Stop collecting, start analysing and become the king of data
by Veronika Schipper, on Sep 18, 2018 11:01:01 AM
Regardless of industry, data continue to dominate the digital age. Organisations are focused on gathering as much information as they can to drive smarter business decisions. But the shift from being data-generating to data-powered organisations is a long process that many companies are yet discovering.
Data is not only being collected from the web and mobile applications but, with the rise of IoT (Internet of Things), also from machines. Having different data sources that are being accumulated at significant volume enhances the need for proper analytics and related technologies. These can turn information into powerful insights. There are various types of data analytics that provide different value to the business:
Business intelligence solutions collect, analyse and make data easily accessible and available so that organisations can gain more insights and focus on improving their business operations. It is one of the most valuable data analytics on the market that turns data into an essential part of the company’s culture.
Who uses business intelligence:
- sales by analysing customer behaviour they can identify new opportunities
- executives to get a full picture of a company's performance
- senior management can benefit from insights related to their department
- finance to view the financial health of the organisation
- marketing to create marketing campaigns and identify new trends
Predictive Analytics is the analysis of data that can predict future events. It uses historical and present data to determine patterns and predict the future behaviour of your customers. There are various techniques involved in that process such as data mining, statistical algorithms and machine learning that can help you get answers on questions like what will be my churn rate in three months from now or what are the purchase patterns of particular target groups.
Who uses predictive analytics:
- retail to predict the best location for product placement
- marketing to plan promotions, also in-store
- financial and governmental organisations to detect fraud
Real-time analytics is a form of data analytics where users receive information within their data tools and application at the moment the data enters the system. There is no processing time nor the developer's intervention required. The business can react immediately and make decisions real-time to prevent mistakes to happen and get ahead of the competition.
Who uses real-time analytics:
- CRM to have prompt information about the customers
- Banks and other financial institutions for real-time credit scoring
- Retail to detect fraud
- Marketing for more accurate promotional targeting
- Weather forecasting, tracking of storms and wind intensity