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ZDNET’s key takeaways

• Your ability to exploit data relies on strong underlying processes.
• AI can be your best friend when it comes to data integration.
• Focus on consistency, orchestration, capabilities, and culture.

As many as 63% of business leaders describe their organizations as data-driven. However, only one in two executives is confident about its ability to deliver timely business insights.

If your business is going to make the most of its information, it’s going to need a technique to make its data available and accessible. So, step forward emerging technology, which increasing evidence suggests can be the key to unlocking value from information.

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Whether it’s integrating platforms, merging companies, or working across geographies, professionals must manage a complex range of sources. Here’s how experts say that AI and automation can help.

1. Drive internal consistency

Joel Hron, CTO at global content and technology specialist Thomson Reuters (TR), said his organization uses AI to overcome data and system integration challenges in software engineering.

“We’ve found great benefit across various modernization and migration activities,” he said. “We heavily use AI tools to help ensure compliance with accessibility standards and things like that.”

That pioneering work continues at pace. Hron said TR’s corporate development teams are currently creating an internal AI system for due diligence to drive more consistency in deal evaluation, risk assessment, and potential risk mitigation.

“It’s really a super powerful idea,” he said. “They’ve been building that for the last month or two, coupling it quite nicely with a legal operations product that we sell in the market called HighQ.”

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Hron said TR is an acquisitive company that spends time integrating systems. While the benefits of these AI-enabled developments for his company are clear, could the tool above one day be used by external clients? Maybe, he said.

“If we can create something really useful for us, why not bring it to market? But at this point, our focus is about how we make this tech useful for all of our M&A activity and help drive not just speed and efficiency, but consistency in the deals that we do.”

2. Orchestrate your insights

Miko Chen, lead data engineer at Create Music Group, uses data and AI to improve her company’s operational processes, and she advises other professionals to explore leading-edge tools.

The Los Angeles-based music technology specialist uses AI and orchestration capabilities in Astronomer’s Airflow service Astro to manage over 600 data pipelines.

Create has used Astro to integrate its BigQuery and Google Cloud Storage technologies, and APIs from Spotify, YouTube, Apple Music, and Amazon Music, into a layer that manages data pipelines for operational activities, such as analytics and financial forecasting for labels and artists.

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“We want to provide better data to help our clients make decisions, instead of randomly thinking about what they should do,” she said.

“For example, if they want to host a concert, they can use our insights to consider which city they should pick versus which city they can select next time. So, with our data, our artists and our clients can make this proactive decision.”

Create is an acquisitive business, and Chen said her team also uses Astro to consolidate data.

“With Astro, we can easily move data around different places, such as from one organization to another, or from one country to another,” she said.

3. Explore current capabilities

Huy Dao, director of data and machine learning platform at Booking.com, said it’s important for professionals to understand the technological capabilities in their existing data stacks.

Booking was already a Snowflake customer when Dao joined the firm in August 2023. While this platform was proving its worth, he knew the technology offered additional capabilities, particularly for creating AI-enabled services.

“We now use it for way more than the warehousing component,” said Dao, who explained to ZDNET his team’s direction of travel during the past two and a half years.

“All our sensitive data access goes through Snowflake, and we are also using the latest available capabilities, both Cortex AI and Cortex Analyst. We’re exploring the Snowflake Semantic View, and we are also interested in the Horizon Catalog, which can interconnect with other data catalogs.”

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Rather than just providing a consolidated source of information, Dao said Snowflake provides an AI-enabled solution that helps professionals solve intractable business challenges. In short, business users now have the power to enact change, thanks to AI.

“The platform reduces the barrier to entry. So, instead of having only 200 users who can access and use our data, we can have 2,000 users because Snowflake makes it easy,” he said.

“With some of the AI capabilities, you don’t even have to write SQL to query the data. Things like that make it easy for people who traditionally did not have data skills.”

4. Focus on marginal gains

Richard Corbridge, CIO at property specialist Segro, told ZDNET that AI and automation can play a crucial role in helping his company bring disparate data assets together. He gave ZDNET the example of cross-European sustainability data.

“We need to monitor, by law, our carbon footprint and sustainability stats. In Poland, they send the meter readings as PDFs. In Germany, they come as digital, automatic readings. In the UK, they might come as photos of utility meters,” he said.

“We’ve got to work out how we take all those disparate ways of reporting on energy usage, put them into one place, and turn it into a Segro report on carbon footprint and energy use.”

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Previously, that laborious task was completed by a human specialist across Excel spreadsheets. Now, with the help of AI and process automation, Corbridge’s team is using AI to free up human resources and create business benefits.

“We’re building AI capability to go out, bring the data back, put it into the database, find out when it’s not right, and point out illogical elements, such as where the meter reading is the same as last month, so there must be something wrong,” he said.

“It’s cool stuff in a small, impactful area. It’s fascinating to see a bit of a geek on this one. The results have been super exciting.”

5. Reduce the management load

Ankur Anand, CIO at global technology and talent solutions provider Nash Squared, said the biggest impact AI has on data management is mapping and normalization.

“AI reduces your integration effort by almost 30% to 40% and gives you far more accurate results compared with the traditional approach of using Excel,” he said.

Using BlueGecko, an AI-enabled data management platform from technology specialist Nextgenlytics, Anand’s team has automated time-consuming data-mapping processes, particularly during post-M&A activities.

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He explained to ZDNET how the system produces accurate results at key stages, such as during ETL (Extract, Transform, Load) processes.

“Blue Gecko understands the data, maps the data, explains how the two systems are talking to each other, and the values within those systems, and through that approach, the technology helps to accelerate your work around ETL development,” he said.

Anand’s advice for other professionals looking to integrate data and systems is to focus on culture.

“Think about people who have been using other tools,” he said. “What are the change management processes that you can bring in? Success is not just about deployment; adoption is also important.”