Do You Need to Be a Data Scientist to Analyze Text?
There has been a lot of discussion and debate recently about big data, big data analytics, and the role of the data scientist. Part of the discussion revolves around the skills required to be a data scientist, who is supposed to possess statistical or quantitative model-building skills, computer science skills to deal with new and diverse technologies, business savvy and acumen, and subject matter expertise.
Because unstructured text data accounts for a large amount of data on and outside of your company’s premises, it is a critical part of the big data equation. Given this, any discussion of analytics, big data, and data science would be incomplete without a discussion of text. Text analytics is rapidly moving into the mainstream as companies look to gain better insight into behaviors of all kinds and improve their predictive capabilities. So do you need to be data scientist to analyze text?
This Webinar will provide an overview of text analytics, what’s involved in analyzing text, various use cases for text analytics, and what it means for big data, and the role of the data scientist.
You will learn:
- The basics of text analytics
- Trends in text analytics
- Categorized use cases for text in big data analytics
- Skills needed to perform text analytics