All You Need to Know About Advanced Data Analytics 

There was a time when business analysts relied on historical data stored in silos and then analyzed after the event in order to be able to derive intelligence that could help businesses take decisions for the future. This proved to be less than satisfactory. Trends have changed and the move is towards analyzing data from diverse sources in real time with the help of big data tools. Data may flow from online searches. Data may flow from sensors in the internet of things environment. All such voluminous amounts of data need to be analyzed fast, in real time, and with high levels of precision

So what exactly is advanced data analytics?

In the simplest terms one can say that advanced data analytics is the science and technology of analyzing terabytes of data possibly in real time to derive strategic business insights and intelligence. Where standard analytics may fail on different counts such as precision and accuracy of analytics or not being able to deliver intelligence in time that will help companies take action in time, advanced analytics does have a measure of predictive capabilities and timeliness. Advanced analytics of data covers various aspects such as data in relation to a company and its workings. It can analyze trends, customer behaviors and expectations, by, for example, analyzing searches and social media. It can help companies keep track of competition and what they are doing. Enterprises can take the right decisions and be ready for the market when the demand arises instead of being late. Advanced data analytics covers predictive, cognitive and prescriptive analytics.

What is included in advanced data analytics?

As can be seen, this is a sophisticated technology since predictive capabilities point to inclusion of a measure of artificial intelligence and machine learning. The prescriptive feature uses machine learning to recommend paths the business could follow to achieve success. This is tied to the cognitive feature that, again, makes use of machine learning and artificial intelligence to parse and analyze data with a high degree of precision. Decision is usually left to business analyst’s recommendation to management but, in this case, the program itself offers solutions based on its advanced analytics and predictive capabilities. In short, it is data analytics beyond simple calculations and averaging. It makes use of sophisticated algorithms that is far more capable than humans to quickly detect trends and make recommendations. It considers probabilities like humans do but can do it with accuracy and speed.

Use areas

Customer preferences keep changing rapidly and advanced analytics can help companies anticipate such trends and be ready with products. It can analyze what is going wrong during contract execution and help project managers take corrective steps. It can be used to group together similar featured objects o find out associations or classify products. One of the most welcome features is the predictive, forecasting capabilities.

Businesses no longer need to rely on analyzing past historical data to find out what happened and how this could point to what is likely to happen. They can jump straightaway to what is in the future and take action right away. It is like having a superhuman analyst by your side with none of the drawbacks of human thinking.