Gary Allemann, MD at Master Data Management.

For many enterprises today, the data captured and retained by their IT systems are among their most valuable assets. Effective use of that unique pool of information and data optimisation can be the key to the business's continuing success in a highly competitive environment.

Yet, in many cases, companies fail to extract the maximum advantage from that potential treasure trove. This often happens because the data, as well as the infrastructure tools employed in managing it, have not been fine-tuned to best support the company’s business goals. That’s where data optimisation can help.

What data optimisation is all about?

The data that modern enterprises depend on may have many different sources and a variety of structured and unstructured formats. In many cases, it contains inaccuracies, inconsistencies, redundant information, or other anomalies that make it unnecessarily difficult to access critical information promptly and comprehensively.

The data optimisation process makes use of sophisticated data quality tools to access, organise, and cleanse data, and to maximise the speed and comprehensiveness with which pertinent information can be extracted, analysed, and put to use. That enhanced availability of critical information provides businesses with significant benefits. Let’s take a look at some of them.

Agility and flexibility in decision-making

In today’s business environment, threats and opportunities can appear with lightning speed, and a company’s very survival can depend on how quickly it reacts. The key is having timely access to good information. But pulling together data from disparate sources and formats, even with automated tools, can be a time-consuming and error-prone endeavour.

Data optimisation alleviates that problem by restructuring datasets and filtering out inaccuracies and noise. The result is usually a significant increase in the speed with which actionable information can be extracted, analysed, and made available to decision-makers.

Performance that meets customer expectations

In the internet age, customers have come to expect—and demand—speed, accuracy, and comprehensive information from the businesses they deal with. Whether the interaction is online, by telephone, or face-to-face, customers expect front-line personnel to be able to respond quickly, with accurate and pertinent information. Data optimisation is often the key to providing real-time service that meets customer expectations.

Enhanced company reputation

Poor data quality can produce inaccuracies and inconsistencies that reduce the perceived trustworthiness and utility of the information that is critical to the operations of the business. The result is often the introduction of confusion, delay, and the potential for conflict in transactions with customers, business partners, and even employees. The improvement in data quality brought about by the data optimisation process minimises a company’s exposure to such problems and enhances its overall reputation.

Increased ROI for IT infrastructure and staff

The infrastructure tools used for optimising data also provide insight into the performance of the server, storage, network, and system software components of a company’s IT operations. Having access to such information greatly facilitates tasks such as planning, troubleshooting, and forecasting, resulting in more efficient use of hardware and software resources, and IT staff personnel.

Maximised IT availability and flexibility

Many enterprises today are moving to a multi-cloud model for their IT operations, not only to take advantage of the unique capabilities of each platform but most importantly, to protect themselves from the effects of a cloud provider unexpectedly going offline. Because the various cloud platforms have different native storage formats and analytical tools, optimising and perhaps compressing data before sharing it between platforms can greatly facilitate the implementation of a multi-cloud strategy.

Data optimisation is worth the effort!

The optimisation of a company’s data and the infrastructure that supports it requires an investment of time and resources. However, the payoff from that investment can be substantial.