Presented By
O’Reilly + Cloudera
Make Data Work
29 April–2 May 2019
London, UK

Architecting a data platform to support analytic workflows for scientific data

Jane McConnell (Teradata), Sun Maria Lehmann (Equinor)
14:5515:35 Thursday, 2 May 2019
Data Engineering and Architecture
Location: Capital Suite 8/9
Average rating: ***..
(3.67, 3 ratings)

Who is this presentation for?

  • CIOs, CDOs, data architects, IT architects, and data modelers

Level

Beginner

What you'll learn

  • Understand what scientific data is and why you need to manage it differently
  • Learn the key decisions are you should make early, including a standardization strategy

Description

In upstream and oil and gas, by far the largest category of data by volume is scientific data about the subsurface, in the form of seismic surveys, petrophysical well logs, drilling logs, and laboratory data and report data from physical samples. Historically, this data has been managed for archive in library-style solutions, and subsets of the data were loaded to specialist applications to perform standard workflows. These applications limited the amount of data that could be analyzed together and restricted the types of analysis that could be done. This scientific data is perhaps the most important data to expose to new styles of analytics and machine learning in terms of the business value this can unlock, but to do it at scale, across all relevant data, and often in near real time, a new approach to the data architecture was required.

Sun Maria Lehmann and Jane McConnell share architectural best practices learned from their work building a subsurface data platform in a cloud environment that is designed from the ground up to support analytical processing. Sun and Jane outline the key architectural patterns needed for managing physical measurement data, detail their approach to standardizing and integrating this data, and discuss the technology choices they made.

Photo of Jane McConnell

Jane McConnell

Teradata

Jane McConnell is a practice partner for oil and gas within Teradata’s Industrial IoT Group, where she shows oil and gas clients how analytics can provide strategic advantage and business benefits in the multimillions. Jane is also a member of Teradata’s IoT core team, where she sets the strategy and positioning for Teradata’s IoT offerings and works closely with Teradata Labs to influence development of products and services for the industrial space. Originally from an IT background, Jane has also done time with dominant market players such as Landmark and Schlumberger in R&D, product management, consulting, and sales. In one role or another, she has influenced information management projects for most major oil companies across Europe. She chaired the education committee for the European oil industry data management group ECIM, has written for Forbes, and regularly presents internationally at oil industry events. Jane holds a BEng in information systems engineering from Heriot-Watt University in the UK. She is Scottish and has a stereotypical love of single malt whisky.

Photo of Sun Maria Lehmann

Sun Maria Lehmann

Equinor

Sun Maria Lehmann is a leading engineer within the Enterprise Data Management Group at Equinor. Previously, she worked in data management at the Norwegian Hydrographic office and in drilling services at Statoil, including serving in advisory positions and as a member of the Blue Book Work Group and Diskos Well Committee. Sun holds an MSc in petroleum geoscience from NTNU.