The volume of data businesses collect is growing rapidly, driven by the Internet of Things and social media. However, there is often a gap between collecting data and knowing how to use it effectively. To address this, businesses need a data management and governance system that aligns with their overall goals, rather than just collecting data arbitrarily.
Effective data analytics can inform strategic decision-making and help identify opportunities and risks. This involves not only collecting relevant data but also controlling its volume and ensuring proper usage. Such approaches can lead to substantial transformations and competitive advantages.
Successful data management requires continuous decision-making, given the increasing complexity of algorithms and compliance rules. This has led to a rise in the number of data specialists within organizations, and the trend is expected to continue as artificial intelligence technologies evolve.
Data stewardship is critical, especially in highly regulated sectors like healthcare and financial services. Effective data usage must involve ethical considerations and robust cyber resilience to prevent breaches. Regulatory technology can help manage compliance risks, and audit firms are developing frameworks to provide ethical algorithm assurance.
Innovative applications of data analytics and AI are already being seen. For instance, an airline using AI to manage hand luggage efficiently and an IT services provider in India using AI to monitor sanitation in schools highlight how data can provide diverse solutions.
The journey towards a data-driven world is ongoing, with new challenges and innovations on the horizon. Technologies like AI will continue to evolve, disrupting some organizations while elevating others. Implementing best practices now can help businesses minimize future risks and stay ahead.
