Data integration

A database is a collection of related data which represents some aspect of the real world. A database system is designed to be built and populated with data for a certain task.

They allow for easy manipulation of the data. They are designed for easy modification & reorganization of the information they contain.  They generally consist of a collection of interrelated computer files.


  1. Improved data sharing:

An advantage of the database management approach is, the DBMS helps to create an environment in which end users have better access to more and better-managed data.

Such access makes it possible for end users to respond quickly to changes in their environment.

  1. Improved data security:

The more users access the data, the greater the risks of data security breaches. Corporations invest considerable amounts of time, effort, and money to ensure that corporate data are used properly. A DBMS provides a framework for better enforcement of data privacy and security policies.

  1. Better data integration:

Wider access to well-managed data promotes an integrated view of the organization’s operations and a clearer view of the big picture. It becomes much easier to see how actions in one segment of the company affect other segments.

  1. Minimized data inconsistency:

Data inconsistency exists when different versions of the same data appear in different places. For example, data inconsistency exists when a company’s sales department stores a sales representative’s name as “Bill Brown” and the company’s personnel department stores that same person’s name as “William G. Brown. The probability of data inconsistency is greatly reduced in a properly designed database.

  1. Improved data access:

The DBMS makes it possible to produce quick answers to ad hoc queries. From a database perspective, a query is a specific request issued to the DBMS for data manipulation—for example, to read or update the data. Simply put, a query is a question, and an ad hoc query is a spur-of-the-moment question. The DBMS sends back an answer (called the query result set) to the application. For example, end users, when dealing with large amounts of sales data, might want quick answers to questions (ad hoc queries) such as:

– What was the dollar volume of sales by product during the past six months?

– What is the sales bonus figure for each of our salespeople during the past three months?

  1. Improved decision making:

Better-managed data and improved data access make it possible to generate better-quality information, on which better decisions are based. The quality of the information generated depends on the quality of the underlying data. Data quality is a comprehensive approach to promoting the accuracy, validity, and timeliness of the data. While the DBMS does not guarantee data quality, it provides a framework to facilitate data quality initiatives.

  1. Increased end-user productivity:

The availability of data, combined with the tools that transform data into usable information, empowers end users to make quick, informed decisions that can make the difference between success and failure in the global economy.


  1. Increased costs:

One of the disadvantages of dbms is Database systems require sophisticated hardware and software and highly skilled personnel. The cost of maintaining the hardware, software, and personnel required to operate and manage a database system can be substantial. Training, licensing, and regulation compliance costs are often overlooked when database systems are implemented.

  1. Management complexity:

Database systems interface with many different technologies and have a significant impact on a company’s resources and culture. The changes introduced by the adoption of a database system must be properly managed to ensure that they help advance the company’s objectives. Given the fact that database systems hold crucial company data that are accessed from multiple sources, security issues must be assessed constantly.

  1. Maintaining currency:

To maximize the efficiency of the database system, you must keep your system current. Therefore, you must perform frequent updates and apply the latest patches and security measures to all components.

Because database technology advances rapidly, personnel training costs tend to be significant. Vendor dependence. Given the heavy investment in technology and personnel training, companies might be reluctant to change database vendors.

As a consequence, vendors are less likely to offer pricing point advantages to existing customers, and those customers might be limited in their choice of database system components.

  1. Frequent upgrade/replacement cycles:

DBMS vendors frequently upgrade their products by adding new functionality. Such new features often come bundled in new upgrade versions of the software. Some of these versions require hardware upgrades. Not only do the upgrades themselves cost money, but it also costs money to train database users and administrators to properly use and manage the new features.


  1. Growing complexity in landscape:

We alluded to this earlier. As the database market evolves, many companies are finding it difficult to evaluate and choose a solution. There are relational databases, columnar databases, object-oriented databases, and NoSQL databases. Not to mention the plethora of vendors offering their own spin on each.

  1. Limits on scalability:

The fact is, all software has scalability and resource usage limitations, including database servers. Forward thinking companies concerned about transaction processing capacity know that cataloging components, database architecture, and even operating systems and hardware configuration all affect scalability.

  1. Increasing data volumes:

As the amount of data generated and collected explodes, companies are struggling to keep up. Research shows that we’ve created more data in the past two years than in the entirety of the human race. Yet, a 10% increase in data accessibility could generate more than $65 million additional net income for a typical Fortune 1000 company.

  1. Data security:

Databases are the hidden workhorses of many companies’ IT systems, storing critical public and private data. Lately there has been an understandable and high-profile focus on data security. A data breach typically costs a company $4 million, not to mention loss of reputation and goodwill.

  1. Decentralized data management

Although there are benefits to decentralized data management, it presents challenges as well. How will the data be distributed? What’s the best decentralization method? What’s the proper degree of decentralization? A major challenge in designing and managing a distributed database results from the inherent lack of centralized knowledge of the entire database.


How to Choose the Right Database Management Solution for Your Business

So, in the face of numerous challenges, how can companies select the best management solution for their business? Here are a few recommendations.


Establish decision criteria:

The first step is to create an objective standard by which to evaluate your options. Of course each company will have different criteria. Some important considerations include cost of ownership, ease of use, functionality, ease of database administration, and scalability. Perhaps most important for businesses with long range projects, will the solution be around in 10 years?

Match the solution to your business goals

Your choice of database technology should take into account your business goals. How much data are you collecting? How fast do you collect it? How will you access and analyze it? Each business is different, thus there is no one-size-fit-all answer here.

Does it work with your existing technology?

Of course you want to avoid ending up with sprawling systems and disparate platforms. So an important consideration is whether your solution will “play nice” with existing software and hardware components.

Workload on hardware resources:

Whatever DBMS you select will be judged on database performance, or how fast it supplies information to users. It is important to remember that workload can fluctuate dramatically by the day, hour or even minute.

Take for example, the database of a retailer during a holiday shopping event. Under those conditions, the processing demands placed on the system may tax the hardware and software tools at the disposal of the system. The goal should be enabling the largest possible workload to be processed without resource upgrades.

Build confidence in your data:

Data that is secure and trusted is essential in today’s world. IBM data integration software solutions can deliver clean, consistent and timely information for your big data projects, applications and machine learning.

Govern data in real time:

Flexible and real-time data governance is needed 24×7. The IBM data integration platform massive parallel processing capabilities help manage, improve and leverage information to drive results and reduce cost and risk of consolidation.

Consolidate and retire applications:

Multiple, disconnected systems or an outdated application infrastructure can negatively impact business and increase costs. IBM data integration software solutions automate manual processes, thereby improving the customer experience and business process execution.

Business challenge:

Aiming to double the value of its real estate portfolio in five years, it should decision-makers need timely, accurate insight into portfolio data scattered across many disparate source systems.


Company is working with IBM to create an advanced, cognitive-ready analytics platform, delivering a single, trusted source of enterprise data that the company can harness to optimize decision-making.



reporting processes, freeing up time for value-added activities


trust in data and analytics, helping the business make informed decisions, faster


Identify opportunities to optimize asset yields and drive business growth