A fully optimised data discovery solution can help you and your team easier understand your information and developing trends. This can be done in many ways, including machine learning, analysing IT systems, bringing AI to the party and using all kinds of tech to enhance your data.

A winning solution has to accomplish a number of goals to ensure the information can be processed and visualised in a way that makes it easily comprehensible and valuable for team members, department heads and stakeholders.

So, what are some of the vital elements a winning data discovery solution needs?

Let’s take a look below:

1. Discovery across all systems

In modern business, information is often found across hundreds or even thousands of locations, with shadow IT typically being present in some capacity.

Therefore, it is vital that the solution you choose has the capability to identify all your systems and locations by referencing existing sources found within your organisation. This includes (but is not limited to) CASB, CSPs, IAM, CMDB and other tools to help locate and make an inventory of your organisation’s complete digital assets.

2. It actually goes one further than discovery

The final – and possibly most important – element of an efficient solution is what it can actually do with the info once it has been correlated?

A robust system shouldn’t end at discovery: it should utilise tools to integrate with other solutions to enhance governance, security and privacy – each team in these fields has different requirements when it comes to such processes and leveraging the information provided.

For example, a privacy team has to DSARs and other information but document the processing of personal information. Security has to understand security risks whilst controlling access. Finally, governance has to apply policies, map the info’s lineage and provide access for analytical and business approaches.

3. It has a reach that goes beyond metadata

Some solutions can only scan at a base level alongside that of metadata. Not only is this not really scratching the surface, but it is typically not analysed by efficiently thus not providing an accurate insight into its value.

This can also mean that sensitive info won’t be located, thus essentially defeating the purpose of having one of these solutions in the first place! Therefore, a robust solution will go far beyond the reach of this metadata drawback, ensuring you have accurate and specific information that will help your company leverage your data more efficiently.

4. It should be highly scalable

Scalability is pretty important for modern organisations, especially when storage plays such an important role in the organisation’s ability to grow. The right solution should be highly scalable and provide a balance between scanning smaller information samples with comprehensive informational sets, essentially being a highly personalised approach that utilises the info that is most valuable to your organisation.

5. AI-friendly

AI and machine learning are essential to data classification and enhancement. However, they require the right informational sets to be efficient. You should seek a solution that trains technology on the most advanced frameworks, definitions and requirements to ensure proper information governance is in place.

Look for these features!

Don’t waste your time with a company that offers this vital, cutting-edge process but can’t provide the above advantages. A robust system should be able to cover all the bases needed to process, visualize and easily comprehend any new and developing trends, and this goes far beyond anything operating on a surface level.