Accelerate Data Discovery by Building a Semantic Metadata Catalogue
Sponsored by: PerkinElmer
- Virtual Data Warehouse
- Data Silo
- Data Analytics
Date: 15 June
Time: 4PM London/8AM California
Unifying data across silos
Scientific organizations, from research and discovery through commercial and operations, rely on a broad and disparate collection of data. This creates compelling opportunities, but also big challenges, as they need to unify the data across silos – from relational databases, document stores, data warehouses and other disparate systems – before any meaningful analysis can take place.
Pulling that data together is very time consuming, manual, and driven by trial and error. Approximately 70% of any Business Intelligence (BI) or data analysis project is spent just finding and profiling available data sources. Traditional approaches include using data warehouses, which suffer from costly ETL processes in unifying the data upfront, or data lakes, which defer the restructuring and unification to costly map-reduce processes downstream.
PerkinElmer Signals Perspectives uses a machine-learning approach to automatically generate metadata so that it can then infer connections between disparate, siloed data sources and semantically tag information. With this semantic metadata catalog as a foundation, IT organizations can rapidly provision virtual data marts to support their business users.
Philip John Skinner,
Solutions Consultant, Data and Content Analytics
Philip is a Spotfire evangelist, specifically in the lifescience and chemistry communities, and is delighted to bring his experience and passion to provide consulting to customers of PerkinElmer who are using or considering using Spotfire. Prior to joining PerkinElmer, Philip spent a decade working as a medicinal chemist at a San Diego based biotech, progressing GPCR ligands into clinical development for metabolic diseases. Philip holds a PhD in Chemistry from the University of Durham and completed postdoctoral studies at the ETH in Zurich.
More recently Philip has been focused on the varying challenges of provisioning quality data to BI tools such as Tibco Spotfire, specifically around the ideas of content analytics and datasource discovery.
Chief Technical Officer, Attivio
Greg is the Chief Product Office for Attivio, where he is responsible for product strategy and research and development. Prior to Attivio, Greg was the Director of Big Data Technology & Alliances for TIBCO Spotfire, where he worked with the data analytics ecosystem for TIBCO's interactive data visualization platform.
Earlier in his career Greg had strategy and product manager positions at Spotfire, SPSS, InstallShield and a number of interactive television start-ups. Greg holds both is BS in industrial engineering and his MBA in marketing and strategy from Northwestern University.
Key Learning Objectives
- Learn how automating the building of a semantic catalogue can accelerate a data warehousing project
- Learn how agile virtual data marts can be quickly generated to support business users and analytics applications
- Learn how the system enabled the building of a catalogue by inferring data types across the broad disparity of data relevant to life science organizations
- Learn how other organizations have reduced their data warehousing projects by up to 75%
- Chief Data Officer
- VP Data Management
- Data Integration Owner
- Big Data Strategy Officer
- Data Architect
- Business Analyst
- Chief Information Officer
- Data Scientist
- Head of Big Data Strategy
- Head of Business Intelligence