Sonal Goyal

Founder & CEO, Nube Technologies

Sonal Goyal is the founder and CEO at Nube Technologies, a startup focused on big data preparation and analytics. Nube Technologies builds business applications for better decision making through better data. Sonal and the team at Nube help customers build better and effective models by ensuring that their underlying master data is accurate. The company’s fuzzy matching product, Reifier, helps companies get a holistic view of enterprise data. By linking and resolving entities across various sources, Reifier helps optimize the sales and marketing funnel, promotes enhanced security and risk management and better consolidation and reporting of business data.

 

Talks on Wurreka:

Integrating multiple and diverse datasets for analytics are an essential part of a data scientist's life. This is an essential part of the analytics journey, as feature engineering on dirty data will only be faulty. However, current tools do not make the process simpler. There is a wide variety of data attributes and formats to take care of. Preparing for analytics by matching and deduplicating records remains a challenge. Unifying matching records into a definite representation of an entity is both time consuming and error prone. Hence, preparing data for predictive analytics requires manual effort and occupies upto 60-70% of a data scientist's time.

In this talk, we discuss how data engineers and scientists can augment their data preparation by leveraging machine learning. We talk about schema mapping, identifying attributes on disparate data sources which refer to the same values. We discuss data mastering and how it is different from a typical clustering and classification problem. We also elaborate about scaling these approaches, and how machine learning can help.

Come see how ML can be leveraged for data preparation for analytics.

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