In the data world there are traditionally three steps for handling data before you can even contemplate empowering your data systems with AI and machine learning algorithms:

Organisations at the outset of their data journey need data capture systems to discover information engrained in all levels of business operations.

Next, the data needs to be ‘cleaned’ – verifying informational accuracy – and integrated to reduce the risk of drawing misleading insights and to create one view of the business

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The final step is analysis; businesses work with data analysts using leading analytics tools to pare back layers of proprietary information in search of insights to power change.

Data services have operated this way for years. Cast Solutions breaks this linear approach with a greater focus on client needs and ‘smarter’ data solutions integrated with artificial intelligence (AI). Here’s how you can empower your data systems with AI and machine learning.

 

How does AI and machine learning work within data systems?

Remember the three-part data handling flow above? Larger organisations with more complex data integration and data analytics processes can introduce a fourth step: predictive analytics.

Predictive data analytics, also known as advanced analytics, deploys autonomous or semi-autonomous algorithms to assess large datasets (big data) and make predictions based on specific information patterns. By generating deeper insights into company data more quickly, data analysts can offer clients better service which can lead to more significant transformations.

Consider the applicability of AI and machine learning within the context of the data handling flow. After your proprietary data has been captured, processed, and integrated in a single view, analytics tools help data analysts to find points for improvement in your business.

However, AI excels at finding data patterns that humans just can’t see. This can be scaled, at speed, depending on the size of the dataset. Machine learning algorithms can also adapt to data pipeline input and human patterns of behaviour to make data analytics seamless. This can be achieved using natural language processing to recode communications between people within an enterprise for algorithms to interpret and act on.

AI and machine learning have been the ‘next big thing’ in a range of industries for decades. Within the marketing sector, for example, people associate smart solutions with chatbots. However, the potential of AI and machine learning goes far beyond just chatbots.

Research from Gartner shows that AI embedded in data analytics tools will free up a third of data analysts in marketing organisations by 2022. That doesn’t just translate to cost savings; that also means increased productivity as humans spend more time on value-added tasks.

 

What are the benefits of data AI and machine learning?

We touched on how integrating smart solutions into your data systems can help. However, the benefits of data AI and machine learning are more far-reaching than you might think:

As mentioned, AI and machine learning reduces time and resources spent on data analytics, allowing expert data analysts to spend more time collating action points and consulting with organisations for more timely and relevant recommendations.

AI and machine learning algorithms can also help to reduce the risks of human error inherent in any data handling process. This will impact a business’ data infrastructure from top to bottom.

The improvements possible with smart solutions are self-sustaining. As an AI system learns more about your business data platforms and processes, it can continue to refine its effectiveness and ability to generate customised insights from big data silos.

Ultimately it’s the hard data that can tell the true tale here. More than 60% of companies with a pre-existing innovation strategy are using AI to identify opportunities in their big data solutions that would be otherwise missed, according to GlobeNewswire. Without incorporating AI into your data infrastructure, your business has every chance of being left in the past.

 

Why ‘future proof’ your organisation?

The scale of change in the business world has never been more significant. As organisations encounter an increasing number of sophisticated data integration and data analytics platforms, as well as dashboards for visualising this data, it can be tricky to determine what steps to take. However, it’s vital that enterprises make the decision to ‘future proof’ operations early.

Future proofing forecasts trends to minimise the effects of shocks, such as the introduction of a new competitor in the market or old technology becoming obsolete, on business operations. With consideration to AI and machine learning algorithms embedded within your data systems, the adaptability and scalability of these solutions are ideal for preparing for all possibilities.

One of the hesitancies of adopting AI technologies is the fear of ‘replacing’ humans. This is sci-fi inspired inaccuracy. Consider Gartner’s research into data analyst roles within marketing organisations. AI and machine learning ‘freed up’ analysts; it took the emphasis away from laborious information processing and refocused the attention on applying insights in the real world.

That’s why future-proofing your company’s data analytics and utilisation is a strategy that will pay long-term dividends; it gives data analysts better tools to work with.

 

Cast Solutions’ AI and machine learning systems

Worldwide spending on AI systems will reach $57.6 billion by 2021, according to IDC. Businesses that fail to plan for how they can use AI and machine learning algorithms to transform operations may ultimately be left behind by more flexible and adaptable competitors.

Luckily, Cast Solutions is here to talk you through what data solutions suit your needs. We have partnered with the world’s biggest data solutions providers, including Microsoft and Amazon Web Services, to offer our clients the leading AI and machine learning-powered solutions.

We also understand, however, that no two organisations are alike, so even the most sophisticated data analytics platform is limited in how it can help unless adapted to your data systems with the help of business intelligence analysts. Chat to our friendly team to get an idea about how you can empower change in your business with data AI and machine learning.

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