The insight that analytical data provides can help to form effective business strategies that produce results.
Data analytics is the investigative analysis of large sets of data to identify or discover the trends and patterns inherent in that data.
Data visualization isn’t about flashy graphics for the sake of them. It’s about displaying data in a way that is easier for business users to comprehend and give them the confidence to take decisive actions. Data visualization represents data in a visual context by making explicit the trends and patterns inherent in the data. Users will only reap the benefits if the visualisation reveals patterns and trends that are not readily apparent in text-based data.
Predictive analytics is the process of analysing historical and current data and applying advanced statistical methods and analytical tools to make reliable predictions about the future. In a business context, our predictive analytics solutions involve the creation of a predictive model used to exploit patterns in historical financial information, customer data, and other third-party data sources to identify risks and opportunities.
Machine learning and deep learning have led to huge leaps for AI in recent years. Machine learning and deep learning require massive amounts of data to work, and this data is being collected by the billions of sensors that are continuing to come online in the Internet of Things. IoT makes better AI. From an industrial point of view AI can be applied to predict when machines will need maintenance or analyze manufacturing processes to make big efficiency gains, saving millions of dollars. On the consumer side, rather than having to adapt to technology, technology can adapt to us. Instead of clicking, typing, and searching, we can simply ask a machine for what we need. We might ask for information like the weather or for an action like preparing the house for bedtime turning down the thermostat, locking the doors or turning off the lights.