By Henning Lund - May 16, 2022
Artificial Intelligence (AI) was the talk of the town a couple of decades ago. Today it is a reality and nobody would doubt that it is here to stay. Many IT system providers including big names as Salesforce and Microsoft started playing on the AI drums ages ago.
It is undeniable that a lot has happened in the field of artificial intelligence. There are many tasks that computers can perform better than humans: play games like chess or even diagnose diseases. The advances in deep learning are fascinating.
We may say that we are still far from true general artificial intelligence. However, the current progress within AI can already give many benefits to organizations that dare investing in a more clever future.
Daring is undoubtedly the key here. Many companies still believe that they have down-to-earth problems to solve before the AI wave really becomes tangible for them.
If you have been in the ERP (Enterprise Resource Planning) industry long enough, you will remember that the “pitch” 30 years ago was about avoiding islands of data or data silos by implementing an ERP system.
ERP systems have indeed helped a long way down the road. However, companies have started collecting an increasing amount of data as well as more complex types of data. At first, specialized IT systems such as SCM (Supply Chain Management) or CRM (Customer Relationship Management) started challenging the traditional ERP philosophy.
Today, most organizations have adopted these systems and as a result many struggle with new data islands. We have seen the rise of big data and crowded cloud data warehouses. As a consequence, keeping systems like CRM and ERP disconnected has led to unrealized potential or worse.
It is however simple and easy to resolve this challenge with appropriate data integration software. Cloud data integration tools have become simple to use and easy to implement. There is no other good reason for not implementing this if not because of a lack of time or knowledge about the potential gains.
Many business leaders have only recently understood how simple a data integration implementation project can be. Many data integration providers use cloud services to make their solutions simpler and more affordable. Today, some data integration services can be implemented remotely and in a matter of days.
A system integration between Microsoft Dynamics (365, NAV, AX, GP, CRM) and Salesforce can easily be done to avoid customer information silos. If you have been interested in data management, data pipelines or data transformation, you are most likely familiar with ETL (Extract, Transform, Load).
With ETL frameworks, data is extracted from the source system, transported via mail or FTP-servers to a place where the target system can read and load the data. This is a common way to share information and data.
Some of the first data integration projects (say for example between a mainframe SAP-based system and a mobile Microsoft Dynamics solution) could be made by simple export and import of ASCII-files (text files).
This was a complex task to define and set up. This kind of approach included extensive development time and could easily become budget nightmares. The task was technically complex and more risky than it is today.
In addition to that, data integration projects were considered as purely technical projects. They were not anchored as they are today in a larger business strategy to satisfy an ambitious company culture.
Much has happened since the early days of data integration. It is no longer necessary to extract, transfer and load data as batch jobs. Modern technologies can detect new and modified data for transfer. Most data integration tools can read and write directly between the systems you wish to connect.
Data transfers can be done one direction or even bi-directionally if this is what your business requires. XML programming can still solve many data integration challenges.
However, it is a good idea to look for a professional alternative if:
In these cases, it is highly relevant to move from a custom-developed system integration and opt for a data integration platform instead.
Solutions like RapidiOnline or the Rapidi Data Integration Platform have rich functionality to deal with any business or technical design. These tools have the ability to remove the need for additional programming.
Performance can also be significantly superior when you use a data integration tool. These solutions are robust even when the connection is poor. Finally, the implementation of such data integration solutions is rarely complex. In most cases, the system implementation can be done in a matter of days and the entire project can be up and running in just a few weeks.
Many business leaders are still waiting to get started with a potential data integration project. This is because they still fear that this type of project is by nature complex and risky. It can however be made simple.
Why do we still doubt that this can be done as a simple uncomplicated project? We do live in a society where smartphones do phenomenal things for us, things there we would not have guessed they could just 15 years ago.
Instead, some people accept to work with disconnected systems. This means that they are doomed to make double data entries, and manually convert quotes in one system to orders in the other system.
Should our phone really work better than our businesses’ customer-facing systems and financial/business operating systems?
There is no reason to keep on accepting such inefficiencies. In today’s highly competitive market, companies must fight against the lack of efficiency. They need this to keep performing, to be able to offer attractive products and services to their clients.
Disconnected systems could be what is preventing your company to truly shine.
In any case, AI must rely on correct current and updated data to perform. If you feed incorrect or outdated data to your AI systems (or any systems), they will not live up to your performance expectations.
If AI does not have accurate and sufficient data to process, it risks to provide misleading or incorrect recommendations. Eventually AI will figure out that your data is not consistent. Therefore, It is crucial to do a thorough data clean up before implementing any kind of artificial intelligence - or even “just” business intelligence.
System integration can help companies organize their data. This is the ultimate tool to secure spotless data that will allow companies to make informed decisions based on real data, accurate data.