OpenText – Core Data Analytics

OPENTEXT
CORE DATA ANALYTICS

My time at OpenText was split between working on SaaS / technical products using the heritage DS and JATO DS.

OpenText Core Analytics Database

I worked on thi SaaS (or DBaaS) product – an interface for OTs high-performance analytics and ML platform for querying a Data Lakehouses. I had limited influence of the UX for this project but I’ve included some of the assets I was able to create. My role was to use the existing UX and build out workflows in collaboration with the product team and provide them with finished designs for the upcoming releases.

  Midway through this work, OpenText released a new design system called JATO. It became a priority to port all new and existing applications to the new design system. As the design system wasn’t fully developed at this point, we were testing and validating concepts for the DS team as we were going along. This and the following screens are a samples of how JATO could look and we had to improvise with our concepts. This work helped the DS team progress the maturity of the design system and validate the components working cohesively in a real life scenario.

User Personas

Data Engineer

Core needs

Creating and maintaining ETL (Extract, Transform, Load) pipelines to move data from various sources into data lakehouses.
Designing and implementing data models and architectures that optimise data storage, retrieval, and analysis.
Managing databases, including relational databases, NoSQL databases, and data lakes, ensuring data is stored efficiently and securely.

Behaviours

Highly technical user with a background in development and database management.
Wants a high level of control when querying data.
Knows SQL syntax to an advanced level amongst other languages.

Pain points

Queries are slow to run so needs to be confident the tools provide the right level of control for focusing in on critical data.
Some online tools don’t provide adequate feedback when debugging queries. An expected feature based on experience of using traditional database management tools.

Data Analyst

Core needs

Needs to be able to gather and clean data to provide business insights to support decision-making.
Identify trends, patterns, and correlations within datasets to help improve strategies, operations, and overall performance.
Key responsibilities – statistical analysis, data visualisation, communicating findings to stakeholders.

Behaviours

Non-technical background.
Familiar with common UI concepts as an avid web / productivity tool user.
Knows of SQL but no/little experience querying with it. More comfortable with spreadsheets or advanced online querying tools.

Pain points

Avoids highly technical tools and doesn’t have the background to feel comfortable writing code.
Gets frustrated with tools lacking the level of control to sort and filter data to a finite set of results.