When it comes to analytics & AI trends for 2019 there are certainly many advancements that will see the analytics space markedly changed from 2018. Here are our thoughts on what we anticipate seeing more of in 2019.

In-house data expertise

The rise of self-service analytics technologies means that unlocking insights is becoming easier than ever. With normal business users empowered to explore their own data, the niche nature of analytics is gradually diminishing – it’s going mainstream.

Despite this, the greater accessibility of analytics solutions will see data experts in higher demand than ever. In order to optimise their analytics efforts, organisations will need increase access to either in-house/to outsource data scientists to collaborate data and ensure best-practice across the organisation, but the role as we know it is set to change.

Eradicating the repetitive tasks associated with traditional data analysis will allow data scientists to be freed up so they can focus on fully exercising their expertise; solving specialised problems, working hand-in-hand with technologies like Augmented Analytics to carry out their roles more efficiently.

The data scientist is also set to move away from simple number crunching and evolve into a strategic voice for organisations to help them make better informed smarter decisions. They’ll generate real value by taking insights generated across the organisation to the next level to ensure that business activity coincides with the wider data strategy.

We know that many organisations are setting up business insight functions, but are hampered because they are either don’t have the people with the skills or they don’t have the latest analytics technologies.

Data Visualisation

It doesn’t matter how sophisticated your insights are, if you can’t communicate them in a clear, concise and engaging way, they won’t count for much. In 2019 we’ll see data visualisation taking centre stage in the world of analytics, acting as the “new language” for organisations to communicate their data insights.

Gone are the days of complicated data that can only be translated into plain English by data experts. Data visualisation is another technology that’s making the way for people from all areas of the business to interpret and interact with the data they produce.

Traditionally, many businesses have viewed their data as two-dimensional, dull and inevitably difficult to understand. That’s all about to change.

Data in any organisation is alive and going into 2019, data visualisation will help to reinforce this message by humanising data and allowing people to see first-hand how it relates to their everyday business processes. Embracing this the human side of insights allows users to identify patterns and trends and truly understand why things happen the way they do.

Overall, as data visualisation becomes more prominent in organisations, data-led conversations will begin to become a normal part of business culture. As a result, we can expect to see the greater synergy between departments as well as an increase in data collaboration and connectivity in organisations in 2019.

Predictive Analytics

The utilisation of predictive analytics relates to the extent to which an organisation utilises the data they produce. The more they do with their data to get the most out of it, the more data mature they are. The concept of advancing in your data maturity journey in 2019 will see this take prominence in many organisations. At present, organisations produce a lot of data, but many are stuck reporting what has already happened in their organisation – kind of like looking back in the rear-view mirror.

Research by  Deloitte shows that 96% of executives believe that using the right tools to get the most out of this data will become more important than ever over the next few years. In order to remain competitive, it’s essential that organisations get the most out of the data that they produce.

This means that we’ll start to see businesses moving away from retrospective reporting and embracing more advanced analytical techniques to gain further insights from their data.

For example, organisations may start to utilise predictive analytics to no longer just use their data to show them what has happened but to predict what will happen five, ten, years from now.

This will enable organisations to predict everything from which employee is most likely to leave the organisation, to which products will perform best during certain seasons of the year. They may even be able to pinpoint the variables that contribute most to these trends and use these insights to solve the problems they face.

Furthermore, with advancements in artificial intelligence and machine learning, some advanced organisations may start their journey towards utilising prescriptive analytics. This will enable them to step back from having to rely on users inputting variables into the system to predict future outcomes and instead harness machine learning and artificial intelligence to solve problems before they’re even aware an issue exists.

Organisations’ increased awareness of their level of data maturity is setting the scene for a world where data is truly seen as a modern-day corporate asset and it’s something that will start to become a core measure of strategic competence.

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