What are Advanced Analytics and what is their value?
By Pankaj Gaur
Advanced Analytics is the foundation for cognitive computing, machine learning, artificial intelligence, and bots. It is an umbrella term for a group of high-level methods and tools that can help you unlock the value of data.
The predictive and prescriptive capabilities of advanced analytics can be used to forecast trends, events, and behaviours. Simply put, it brings static data to life and unlocks the insight you’ve been searching for.
It is important to note that Advanced Analytics is not meant to replace business intelligence, but to augment its efforts. It strives to ask deeper questions of the data, generating insights that not only indicate how the business is currently performing but where its future is headed.
If we consider that business intelligence largely aims to point out strengths and weaknesses in current business processes, advanced analytics has the potential to make recommendations and predictions as to how to steer an organization forward.
What is the Value of Advanced Analytics?
Time series analysis is the technique of analyzing historical data to predict future outcomes. It considers prior trends to recommend how organizations should plan ahead, such as stocking more inventory for a historically popular sales day. Forecasts can be extremely accurate, but their reliability depends upon the relevance and availability of historical data, as well as the time period to be forecasted.
Machine learning is the process of training a computer to predict outcomes without it being specifically programmed to do so. Machine learning models are built to model the desired behaviour, and as the model is fed more and more training data, its accuracy in predicting outcomes increases. Data—and lots of it—is the key to effective machine learning models.
Semantic analysis is the act of determining meaning from text data. By way of semantic analysis, computers can “read” full documents by analyzing its grammatical structure and the relationship of individual words. The technique is particularly useful for marketing teams to be able to analyze social media data or for customer service teams to better understand the effectiveness of online customer support.
At Content Bloom, our team of Architects, Data Engineers, and Data Scientists will help you not only build best-in-class AI/ML platforms but also productionize your solutions by using best practices like MLOps and experiment tracking.
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