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DB2

DB2 is a relational database management system (RDBMS) developed by IBM. It was first introduced in the 1980s and has since gone through many iterations and updates.

DB2 is designed to manage large amounts of structured data and provides a wide range of tools and features to ensure data integrity, reliability, and security. It supports SQL (Structured Query Language), which is a standard language for accessing and manipulating data in a relational database.

Some of the key features of DB2 include:

  • Scalability: DB2 is designed to handle large amounts of data and can scale up or down depending on your needs.
  • Security: DB2 provides a range of security features, including encryption, access controls, and auditing, to ensure that your data is protected.
  • Availability: DB2 is designed to be highly available, with features like automatic failover and backup and recovery options.
  • Compatibility: DB2 is compatible with a wide range of operating systems and platforms, including Windows, Linux, and UNIX.
  • Performance: DB2 is optimized for performance, with features like data compression and indexing to ensure that queries and transactions run quickly and efficiently.

Overall, DB2 is a powerful and versatile RDBMS that is widely used in enterprise environments for managing large amounts of structured data.

Data Scientist

A data scientist is a professional who applies scientific methods, statistical algorithms, and machine learning techniques to extract insights and knowledge from structured and unstructured data. In simpler terms, data scientists analyze and interpret complex data sets to uncover patterns, trends, and insights that can be used to inform business decisions, product development, and other applications.

Data scientists are skilled in data manipulation and have a deep understanding of programming languages, statistical modeling, and data visualization tools. They work with large amounts of data from various sources, including databases, social media platforms, and sensor networks, to extract meaningful insights.

Data scientists are essential in today’s data-driven world, where businesses and organizations require accurate insights to make informed decisions. They can work in various industries, including finance, healthcare, e-commerce, and marketing, among others.

To become a data scientist, one typically needs a strong foundation in mathematics, statistics, and computer science, along with experience in programming languages such as Python or R. Additionally, data scientists must possess critical thinking skills, attention to detail, and the ability to communicate complex data analysis in a clear and concise manner.

In summary, data scientists are highly skilled professionals who play a crucial role in interpreting and analyzing complex data sets to inform business decisions and drive innovation.

Data Analyst

A data analyst is a professional who is responsible for collecting, processing, and performing statistical analyses on large sets of data. They use various techniques to identify patterns and trends in data, which can be used to inform business decisions and strategies.

Data analysts are proficient in programming languages like Python and R and have expertise in using data analysis tools such as SQL, Excel, and Tableau. They work with data from various sources such as customer transactions, web traffic, and social media interactions, among others.

Their main responsibilities include identifying data trends, generating reports, creating data visualizations, and developing data-driven solutions to business problems. They also collaborate with other professionals like data scientists, software engineers, and business analysts to improve data quality and streamline data processes.

Overall, data analysts play a crucial role in helping organizations make data-driven decisions and achieve their business objectives.

Application & Database Modernization IBM i

     In today’s fast-paced world, businesses are constantly looking for ways to streamline their operations and increase efficiency. One area that has seen significant advancement in recent years is database modernization. This innovative approach to software development is designed to help organizations bring their systems up to date and compete.

What is Application & Database Modernization?

     Database modernization implies updating an organization’s existing software systems to take advantage of data-centric technologies. This involves a combination of code and database refactoring, to create a more efficient and competitive software infrastructure that is better suited to meet the changing needs of businesses.

Benefits of Database Modernization

     There are many benefits to modernizing an organization’s code database. Some of the most important include:

  • Increased efficiency: By taking advantage of the functionality built. into DB2 (trigger programs & constraints).
  • Degrease maintenance & testing effort: No need to check the constraints the old fashion way when the operating system does it for you and secondly when the business logic is consolidated in the database with trigger programs there is no need to repeat it every time you write a new program. This will result in less coding and less testing over time.
  • Increased competitiveness: By adopting modern software development practices, organizations can stay ahead of the curve and remain competitive in their respective industries.
  • Better security: With updated software systems, organizations can take advantage of the latest security features and technologies, reducing the risk of data breaches and other security-related issues.
  • Performance: Because triggers and constraints run in the operating systems storage pool they are faster

The Process of Application & Database Modernization

     The process of application & database modernization involves several key steps:

  1. Assessment: The first step in the code database modernization process is to assess the existing systems to determine what needs to be updated and how.

  2. Code refactoring: Once the systems have been assessed, the next step is to refactor the existing code to make it more efficient.

  3. Database migration: This step involves migrating the existing database to a modern platform, such as a cloud-based solution.

  4. Testing: Once the code has been refactored and the database migrated, the final step is to test the updated systems to ensure that they are working correctly.

The Future of Database Modernization

     As technology continues to evolve, database modernization will become increasingly important for organizations of all sizes. By staying ahead of the curve and adopting modern software development practices, organizations can remain competitive and achieve their goals more effectively.

Conclusion

Code database modernization is a critical component of any software development strategy. By updating existing systems to take advantage of modern technologies, organizations can improve efficiency and become more competitive and improve security. With the right approach and tools, the future of code database modernization on the IBM i is bright and full of opportunities.

Referential Constraints IBM i

Benifits of using Referential Constraints IBM i

Accuracy – prevent orphaned records by letting the RDBMS validate the parent/child relationships between tables 

Performance  – RDBMS runs in the operating system storage pool and provides excellent performance

Functionality- The functionality provided by the constraints is all functionality that need not be performed in the programs, resulting in less coding and testing 

 

DB2 Relational Database Components IBM i

Overview of the Components that makeup DB2 on the IBM i

DB2 comes with some very powerful features

Performance – RDBMS (Relational Database Management System)  runs in the operating system storage pool. Therefore constraints and trigger programs become prioritized

Reduce Coding effort – RDBMS will enforce constraints negating the need to do so in the programs That mean’s not having to declare various master files in the programs used to verify data. That has a trickle-down effect on testing and maintenance. 

Trigger Programs. Consolidate all the validation rules in one place. Do it once in a file trigger and you no longer have to do it in multiple programs. Once again there is a trickle-down effect on testing and maintenance.

I/O servers while not strictly part of RDBMS, complement the Relational Database by establishing a border between the application and the database

 

I/O Servers IBM i

I/O Servers Provide

Border Patrol –  Separates the Database from the program.

Performance – Consolidates open data paths which reduces the size of the PAG and the program

Security – By defining the table as 1. public exclude  2 owned by a profile (with no sign-on capabilities) you are providing a high level of security. The only access is threw the I/O server.

The compelling reason for using an I/O server is to manage data definition changes as in expanding fields or getting the data type right. 

Trigger Programs IBM i

Trigger Programs: Improve performance, Reduce Application Code, after triggers replace end of day, month, and year processing resulting in data that is up to date in real time.

Improve performance: Because they run in the operating system storage pool.

Reduce Application Code: By attaching trigger programs to the file, the validation logic is consolidated into one place negating the need to do so in every application program that updates the file

Reduce Batch processing: After triggers are commonly used to replace End of Day, Month and Year processing which will keep your database up-to-date in real-time.

AO S2E Harvesting Technology

The unique AO S2E harvesting technology was developed to recover the functional design of any S2E generated application from the S2E internals (models).

All resulting application components, including all tables and data elements, are brand new, removing ANY S2E references. All components and source are NEW, with not a single line of code or element of the original product remaining. The best example of the results from this approach can be found at

http://www.i-nterprise.org/