Discussion 1knowledge Centric Organizations Have Incorporated Modern T ✓ Solved

Discussion 1 Knowledge-centric organizations have incorporated modern technological systems in their creation and management of knowledge. In a business organization, the knowledge-centric department is dedicated to creating and updating knowledge as part of strategic thinking and business operations. It is possible to achieve knowledge centricity when there are sufficient systems associated with its creation and management embedded in the organization’s structure (Eini, 2018). Modern technological systems for data storage and management have played a critical role in the success of knowledge-centric organizations. Provide a suitable database is chosen, the organization involved can do well their routine operations related to knowledge acquisition, utilization, and storage.

While databases in knowledge-centric organizations have been of paramount importance in improving efficiency, some challenges accompany the process. Poor choice and implementation of a database can pose a severe setback to the organizational operations. One of the most significant challenges facing modern database systems is data security. Over a hundred thousand systems have been hacked in the last two years because their databases are vulnerable to malicious groups on the public internet. The vulnerability in most of these database’s stems from poor normalization.

Eini (2018) states that there are databases designed on the fly without paying close attention to the basic rules of normalization. Without the third normal form, the end-user may delete records instead of querying or inserting them. Similarly, several databases are subject to an improper performance criterion. Sometimes the incoming data might be exponentially rising in capacity and continue satisfying user needs; there is a need for high-speed processing without taking through hoops. Performance facing many knowledge-centric organizations stems from deploying a poor default and recognizing the operational environment.

Therefore, in practice, some databases are not flexible enough to adapt dynamics of rapidly changing atmosphere. According to Eini (2018), a database should be designed for high-performance regardless of the hardware. A database that works well in older machines and small-sized systems such as Raspberry Pie implies good default performance. Date safety is another challenge facing modern database systems in knowledge-centric organizations. Some databases can quickly lose data for reasons related to poor user-interface, software- or hardware-related issues.

Some databases do not guarantee ACID, especially when a fully transactional operation is involved (Eini, 2018). Whenever losses occur, the organizations may lose critical information leading to an extended downtime while seeking to recover the loss. Sometimes, customers may shun the organization’s services and migrate to other companies. Therefore, while databases promise data security, others may fail to meet this expectation through data losses. Reference Eini, O. (2018).

How to overcome five common database challenges - JAXenter. Retrieved 22 February 2021, from Discussion 2 Database is one of the most important pieces of technology and it is implemented in every organization. All the business data is stored and archived for several years. There are only few named vendors in market who provides this Database services and software’s. The primary target for the hackers would be breaching the database to collect the business information.

So, it is critical tool that effects the functionalities of overall business. One of my personal experience in dealing a poor database is with my previous client. They have chosen to use an open-source database client and customize it according to their needs. They Plan to end the contract with one of the big companies like Oracle who was providing this service for an amount. Due to different and multiple developments in technologies the database became a simple open source.

Using an open-source software is a good option in client budget perspective but at the same the number of risks is grater when compared to vendor supported platforms. Our infrastructure architect used this open source and customized it according to business needs. After few we started noticing how poorly this was customized and found some security vulnerabilities. Due to the poor configurations, the data stored was unorganized and became unresponsive for every 24 hrs. The tables stored were saved with different file permissions and allowing other users to easily access this data.

The stored data was not fully encrypted and stored with easy password in one file. The connection pools set are very less and takes lot of time to respond. All this issue would have been resolved if the open source is properly customized. The other solutions would be a proper planning, peer analysis before implementing and a strong team with enough Database knowledge. Any changes to Database showed be tested thoroughly and reviewed multiple time before implementing the change.

References: Berg, K. L., Seymour, T., & Goel, R. (2012). History of databases. International Journal of Management & Information Systems (IJMIS) , 17 (1), 29–36. Garcia-Molina, H. (1992).

Main Memory Database Systems: An Overview. Retrieved from, Kraleva, R. S., Kralev, V. S., Sinyagina, N., Koprinkova-Hristova, P., & Bocheva, N. (2018). Design and analysis of a relational database for behavioral experiments data processing.

International Journal of Online Engineering (IJOE), 14(02), 117. Discussion 3 Poor Database design and its impact on the organization: Data plays a very important role in every organization. It is very important for every company to store the data in a safe and secure way. All the hackers would eventually target the data when they are trying to enter any system without proper authentication. So, it is very vital to store the data in a very safe way. (Pascal, 2020) The definition of well-defined data is that it maintains all the encryption for storing any sensitive information.

Every organization should make sure that they are not storing any unnecessary data. If so, it will cause an extra burden on the company to store and retrieve that information. It also should make sure that the data is well normalized before storing. Analysis on Cause of the Problem and a Potential Solution: The cause of the problem that I am discussing has occurred because it has failed to comply with some basic rules of data storage. It tried to store some confidential information and it also did not encrypt the data before storing it.

So, when the hackers entered into the system via SQL injection, they noticed that the data is not so secured in storing and got hold of much confidential information. (Khanuja, Adane, 2018) The cause for this problem is that there are no proper validations for the application they designed in, so this made the hackers enter the system. After entering the system, the second cause for the data loss is the way they stored the data and they also have not maintained a secured connection between the database server and the application server. So, this is the second cause. (Shelly, Pradeep, 2019) References: Pascal, F. (2020, March). What First Normal Form really means and means not? Retrieved Oct 1, 2019, from Database Debunkings: Khanuja HK, Adane DS.

Database security threats and challenges in database forensic: A survey. In Proceedings of 2018 International Conference on Advancements in Information Technology (AIT 2011), available at pics. com/vol20/33-ICAIT2011-A4072. pdf 2018. Shelly Rohilla, Pradeep Kumar Mittal, Database Security: Threats and Challenges, International Journal of Advanced Research in Computer Science and Software Engineering, Volume 3, Issue 5, May 2019. Discussion 4 Poorly implemented database Poor database refers to the problems faced while constructing the database in the project environment. According to our requirement, database type can be changed, and the procedure for building can be designed.

The front end helps to decide the back-end requirement, and that plays a significant role. Back end is also called a database, and connections can be established to store data from front end to back end. The poor database describes the problems and challenges involved in the database. According to my experience, problems of the database include poor Normalization (Durga & Jeyaprakash, 2019, July). Normalization is defined as a systematic approach of decomposing large tables to smaller and eliminates the data redundancy.

Here redundancy refers to the reputation of data. It carries some undesirable characteristics like deleting anomalies, inserting, and updating. So, here Normalization plays a major role in database design. It has different forms according to the form requirement table designing can be utilized. Poor Normalization refers to the implementation of normal forms in the database that are not procedural and not up to the best.

Decomposing the large tables into smaller ones helps to better understand, and storage capacity will be reduced. Data loss can mean huge losses for any company. Even though the company follows a lot of data storage practices, there is a big possibility that mistakes will occur. Without utilizing it properly, it will create a lot of problems in the database, like the repetition of data can cause primary key issues. It also lost its uniqueness.

For example, a website accepts registration forms and providing a user account to the user, and that website not implemented normal forms properly. Here the problems will appear like they will register with user id as ‘111’, and other users also registered with the same id. Therefore, the first user id can upload his personnel data, and the second user id also accesses the same data, sharing their data without securing their accounts. It will create many problems while dealing with different transactions. So, Normalization plays a major role in building the database (Walach, et al., 2018).

References Durga, V. S., & Jeyaprakash, T. (2019, July). An Effective Data Normalization Strategy for Academic Datasets using Log Values. In 2019 International Conference on Communication and Electronics Systems (ICCES) (pp. ). IEEE.

Walach, J., Filzmoser, P., & Hron, K. (2018). Data Normalization and Scaling: Consequences for the Analysis in Omics Sciences. In Comprehensive Analytical Chemistry (Vol. 82, pp. ). Elsevier.

Paper for above instructions

The Role of Modern Technological Systems in Knowledge-Centric Organizations

In contemporary business environments, knowledge-centric organizations have significantly integrated modern technological systems into the creation and management of knowledge. This integration not only facilitates the acquisition, utilization, and storage of knowledge but also enhances operational efficiency. A well-designed database serves as the backbone of these efforts, allowing organizations to harness their data for strategic decision-making. This paper discusses the importance of databases in knowledge-centric organizations, challenges related to their implementation, and best practices for optimizing database operations.

The Importance of Databases in Knowledge-Centric Organizations

Databases are fundamental to the effective management of organizational knowledge. They store vast amounts of data in structured formats, enabling efficient retrieval and analysis. According to Eini (2018), a significant aspect of achieving knowledge centricity is through the systems that are established for the creation and management of knowledge. These systems must be integrated into the organizational structure, ensuring that data management aligns with business operations and strategic goals.
Moreover, modern databases support advanced analytical capabilities that allow organizations to analyze trends, forecast outcomes, and make data-driven decisions. For instance, relational databases offer robust querying capabilities, enabling organizations to extract meaningful insights from their data (Berg, Seymour, & Goel, 2012). The implementation of databases has transformed how organizations store, manage, and utilize information, fostering an innovative environment conducive to growth and adaptation.

Challenges Associated with Database Management

Despite the benefits, there are several challenges associated with database management in knowledge-centric organizations. A primary concern is data security, particularly given the rising incidence of cyberattacks. In the past two years alone, over one hundred thousand systems have been compromised due to vulnerabilities in their databases (Eini, 2018). Such vulnerabilities often stem from poor normalization practices, where databases are designed haphazardly without adhering to established rules.
Normalization is critical for structuring data efficiently and avoiding redundancies. Poorly normalized databases can lead to several complications, including loss of data integrity and difficulties in data retrieval. For example, without proper normalization, end-users might accidentally delete important records instead of performing intended actions like querying (Eini, 2018).
Another challenge is performance-related issues that arise from choosing an unsuitable database design or configuration. Many organizations face limitations due to their database systems not being optimized to handle high volumes of incoming data efficiently. For instance, if a database is not capable of processing large datasets quickly, it may hinder operational capabilities and negatively impact user experience (Eini, 2018).

Specific Case Study: The Risks of Poorly Designed Databases

A case example illustrating the risks of a poorly implemented database is a project involving an open-source database client that was customized for business needs. Although cost-effective, the decision to transition from a vendor-supported platform, such as Oracle, to an open-source solution created substantial risks (Discussion 2). The customization efforts led to vulnerabilities in the system, causing unresponsive behavior and security breaches.
For instance, inadequate encryption and poorly set file permissions made sensitive data easily accessible to unauthorized users. Additionally, the connection pools were insufficient, leading to slow responses and operational disruptions (Discussion 2). This illustrates how critical it is to invest in well-supported and robust database solutions instead of opting for cheaper, less secure alternatives.

Best Practices for Optimizing Database Operations

To mitigate the risks associated with poor database design and management, organizations should adhere to specific best practices. First, thorough planning and analysis before database implementation are essential. Organizations must assess their needs carefully and identify the right database technology that aligns with their operational requirements. Conducting peer reviews and leveraging insights from experienced personnel can aid organizations in making informed decisions about database configurations (Discussion 2).
Second, regular audits and testing of the database's performance are vital. Organizations should monitor how their databases handle data loads and run performance tests to identify bottlenecks or vulnerabilities. This enables enterprises to adjust configurations proactively, ensuring the database is optimized for high performance even as loads fluctuate.
Third, robust security measures are paramount. Implementing encryption methods for sensitive data, establishing strict access controls, and regularly updating systems can significantly reduce the risk of data breaches (Discussion 3). Training employees on security practices and the importance of data integrity can further strengthen organizational defenses against cyber threats.
Lastly, maintaining proper normalization practices is essential. Ensuring that databases are structured correctly not only enhances data integrity but also improves operational performance. Organizations should invest in training for database administrators on the principles of normalization and the implementation of best practices in database design (Discussion 4).

Conclusion

In conclusion, knowledge-centric organizations are increasingly reliant on modern technological systems for effective knowledge management. The success of these systems largely depends on the strategic implementation of databases and the adherence to best practices surrounding design, security, and performance optimization. Addressing the potential challenges that come with database management is crucial for organizations to harness the full potential of their data, ultimately driving business innovation and success.

References

1. Berg, K. L., Seymour, T., & Goel, R. (2012). History of databases. International Journal of Management & Information Systems (IJMIS), 17(1), 29–36.
2. Eini, O. (2018). How to overcome five common database challenges - JAXenter. Retrieved from [https://jaxenter.com](https://jaxenter.com).
3. Garcia-Molina, H. (1992). Main Memory Database Systems: An Overview.
4. Kraleva, R. S., Kralev, V. S., Sinyagina, N., Koprinkova-Hristova, P., & Bocheva, N. (2018). Design and analysis of a relational database for behavioral experiments data processing. International Journal of Online Engineering (IJOE), 14(02), 117.
5. Khanuja, H. K., & Adane, D. S. (2018). Database security threats and challenges in database forensic: A survey. In Proceedings of 2018 International Conference on Advancements in Information Technology (AIT 2011).
6. Durga, V. S., & Jeyaprakash, T. (2019). An Effective Data Normalization Strategy for Academic Datasets using Log Values. In 2019 International Conference on Communication and Electronics Systems (ICCES).
7. Walach, J., Filzmoser, P., & Hron, K. (2018). Data Normalization and Scaling: Consequences for the Analysis in Omics Sciences. In Comprehensive Analytical Chemistry (Vol. 82, pp. 1-30).
8. Pascal, F. (2020). What First Normal Form really means and means not? Retrieved from [https://databasedebunkings](https://databasedebunkings).
9. Shelly, R., & Mittal, P. K. (2019). Database Security: Threats and Challenges. International Journal of Advanced Research in Computer Science and Software Engineering, 3(5).
10. Discussion contributions (1-4). Data provided from an ongoing class discussion on database management challenges and solutions.