As businesses look to get the greatest value from their data, investments in cloud infrastructure from customer relationship management (CRM) systems to email to points of sale can help make data more accessible and bolster innovation, says PwC principal in the analytics insights practice, Anil Nagaraj and Microsoft director of product management Azure Synapse Analytics and Power BI, Kim Manis.

Weighed down by legacy systems and rapidly increasing data volumes, many businesses have begun to migrate to cloud infrastructures to modernize their platform. According to Manis, the clearest benefits of moving to the cloud are speed and time to market as cloud platforms allow businesses to focus on core needs and customers rather than infrastructure and integration.

Although migration to the cloud can help businesses focus on their core competencies, making data accessible is key to becoming data-driven.

“The most important thing is building that data culture,” says Manis. “The people making decisions every day in your business actually use that data. So it doesn't matter how much data you have or how many metrics are being tracked in some spreadsheets somewhere if nobody's actually using it to make decisions.”

Industry-leading practices for strengthening data culture and real-time decision-making, says Nagaraj, include empowering teams across the enterprise with data, creating a culture of openness and transparency, and encouraging new innovations utilizing optimized data.

“I think we’ve got to break those barriers to make sure data is truly available to end business users through multiple experiences that you can bring about,” says Nagaraj.

Technologies like AI and machine learning can help enable new business innovations and improve data literacy without the intermediary help from data scientists. However, on top of maintaining interoperability between emerging technologies with cloud migration, businesses, especially those in the finance and healthcare sector, should also focus on data governance. 

“I think it comes down to the data needs to be trusted in the first place and in the right structure in the first place for these AI capabilities to work,” says Manis. “No one is going to trust the new AI capabilities if they don't trust the data. And that's where the governance piece comes in.”

Looking forward, Nagaraj forecasts that cross-industry and cross-customer shared data can help enable critical decision making.