How Qual and Quant Can Work Together
Don't miss this month's London Business Analytics Group where we're joined by Alice Daish and Casey Scott-Songin. Check it out!
The value of data is more widely accepted than ever before with more organisations adopting data initiatives. Quantitative and Qualitative data methods are often pitted against each other. Quant vs Qual! Both qualitative and quantitative methods have unique strengths. We want to discuss how they can work together to help organisations harness of the power of united data insights.
YOU MAY ALSO LIKE:
- Transforming a Museum to be data-driven using R (SkillsCast recorded in March 2017)
- Elasticsearch for Developers with Itamar Syn-Hershko (in London on 23rd - 25th September 2019)
- µCon London 2020 - The Conference on Microservices, DDD & Software Architecture (in London on 27th - 29th May 2020)
- Keynote by Ryn Daniels on Designing Sustainable Ops Cultures (in London on 21st August 2019)
- Leonardo De Marchi's Deep Learning Fundamentals (in London on 22nd - 23rd October 2019)
- Lightbend Akka for Scala - Professional (in London on 11th - 12th November 2019)
- Haskell eXchange 2019 (in London on 10th - 11th October 2019)
- F# eXchange 2020 (in London on 2nd - 3rd April 2020)
- Algorithmic Art (in London on 29th August 2019)
- Keynote by Noelia Jiménez Martínez and Phil Harvey on Data: A Guide To Humans. (in London on 16th September 2019)
- How real-time data processing is used for application in customer experience? (SkillsCast recorded in July 2019)
- A Look at the technology of LUNO and Adjust (SkillsCast recorded in July 2019)
Thanks to our sponsors
How Qual and Quant Can Work Together
Casey Scott-Songin
Casey Scott-Songin is Senior Manager: Data & Insight at the National Gallery, leading a joint team of quantitative and qualitative researchers to inspire data-driven decision making within the organisation. She is a social/cultural anthropologist with seven years experience in UX Research at organisations such as The British Museum and Which?.
Alice Daish
Alice Daish is a Data Scientist with experience in using data for decision making and organisational data transformation. Previously working at The British Museum focusing on making the museum data-driven. Co-Founder of R- Ladies Global and Leadership Team. Microsoft MVP. Registered Scientist previously trained in ecology and quantitative biology.
Don't miss this month's London Business Analytics Group where we're joined by Alice Daish and Casey Scott-Songin. Check it out!
The value of data is more widely accepted than ever before with more organisations adopting data initiatives. Quantitative and Qualitative data methods are often pitted against each other. Quant vs Qual! Both qualitative and quantitative methods have unique strengths. We want to discuss how they can work together to help organisations harness of the power of united data insights.
YOU MAY ALSO LIKE:
- Transforming a Museum to be data-driven using R (SkillsCast recorded in March 2017)
- Elasticsearch for Developers with Itamar Syn-Hershko (in London on 23rd - 25th September 2019)
- µCon London 2020 - The Conference on Microservices, DDD & Software Architecture (in London on 27th - 29th May 2020)
- Keynote by Ryn Daniels on Designing Sustainable Ops Cultures (in London on 21st August 2019)
- Leonardo De Marchi's Deep Learning Fundamentals (in London on 22nd - 23rd October 2019)
- Lightbend Akka for Scala - Professional (in London on 11th - 12th November 2019)
- Haskell eXchange 2019 (in London on 10th - 11th October 2019)
- F# eXchange 2020 (in London on 2nd - 3rd April 2020)
- Algorithmic Art (in London on 29th August 2019)
- Keynote by Noelia Jiménez Martínez and Phil Harvey on Data: A Guide To Humans. (in London on 16th September 2019)
- How real-time data processing is used for application in customer experience? (SkillsCast recorded in July 2019)
- A Look at the technology of LUNO and Adjust (SkillsCast recorded in July 2019)
Thanks to our sponsors
How Qual and Quant Can Work Together
Casey Scott-Songin
Casey Scott-Songin is Senior Manager: Data & Insight at the National Gallery, leading a joint team of quantitative and qualitative researchers to inspire data-driven decision making within the organisation. She is a social/cultural anthropologist with seven years experience in UX Research at organisations such as The British Museum and Which?.
Alice Daish
Alice Daish is a Data Scientist with experience in using data for decision making and organisational data transformation. Previously working at The British Museum focusing on making the museum data-driven. Co-Founder of R- Ladies Global and Leadership Team. Microsoft MVP. Registered Scientist previously trained in ecology and quantitative biology.