5 Ways Data Engineering Improves Your AI Efforts

AI is here to stay. But is your business ready for it? 

Or, like many others, is it lagging behind?

The United States has a lower adoption rate, with 25% of companies using AI and 43% exploring its potential applications. In the UK, around one in six organisations have embraced at least one AI technology. 

The lifeblood of AI is data. AI needs clean, rich data to work to give your business the best possible outputs. While businesses today face a never-ending rush of data – whether from sources like social media, IoT devices, or customer interactions – this mass of information comes with a significant challenge.

And companies that fail to efficiently harness and analyse this data find themselves at a clear disadvantage. Leaving them to struggle with making informed decisions, understanding customer behaviours, or predicting market trends.

The result? Lost opportunities, eroding competitive edges, and dwindling relevance in their respective markets.

With the impact that AI is making on the world, the divide between businesses that adapt and those that resist widens, leading to a stark reality: adapt or risk obsolescence. The acceleration of digital transformation is not just a trend; it’s a tidal wave reshaping the world. Across virtually every industry.  

Enter data engineering – the beacon in this storm. 

At its core, data engineering involves the collection, storage, processing, and analysis of data. It lays the groundwork for making sense of the information that flows into a business, turning raw data into actionable insights. 

But the role of data engineering doesn’t stop at managing data; it’s also about preparing for the future. Emerging trends and technologies, such as artificial intelligence (AI), machine learning (ML), cloud computing, and real-time analytics, are pushing the boundaries of what’s possible with data.

[Read more: Want AI Driven Success? Look To Your Data]

Here’s how data engineering is future-proofing businesses:

Enabling AI and ML Deployment

The AI market is projected to grow more than 5x to £246.10 billion by 2028, indicating a significant shift towards AI and ML as essential business tools. 

With cloud offering the most ideal environment to store, manipulate and operationalise data, AI and cloud computing are converging to automate processes such as data analysis, decision-making, and security, leading to significant cost savings and efficiency improvements. 

The application of AI software based on ML algorithms in cloud environments delivers intuitive and connected experiences for customers and users.

That’s where data engineering shines. Data engineering provides the clean, structured data necessary for these technologies to operate effectively, unlocking new avenues for automation, innovation, and efficiency.

This preparation allows AI and ML models to learn from accurate, reliable data, enhancing their precision and utility. The outcome is a suite of tools that can automate decision-making, personalise customer interactions, and streamline operations – positioning businesses at the forefront of innovation and efficiency.

Facilitating Scalable Cloud Solutions 

The cloud computing market is projected to double from its current size to £754.24 billion by 2026. 

With the growing shift towards cloud computing, data engineering ensures that data is accessible, secure, and ready for on-demand analysis, supporting scalability and flexibility.

Cloud infrastructure supports big data analytics, AI, ML models, the Internet of Things (IoT), and advanced Business Intelligence (BI), ensuring that data is accessible, secure, and ready for on-demand analysis, supporting scalability and flexibility.

By optimising data for cloud environments, businesses can leverage on-demand analytics and storage solutions, scaling resources up or down as needed. This agility allows for a more flexible response to market demands and operational requirements, ensuring businesses remain competitive and resilient.

Empowering Real-Time Analytics

The impact of real-time analytics on any business is profound to say the least. 

According to PRNewswire:

  • 80% of businesses report an increase in revenues equating to a possible total recognised value of £2.07 trillion.
  • It is estimated that £255 billion in non-personnel-related operating costs have been saved. The potential for this number could rise to £301 billion if real-time data analytics were fully implemented across all firms in the key industry sectors surveyed.
  • 98% of respondents reported increased customer satisfaction as a result of implementing real-time data analytics technologies.

In an era of data-driven decision-making, real-time analytics is a must. But it has to be driven by efficient data pipelines that allow businesses to make quicker decisions, enhancing customer experiences and operational agility.

This immediate analysis enables businesses to quickly address customer needs, adjust to market dynamics, and optimise operational processes. Which dramatically enhances customer satisfaction and operational efficiency.

Ensuring Compliance and Security

With data privacy laws becoming more strict and exact, a solid data engineering foundation helps businesses navigate these regulations. Which helps ensure the handling of data is both secure and ethical.

By implementing secure data storage, encrypted transmissions, and access controls, data engineering minimises the risk of breaches and ensures data is used ethically. 

Doing this not only protects your business and its customers, but also builds trust and credibility in the marketplace.

Driving Innovation

By unlocking the potential of big data, businesses can explore new markets, understand emerging trends, and innovate ahead of competitors.

The overall AI software market will approach £474 billion in revenue by 2025. This indicates a need for businesses to strategically scale their AI/ML initiatives.

According to Snowflake, AI disruptors report significant improvements in customer experience and employee efficiency.

This ability to innovate based on data-driven insights gives businesses a competitive edge, allowing them to adapt to changes in the market landscape and customer preferences swiftly.

Turn Your Raw Data Into Gold 

Data engineering is not just a necessity for today’s businesses; it’s the lifeline that will carry them into the future.

Investing in robust data engineering practices is essential for any business aiming to thrive in the data-driven era. The question isn’t whether your business can afford to embrace data engineering – it’s whether it can afford not to.

As experts in the data engineering, cloud, ML and AI space – we can help you with your data.

Start your data engineering journey today. Turn your raw, uninspired data into rich insights, algorithms and innovation!

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