How ERP Database Solutions Aid Scientific Research

The emerging research field of data science is growing alongside the vast build-up of datacenters and associated infrastructure in recent years. One of the "killer-apps" driving this growth are Enterprise Resource Planning systems, or ERP, which have been a hot topic with many companies a number of years now. As businesses seek to gain greater efficiencies in time and costs, the benefits that can be derived from ERP have been tempting many entrepreneurs and business owners to take the plunge and implement the system.

A brief outline of ERP

ERP is, in very simple terms, a system that centralises data and data collection in such a way that anyone in a company or organisation can access it and use it in real time. In physical terms, rather holding data in disparate locations, on individual employees' hard drives or across servers, an organisation saves its data in a single location, often off-site on a cloud computing basis. This reduces the complications that arise from trying to maintain all the company data consistently across various departments or geographical locations. There are no separate logistics, accounting or warehousing databases, for example, just one central database to which every relevant employee and department can have access.

How ERP solutions can aid scientific research

There is more to ERP, however, than just immediate access to up-to-date invoicing and inventory information. Once a reliable corpus of data is established in a database and built up over a period of time, there are other significant benefits to be had. In these terms, ERP is part of a phenomenon that has become widely known as 'big data'. Such data can often be used, for example, to study patterns in data sets and data usage and in terms of business, to scientifically analyse ways in which further efficiencies might be found.

For example, with integrated data from various sources across a company, the manner in which the different departments interact with the same data can be tracked and behaviour with the data can be logged and analysed. Through research, this can help to find further business efficiencies in terms of who needs what data and when; it can also reveal whether existing data structures are fit for purpose in terms of the way in which the business uses them. Given the global reach of ERP and big data, there is an astonishing potential for large-scale scientific analysis of such data usage. Knowledge arising from this research can then, in turn, be fed into the design of systems that are more efficient from a business perspective. That is, in essence, analysis of data arising from ERP can help to create systems that match actual data needs, rather than forcing data to fit in with pre-defined systems.

How ERP systems are a basic need in data infrastructure

As experience with big data increases, it is becoming clear that ERP systems are now one of the basic infrastructure needs when it comes to advanced data analytics. Desired portions of data can be selected and consolidated from one or multiple sources in a data warehouse to then run all kinds of queries and pattern recognition algorithms on it. Such systems bring ever-increasing possibilities in the field of data science, the practice of deriving valuable insights from very large data sets, which is in turn becoming more visible and important due to the rapid growth of its research subjects like social networks and cloud computing.

It may not be possible to predict, with any accuracy, what the results of research into big data will bring in the future, but the contribution of data from ERP to the process helps to ensure that business interests are included in the considerations.