Prontoux | Data Integration

Modernizing Data Integration with robust enterprise solutions to connect data in a fast and scalable way.

Data Integration

We are living in a developing IT world where technology change happens almost on a daily basis.

And with the emergence of numerous technologies and ideologies to store data across multiple platforms, it is given that enterprises will look out for options which are more suited to their needs and are budget friendly at the same time. However, this gives birth to an array of challenges which needs to be considered and evaluated carefully before taking the plunge.

The concept of “Data integration” comes up with organized and systematic way of handling these problems.

Some of the most critical and commonly occurring use cases based on our interaction with multiple customers are:

Creating and maintaining a single source of truth

Hybrid approach to data storage

Adopting a new database management system

Warehousing and Reports

Data analytics

Problem Statement

01.

The world today is dealing with data boom. And we are looking at the future where the more data you have, more successful you would be. So, it’s imperative that enterprises will look beyond conventional ways of acquiring and storing data. Distributed database systems come as one of the ways to do that. Having multiple heterogeneous database systems is also what many opt for.

02.

The challenge that arises out of it, is maintaining a single source of truth. It is very critical as well because warehousing, reporting and analytics all depend on a reliable data source which can cater all the needed data.

03.

Another challenge which is very common, is what to do with existing data while adopting a new database system. From data format to data model and architecture, everything can change while doing such adoptions and abandoning existing or even a slight loss in data may result to substantial revenue loss.

Existing solutions and why they are not enough:

Such is the world of technology that with every problem, a wide spectrum of solutions comes out each claiming to be solving all the use cases. But as a matter of fact, most of them fail at one point or other. There are multiple reasons for such failures. Some of them are:

01 Lack of understanding of source data:

The first risk to the success of Data Integration projects is lack of knowledge about the source data that is going to be used to populate the target system. A lack of knowledge means things like:

Unexpected values, formats and combinations of values.
Misspellings
Data which is wrong or simply in the wrong place
Duplicates
Missing information
Hidden or embedded information

People assume that data which is used by existing applications will be suitable for a completelydifferent use case. They seem to forget that they have spent years developing and maintaining the existing applications to cope with all non-standard eventualities, and they do not realize that the new use case is unlikely to have the same requirements.

02 Non-Flexible and Non-Scalable data modelling structure:

Many software and tools attempt to convert data into a common format which works well for data warehousing use cases, but that’s not good enough when dealing enterprise level solutions. It requires business and application specific architecture and data models.

03 Hardware and Infrastructure considerations:

While moving to a new database system or having synchronization and communication between multiple heterogeneous and hybrid data sources, infrastructure requirements are of paramount importance. Some of the key points to be considered are:

Computation capabilities
Memory requirements
Storage capacity
Network bandwidth requirements

04 Relational vs Non-Relational:

This is one of the most popular topic of debate while talking about new budget friendly, easily scalable and emerging database systems.

Emergence of Non-relational database system from relational database systems is a paradigm shift. And the inertia of comfort makes it difficult to adopt to new architecture. In fact, even after adoption of non-relational system, application architectures are still designed with the mindset of relational systems. To deal with it, a solution is needed which not only gives a way of moving data between relational and non-relational system, but also educates and guides on what needs to be done.

In the ever-changing technical world, when everyone is looking at the future, data integration lies at the core for enabling it. With proper application of futuristic solutions, it can be made much simpler and achievable without the risk of data loss and all the problems that come along with it.

The Prontoux Solution:

Each enterprise has its own way of handling their data, so the solution has to be custom built.

However, we do understand that there are a lot of issues which are very common and are faced by all.This is the reason why we have adopted a hybrid approach to data integration in our services and solutions.Our feature rich application deals with all the above-mentioned use cases and is highly customizable.It has a very interactive GUI to map data from source to target which suits both relational and non-relational and hybrid data transfer and synchronization. The application not only facilitates with different features, it also guides user to do it effectively, highlighting all the best practices. It has both the capabilities of one time data load and real-time data replication.With custom built powerful data transformer at its core, it provides flexibility and scalability to model data which suits more to customer specific needs instead of having a fixed data modeling approach.And since, it is designed to adapt and scale to future systems, it can be easily molded and customized for any specific use case based on customer demands.