Elsevier’s Entellect Platform gets a new data pipeline in order to service life sciences customers with research data in key therapeutic areas.
- Elsevier is an academic publishing company that specializes in information analytics across science, technology and medical content.
- Elsevier has many well-established academic content solutions such as Embase, Science Direct, Reaxys, Scopus, SSRN, among many more!
- Elsevier is underpinned by technology which allows then to deliver more data to customers, faster, more concisely and accurately.
- Project Results
- Formed a new multi-competency squad
- Created a new data pipeline on Elsevier’s existing Entellect Data Platform
- Established a new and innovative way of selling data to Life Sciences customers by grouping data by therapy area rather than journal title
Content is what Elsevier does! However, ensuring it is delivered on time, to the right customer, in the right way, every time is quite the challenge.
Elsevier curated and published 16% or 3000 of the world's journals in 2020 alone – that’s a lot of text for anyone to consume!
With that, they wanted to create a real-time feed of the latest Science Direct content that was technically analysed according to Medical standards, and grouped according to what therapy area the journal was talking about. This was a much-requested customer need that was impossible to deliver on, until the acquisition of a text mining company called SciBite.
Their existing software development department was creaking under the already substantial customer data requests and the platform was also underdeveloped to meet the need either.
“It’s like Lego, we need to build a new and reusable software component that slots into the existing platform that then gives us the capability to take Science Direct content, transform it and deliver it to customers in medical groupings that they are most interested in researching”
Head of Engineering
- Stand up a new and multi-skilled team of 3rd party suppliers
- Understand the existing architecture and document the ‘to-be’ solution
- Used Behaviour Driven Development techniques to break down the high-level epics into user stories and key technical steps
- Created a weekly and monthly governance structure to keep the PMO, Technology leadership, and marking up to date on the latest progress
- Drafted formal communications to the project’s closest stakeholders at key milestones
- Set up the team to work in a best-practice agile way, practicing Scrum as the delivery methodology
- Hired 3rd party consultants or experts where there were gaps in technical expertise, for example with NiFi (for data processing) or Kibana (for Elastic Search)
Results & Benefits
- Great team culture – many of the 3rd party suppliers have stayed on
- Clear product goals and priorities
- A fit-for-purpose data pipeline
- Elsevier content can now be sold by therapy area rather than just by journal title