59 percent of executives say big data at their company would be improved through artificial intelligence (AI).

It comes from studies conducted by PwC and reflects the growing belief among business leaders that AI can significantly enhance the management and use of big data within their organizations​. This view is supported by the recognition that AI can improve processes like data analysis, pattern detection, and decision-making, making it easier to derive value from the vast amounts of data businesses collect.

The importance of this statistic lies in the fact that many companies struggle to fully capitalize on their big data investments. The tools and methods to extract insights from data have often been immature or difficult to scale. AI can bridge this gap by automating complex analytics tasks, improving data quality, and enabling more accurate predictions, helping organizations make data-driven decisions faster and with greater precision​.

A data consulting firm can assist companies in this area by implementing AI solutions tailored to their specific needs. These firms can help integrate AI tools to streamline data processes, improve data governance, and ensure that data is prepared for AI use. Additionally, data consultants can provide the expertise needed to align AI initiatives with business goals, ensuring a higher return on data investments. They can also support organizations in overcoming challenges such as data silos, incomplete data, or bias in data, which are critical for successful AI implementation​

• Data warehouse optimization is considered the most important big data analytics use case, and is considered critical or very important by 70 percent of businesses.
• 40 percent of businesses say they need to manage unstructured data on a frequent basis.
• 45 percent of companies run at least some big data workloads in the cloud.
• 53 percent of companies are adopting big data analytics
• 8 percent of businesses say data and analytics have fundamentally changed the nature of industry-wide competition
• The education vertical currently has the lowest adoption of big data among vertical industries, but educators are most likely to say they may use big data in the future.
• By 2025, more than a quarter of all data created will be real-time, with 95% of that data generated by the Internet of Things.
• Analytics leaders are nearly twice as likely as others to report enacting a long-term strategy to respond to changes in core business practices.
• In the banking sector, investments in big data analytics were estimated at $20.8 billion in 2016.
• Customer/social analysis is considered the second most important big data analytics use case, followed by predictive maintenance.