There is an ongoing perception that investing in data and analytics comes with a significant complete digital transformation price tag. This can cause many organisations to hesitate and ultimately fail to capitalise on the opportunity.

However, there is a lot that organisations can do quickly to start generating insights into their data, and it starts at automation.

With data, automation is the key goal. Generating meaningful insights from data in modern environments to make critical business decisions comes from having the right structures and teams, but equally and especially given the size of the datasets involved, it rests on having the right automation in place.

This is why data and automation are going to drive so much spending in the years ahead. Research suggests that global technology spend will reach $2.5 trillion by 2025 – a significant gain on 2021 spending of $2 trillion, and that data solutions and enterprise automation will be at the core of that.

Within that, one of the key themes is – and will continue to be talked about a great deal – “breaking down silos.” More traditional ways of computing have resulted in highly siloed legacy environments, and many organisations are struggling to grapple with the idea that they need to transition to data lake-style environments, where silos are replaced by all-of-business environments.

However, there is a misconception about how essential this process is, and it isn’t always practical. A line of business might have a critical application sitting in a silo that would cost $2 million to redevelop for new hosting. Legacy environments might be siloed for other, very good reasons.

Our work with Parliaments across the globe provides a good example of this. Parliaments typically have a lot of legacy systems in place, but those systems still have plenty of useful information that they want to draw insights from. At NovaWorks, the way in which we responded to this challenge for one government client is to import information from five disparate systems which have similar data, and merged them to utilise in their main platform.

This way, they can still maintain information in their silos – which they might need so they can maintain compatibility with their application environment – but then also provide that data into a single silo set for use for everyone. This is a useful and practical solution when the cost of redeveloping those other systems are not beneficial for the business.

Addressing the skills challenge

Another area where automation can assist is in addressing the skills gap, which is challenging a lot of organisations across Australia, of all sizes. Businesses are paying a substantial premium to try and attract and retain IT skills in all areas of IT, and with data being at the core of the operation, those that are unable to attract talent face wide-ranging challenges.

However, many organisations could be doing more to leverage their existing talent, too. Existing database and BI teams might be used to working on an on-premises environment, for example, but they have a good understanding of the data itself. Rather than aim to simply bring in new skills to handle Synapse servers of Data Factory servers (for example), understanding how to help the existing teams transform their skills into these new environments is an opportunity to address the skills crisis.

Those skills can be supported by automation. In conjunction with the existing team and some retraining, many organisations can access better data and insights than they often thought they had access to and can save significantly on both recruitment and migration with the right strategic approach.

A good example of these dynamics at play, which NovaWorks helps many customers take full advantage of, is Microsoft Purview. This cloud-based analytics program draws in data from hybrid sources to give teams automated analytics – a “Microsoft Purview Data Map” across the entire organisation. This data then becomes easily discoverable across all lines of business thanks to its ease of use and provides the data science team with what they need to develop BI, AI and machine learning models. All of this is protected by strong policies so that only the right users have access to the data, meaning the organisation can meet their compliance obligations.

A lot of the rhetoric around an organisation’s data practices involves heavy investment – complete transformations to de-silo data and move all of it – and all the applications – into cloud-driven data lakes, and heavy investment in skills for these new environments. This isn’t always practical or viable for an organisation, but there are solutions, in leveraging automation, the right data applications, and reskilling the existing team that will allow an enterprise to tap into the modern data opportunity.

For more information on how to get started on data automation and insights quickly, contact NovaWorks today!