Data analytics is the practice of using information extracted from databases to uncover useful knowledge that supports decision-making processes, providing crucial tools in healthcare, retail and manufacturing environments alike.
Data analytics involves several steps in its lifecycle, beginning with gathering and prepping the data. Next, it must be organized in an easy-to-analyze format before building models to identify patterns and trends within it. Once complete, business leaders use this information to help make decisions regarding products, services, marketing strategies and other areas of their organizations.
Data analytics can be used for various purposes, such as risk analysis, fraud detection and security monitoring. IT departments can run statistical models that predict the probability of cyber attacks happening and use that knowledge to better protect an organization against future attacks.
Before embarking on data analytics, businesses should ensure they have sufficient data for meaningful analysis of their operations. They can do this by collecting and storing this information in an easily accessible warehouse for further analyzing purposes.
Data Warehouses are essential in sharing data between departments and external parties, and managed by central IT departments. By centralizing and analyzing from one central location, warehouses help reduce costs while increasing speed.
Data storage options vary, but most organizations opt to store theirs in a data warehouse. A data warehouse offers secure yet easily accessible databases which enable users to quickly gain access to business-related information about an organization - this makes analyzing sales or inventory levels especially helpful.
Data warehouses can serve as an efficient means of keeping historical records for predictive analytics purposes, providing companies with easy ways to monitor customer trends and purchases. E-commerce businesses, in particular, will find such storage useful.
Data warehouses also make it easier for businesses to make future-focused decisions, which can be essential for sustainable business growth. One flower shop owner who invested in an analytics team was able to expand his business by 30% annually while increasing profits, customer satisfaction and revenue at the same time.
The business owner achieved this through using data gleaned from various sources, including social media. By gathering such information he was able to gain a better understanding of his target audience and devise an effective marketing plan which led to increased sales.
Data analytics not only lay a firm foundation for sustainable growth, but can also assist organizations with increasing efficiency and lowering costs. A freight company using a data analytics center of excellence to track shipping operations was able to save money by cancelling an unprofitable route and optimizing operations with its data warehouse to minimize customer wait times.
