Enabling Data Science to Be Data Science: Strategies for Increasing Self-Service Data Science
Webinar Speaker: David Stodder, Senior Director of Research for BI, TDWI
Date: Tuesday, January 23, 2018
Time: 7:00 a.m. PT, 10:00 a.m. ET
Data science offers great potential for what it can contribute to business strategy and operations—that is, if data scientists are actually able to do data science rather than spend most of their time on data management and preparation. TDWI finds that most data science projects spend the majority of time on these areas rather than on development of analytics, models, and algorithms. To increase business value, organizations need solutions that will flip this ratio.
In addition, companies are under pressure to democratize data science so that more of their organizations can gain value. Lines of business, divisions, and operations that do not have data management specialists on staff are often wholly dependent on central IT, which slows down data science and reduces its impact. IT is concerned about negatively impacting production systems. Business leadership needs agile, self-service data science that can be dynamic and in sync with business demand but not put production systems at risk.
Attend this TDWI Webinar to learn how you can create a data science strategy that benefits from less dependence on IT and affords greater self-service capabilities for both data scientists and business users. We will discuss how trends in technologies and practices are opening up opportunities to significantly reduce the data management drag on data science projects so that there can be greater focus on what adds the most value to the business.
Topics this webinar will cover include:
- Interpreting data science trends demanding greater self-service and less dependence on IT
- How technology options, including data-as-a-service and cloud-based data science, are enabling agility
- How to make it easier for business users to engage in data science through self-service tools
- Best practice recommendations for business-driven, self-service data science