Use Location Analytics to Improve Bottom Line of Businesses
Geospatial data can enhance a business' data assets and provide more valuable insights. Incorporating geographic information into performance analysis can bring to light new insights.
Detect Outliers in Data Wrangling: Examples and Use Cases
How to Detect Outliers in Data Wrangling: Examples and Use Cases Outliers is the term that strikes your mind whenever you speak about analyzing data. If you are planning to inspect any task to examine data sets, you can make assumptions about the methods used to produce
How to Improve Your Brand’s Net Promoter Score (NPS)
A Net Promoter Score is a key metric to measure what your customers think of your brand. There are many ways to improve this score.
How to Use Propensity Modeling to Predict Customer Behavior?
Propensity modeling is a statistical technique used to predict future events. Machine learning allows companies to build robust propensity models and make accurate forecasts. In marketing, for example, propensity models are used to predict customer behavior.
Graph Analytics to Find Hidden Patterns and Relationships in Data
Analyzing data graphs can help you discover hidden patterns and relationships. Making better business decisions and improving performance are possible when your data is interconnected.
Customer Segmentation Using RFM Analysis
To run a profitable business, you need to know your customers. For which, you need to first segment them. Segmentation can be done in a number of ways, but one of the most effective one is RFM analysis. RFM stands for the Recency, Frequency, and Monetary value.
What is Automated Machine Learning (AutoML): A Guide
Data is used to teach computers how to learn through machine learning, which is a subset of artificial intelligence. In automated machine learning, the entire process of applying machine learning to real-world problems is automated.
Benefits of Using Data Fabric
A data fabric is a type of data architecture that allows for the integration of data from multiple sources. It is designed to provide a single, unified view of an organization's data.
What is Named Entity Recognition (NER): Benefits, Use Cases
Named Entity Recognition (NER) is a field of computer science and natural language processing that deals with the identification and classification of named entities in text. The aim is to automatically extract information from unstructured text such as people's names, of organizations, locations, and so on.