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Data Analysis & Data visualisation

You give us your data - We analyse it - We provide you actionable insights !


Text analysis -

Text analysis is a machine learning technique that allows companies to automatically extract and classify text data, such as tweets, emails, support tickets, product reviews, and survey responses.

Text analysis applications are vast: you can extract specific information, like keywords, names, or company information from thousands of emails, or categorize survey responses by sentiment and topic.


Data Mining -

Text analysis is a machine learning technique that allows companies to automatically extract and classify text data, such as tweets, emails, support tickets, product reviews, and survey responses.

Market Basket Analysis

is one of the key techniques used by large retailers to uncover associations between items. It works by looking for combinations of items that occur together frequently in transactions. To put it another way, it allows retailers to identify relationships between the items that people buy.

Association Rules are widely used to analyze retail basket or transaction data, and are intended to identify strong rules discovered in transaction data using measures of interestingness, based on the concept of strong rules.


Data visualisation -

We need data visualization because a visual summary of information makes it easier to identify patterns and trends than looking through thousands of rows on a spreadsheet. It’s the way the human mind works. Since the purpose of data analysis is to gain trends, data is much more valuable when it is visualized. Even if a data analyst can pull insights from data without visualization, it will be more easy to communicate the meaning with visualization. Charts and graphs make communicating data findings easier even if you can identify the patterns without them.