that there is no compromise on the quality and consistency of the data. If the quality of the data is not managed and maintained then there may be various issues that may emerge such as redundancy and duplicity of the data. The same applies to the small scale enterprises as well. There are lesser resources engaged with the small scale enterprises but the need to make sure that the data quality is maintained is high. Absence of the adequate quality of data can lead to several issues in terms of inefficiencies in the business activities and likewise.

With the emergence of these needs and requirements of the enterprises, there are various automated technologies and processes that have been created for the adequate management of the quality of data. These technologies are applicable in large as well as small scale enterprises.

Multi-Model Databases are defined as the databases that support more than one data models simultaneously. It is a data processing platform that allows the organization to store and arrange the data that is associated with the enterprise with the aid of multiple data models.  There are several advantages that are provided by the multi-model database technology as it allows the enterprises to meet several different requirements instead of making use of multiple database systems (Ciosummits, 2017).

About Multi-Model Database Technology

There are various types of database systems such as relational databases, hierarchical databases and many more. In case of multi-model database systems, all of these database types come together as a single unit. There are a number of NoSQL databases that follow multi-model database technology as its base technology. There are various enterprises and organizations that are now making use of multi-model database technology in their architecture (Lu, 2017).

• Multi-model databases support platforms for different types of use cases and have the ability to consolidate all of them together on a single platform. It provides a great degree of flexibility in terms of the query language and provides good storage capability as well.
• There are scenarios wherein the database requirements of an enterprise may increase or decrease as per the project specifications and needs. Multi-model databases can be easily used to provide the quality of performance scaling to the enterprises as these databases can be easily scaled up and down (Oliveira & Cura, 2016).
• When there are more than one database systems and types present in the organization then the reliability of the database systems may reduce. In case of multi-model databases, the reliability of the data and information that is present in the databases is not compromised at all. There is lesser time that is spent in the coordination and processing of the data and information in the multi-model database technology (Bocquet, 2008).
• It is often observed that data consistency is compromised at some level due to the presence of huge clusters of data and multiple data systems in the enterprises. Database transactions are required to maintain ACID properties as atomicity, consistency, isolation and durability. These properties are not adhered and there are severe impacts of the same. However, consistency is easier to maintain in multi-model database systems as it has a single platform for all the database types.
• The cost of the multi-model database systems is much lesser than the individual database systems that are deployed in the enterprises. Cost of installation along with the cost of maintenance is much lesser in case of multi-model database systems. There are also more bugs that come up in the database systems if installed separately and there is a lot of cost that is spent in the resolution of these bugs. In case of multi-model database systems, this share of cost is also easily avoided.
• Multi-model database systems have higher fault tolerance as compared to the individual database systems.

Enterprise Data Management is a vast discipline and there are several activities that come under the same. It is necessary to make sure that some of the essential requirements are met and Multi-Model DBMS technology has the capability to fulfil all of such requirements and necessities.

Data Migration

In case of the application of a new technology in the enterprise or any set-up, the existing elements need to be migrated as per the new technology that is implemented. Multi-Model database systems have the capabilities that can ensure the smooth and easy migration of the existing data elements as per the new technology.

Data Integration

A strong integration of the data sets and the information contents that are present in the organization is necessary so that the business activities can be adequately carried out. Data integration shall therefore be present in the technologies that are implemented and capability is ensured in case of multi-model database technology.

Data Maintenance

Maintenance of the data is essential in association with the enterprises and multi-model database technology has the measures to carry out easy and smooth maintenance of the data (Faircom, 2015).

Data Quality Assurance

If the quality of the data is not managed and maintained then there may be various issues that may emerge such as redundancy and duplicity of the data in large scale enterprises. The same applies to the small scale enterprises as well. There are lesser resources engaged with the small scale enterprises but the need to make sure that the data quality is maintained is high. Absence of the adequate quality of data can lead to several issues in terms of inefficiencies in the business activities and likewise. Multi-model database technology ensures that quality of the data is assured at all times (Datafloq, 2017).

Data Retention

Certain data sets lose their requirement over the passage of time and these sets are then required to be removed. Multi-model database technology has the mechanisms to identify and carry out such procedures.

Multi-model database technology provides a number of benefits for the large enterprises. There is a lot of data that these large enterprises are required to manage and handle. With the use and installation of multi-model database systems, the management of the data along with the execution of a number of data related operations become easy.

Features of Multi-Model Database Technology

Data redundancy is one of the most common problems that have been observed in association with the large scale organizations. It is because of the reason that there are a lot many data sets that are present in the organizations and the monitoring of the same is not done adequately. Multi-model database technology makes sure that the problem of data redundancy is not present (Krebs, 2016).

Multi-model database technology also makes sure that the data analysts and data experts can easily carry out master data edits on the data sets. With the aid of these master data edits, it becomes possible to ensure that integrity of the data is maintained and there are is no violation in terms of the data integrity on any of the data sets that are present in the enterprise.

Security and access control are two of the most significant benefits that can be achieved with the implementation of multi-model database technology. It allow the access to only the authorized entities.

Data analysis is required and is essential for every enterprise and its necessity increases for large scale enterprises. It is because of the involvement of huge data sets which makes it necessary to carry out data analysis so that significant patterns and trends can be understood after the process of data analysis.

Quality of the data is maintained and ensured by multi-model database technology which in turn leads to the achievement of business activities and business operations as per the business requirements and specifications.

Multi-model database technology also makes sure that the employees that are present in different geographical locations can securely access the data that is associated with the enterprise.

There is a great degree of uncertainty that is associated with the small scale organizations in terms of the data usage, data volumes, and data specifications and likewise. It leads to the requirement of the technology that is scalable and flexible in nature. Multi-model database technology provides the same ability to the enterprises.

Security of the small scale organizations is not advanced and there are certain security loopholes that are observed in these organizations. These can have impact on the data that is associated with the enterprises as there may be a number of security risks and attacks that may take place. Multi-model database technology makes sure that the security of the data sets is enhanced and is improved (Lam and Taylor, 2016).

Data quality along with the usability of the data is improved with the implementation of multi-model database technology in the small scale organizations. This leads to the maximization of the customer base that is associated with these enterprises.

The business operations and processes are not very advanced and mature in the small scale organizations. Multi-model database technology makes sure that a proper standard is followed in terms of the maintenance and management of the data sets that are associated with the enterprises (Backaitis, 2016).

Conclusion

The most important asset that is present and is associated with the enterprises in the current scenario is the information and data sets that are present with these enterprises. These data sets have varied properties and attributes related with them in terms of volumes, types, specifications etc. There are technologies that have been developed so that the enterprise data can be efficiently managed and handled. Multi-Model Database is one such technology that has allowed small scale and large scale enterprises to efficiently manage the data that is associated with them. There are several benefits that are provided by this technology to these enterprises in terms of removal of data redundancy along with strengthening of data quality and flexibility. Also, integration of the business activities and IT processes is also easily carried out with the implementation of multi-model databases in the enterprises. There are certain requirements that shall be met with any of the technology that is defined under EDM such as migration of the data sets, assurance of the data quality, enhancement of data security along with retention of data sets. All of these requirements are easily met by multi-model databases which make it a preferred technology by the large and small scale enterprises

References

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Bocquet, A. (2008). Benefits of multi-model architecture-based development for railway applications. [online] Available at: https://uic.org/cdrom/2008/11_wcrr2008/pdf/PS.2.15.pdf [Accessed 22 Jun. 2017].

Ciosummits (2017). The Multi-Model Database Cloud Applications in a Complex World. [online] Available at: https://www.ciosummits.com/Online_Assets_DataStax_Whitepaper_-_The_Multi-Model_Database.pdf [Accessed 22 Jun. 2017].

Datafloq (2017). Multimodel Databases. [online] Datafloq.com. Available at: https://datafloq.com/big-data-open-source-tools/os-multimodel/ [Accessed 22 Jun. 2017].

Faircom (2015). A True NoSQL MultiModel Database. [online] Available at: https://www.faircom.com/wp-content/uploads/1603ShowFlyer2.pdf [Accessed 22 Jun. 2017].

Krebs, A. (2016). VistA’s Multi-model Database | OSEHRA. [online] Osehra.org. Available at: https://www.osehra.org/post/vista%E2%80%99s-multi-model-database [Accessed 22 Jun. 2017].

Lam, V. and Taylor, J. (2016). Enterprise Information Management (EIM): The Hidden Secret to Peak Business Performance. [online] Available at: https://www.umsl.edu/~sauterv/DSS4BI/links/EIM_Final.pdf [Accessed 22 Jun. 2017].

Lu, J. (2017). Multi-model Data Management: What’s New and What’s Next?. [online] Available at: https://udbms.cs.helsinki.fi/assets/tutorials/edbt2017-multi-model-data.pdf [Accessed 22 Jun. 2017].

Oliveira, F. and Cura, L. (2016). Performance Evaluation of NoSQL Multi-Model Data Stores in Polyglot Persistence Applications. [online] Available at: https://dl.acm.org/citation.cfm?id=2938518 [Accessed 22 Jun. 2017].

Ronthal, A. and Simoni, G. (2015). Hype Cycle for Enterprise Information Management, 2015. [online] Gartner.com. Available at: https://www.gartner.com/doc/3096424/hype-cycle-enterprise-information-management [Accessed 22 Jun. 2017].