There’s a wide range of data analytical tools that businesses can use, and more are being introduced all the time. Some of the most widely-used data analytics technologies include the following:
- Predictive analytics: We briefly defined predictive analytics earlier, as using old data to forecast future outcomes. Based on statistical algorithms and machine learning (about which, more later), it provides businesses with a clearer idea of what to expect in the relatively near future, allowing them to prepare and position themselves accordingly.
- Data management: Collecting data is one thing, but you need to know how to manage it if you’re going to make effective use of it. Analytics processes and tools are therefore indispensable for managing the flow of data and organizing it. They can help your business ensure that you have high-quality data and that it’s easy to obtain when your teams need it.
- Data warehouse: A kind of management system used to facilitate data analytics and other business intelligence processes. Businesses can use data warehouses to centralize data drawn from various sources, thus making it more manageable and easier to draw insights from. It can also come to serve as a useful historical record which data analysts can use to make long-term comparisons.
- Machine learning: A subset of artificial intelligence (AI), machine learning essentially involves the simulation or approximation of human intelligence in completing tasks. As the name implies, it involves applications which can analyze data and learn from it over time, ensuring that it gradually becomes more and more accurate at predicting outcomes.
