How To Reduce Compliance Risk for Pharmaceutical and Medical Device Companies
October 27, 2025

How To Reduce Compliance Risk for Pharmaceutical and Medical Device Companies

Shankar Mahindar Redica Systems | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User

Overall Satisfaction with GoodData

At [...], we are using GoodData Platform to build Embedded Analytics solution which is integrated deep into [...]'s core platform to provide regulatory intelligence, vendor quality intelligence and inspection intelligence for Pharma, pre-market and post-market intelligence in MedTech. This solution involves building key dashboards that provides insights into the world of regulatory affairs that are actionable for our customers. The analytics solution is built on top of a semantic data model that unifies compliance data streams, is well integrated with key objects in the regulatory and quality life-sciences domain, and provides inspection trends and tracks supplier quality risk. Customers at leading Pharma and MedTech companies use these insights and data intelligence to champion quality of their products and ensure safety and compliance.
The key business problems which GoodData address for us at [...], is really being able to tap onto the unified semantic data model and get data intelligence and visual insights that help our customers prepare for inspections in a fraction of the time, identify supplier risks earlier, and reduce deviations that lead to costly findings.

Pros

  • The source datasets are often complex, semi-structured and un-linked to key entities. With GoodData, all of these datasets are unified to serve as a central semantic data model layer, building into a galaxy schema with dimensions, bridge, and facts, which then forms the backbone that powers the [...] data intelligence cloud. Building insights and dashboards become a much easier task once the underlying data model is designed. GoodData enforces certain best practices as a BI tool, which must be adhered to get the true value of the raw data. For e.g. the source FDA dashboard may just show inspection data but the Site Profile dashboard built on GoodData goes beyond the standard information and shows more insight into site risk scores and can be drilled into details. There is blog written on this topic: [...].
  • GoodData provides a rich collection of visualization options that help us create compelling story-telling via dashboards. Being well-prepared for FDA inspections is essential for maintaining product quality, regulatory compliance, and avoiding serious business setbacks. FDA inspections are critical events that can shape a company’s market access and reputation. The FDA itself offers the FDA Data Dashboard, but it doesn’t make every document available. There is a blog written on this topic: [...].
  • Medical devices and technologies do not stop evolving after they receive regulatory approval. Once a product hits the market, it faces real-world usage, compliance challenges, and an array of regulatory scrutiny. Managing these postmarket dynamics is critical to a product’s long-term success and patient safety. However, many companies struggle to keep track of relevant events across a product’s markets, from adverse event reports to changing regulations. Postmarket Intelligence developed on GoodData platform enables us to solve that problem. It empowers MedTech companies to efficiently monitor, assess, and act on postmarket data—saving time, improving decision-making, and ensuring compliance with industry standards. Anyone who is used to trying to get the data they need from the various FDA, and other regulatory agency websites, knows that collecting, cleaning, and structuring that data takes hours. And that’s before any analysis can get done. We enable customers to free up time to focus only on the high-value analysis and subsequent recommendations to leadership, rather than wrangling the data.
  • The data pipeline refresh that is provided by GoodData Platform is also quite useful from data engineering perspective. The Automated Data Distribution v2 or commonly called as ADD refresh follows a set pattern of identifying the analytical data model through output stage which helps abstract the complex table definition to simpler views that can help with quick rebuild at the data warehouse level while loading the data into GoodData's ADS storage layer. The import first way of loading data into GoodData's cloud storage, followed by querying for any aggregations or metrics on the GoodData analyzer, makes this simple and fast.
  • GoodData's latest product i.e. Cloud also offers several good features like Analytics as Code which helps software engineering teams follow a code-first approach to analytics, where building insights, dashboards or even datasets can be done in YAML templates or serviced by REST APIs. This is particularly forward thinking in the modern technology stack and evolving industry requirements. These provide seamless integration options to front-end and backend code, embedded analytics with multiple choices from HTML to React based workloads. At [...], we are currently exploring most of these features while planning for a future migration from Platform to Cloud.

Cons

  • GoodData's ADD load for the older product i.e. Platform has some limitations like error logging and debugging is cryptic. If orchestrated via any external tooling like Airflow or Prefect, the REST API based ADD loads sometime fails with HTTP 429 errors indicating as-if there are too many requests but in reality, it is sometimes due to GoodData server busy responding about the outcome of the past execution.
  • GoodData Platform's documentation though well-written sometimes lack some of the key information which could make the overall admin process a little too complex to implement. I have encountered issues trying to delete or provision workspaces, where each workspace gets tied to the parent-child hierarchy based segments and that makes the admin process operationally challenging.
  • There is a data limitation on the GoodData Platform wherein the maximum allowed characters that can be displayed on a tabular chart for a text field is 10000 characters. At [...], we work with lot of regulatory documents that are often 200+ pages long in their content. We summarize the content of such documents and enrich with our proprietary labels, before finally sharing with customers via dashboards. However, the limitation of characters to default 500 often requires us to ALTER DATATYPE using MAQL to be able to move up to 10000 characters to workaround. At times, even 10000 characters get trimmed and often do not get displayed on mouse-hover. Thus it impacts the customer experience when trying to perceive the dashboard. Note, if the dashboard is downloaded in excel or csv, then and only then the full content is observed.
  • We have launched MedTech Post-market intelligence demonstrating 22+ million post-market medical device events with their analysis of how they are linked to affected products, device problems, patient problems and manufacturers. The ease of being able to process and display such high volume data with intricate joins is done seamlessly within GoodData.
  • Another core offering from [...] is MedTech Pre-market intelligence that involves tracking the life-cycle of a product or medical device's licensing journey before it hits the market. This involved processing and supporting 2+ million device records globally and their linkages. Our customers exclaimed "You just did in 15 seconds what took me and my team 3 months to do … and I trust your data more than what we did." For more details, read here:[...]
  • [...] is the Intelligence Cloud for quality and regulatory operations, transforming regulatory complexity into trusted, proactive intelligence. We unify global regulatory intelligence, inspection data, and supplier insights so you can predict and prevent compliance risks before they happen. As part of these key offerings, we compute Site Risk scores from supplier analysis standpoint for over 300+ thousand sites and categorize risks in the different department and quality system label issue. These risk score model help customers assess how likely that supplier can get a 483 or warning letter, and what were the top issues reported during their previous inspections. These critical components help customers stay aware of the supplier quality and help them make informed business decisions that saves hundreds of thousands of dollar.
Embedding flexibility was the main reason we chose GoodData. Interactivity, customization options, and programmatic ability were all very important to us and GoodData's embedding via React SDK offers exactly that. Another reason we chose GoodData was the time to market. With the help of the professional services team, we were able to finish a complex implementation in under 6 months. Originally, we estimated it would take much longer. GoodData’s semantic layer and logical data model allow [...] to process large amounts of data and generate real-time views.
With the help of the professional services team, we were able to finish a complex implementation in under 6 months. Originally, we estimated it would take much longer. This involved the early discovery with GoodData product, followed by proof of concept and some sessions to get onboarded with a trial account. After reviewing the data, scale, complexities involved and tech stack compatibility, it was a fast integration project followed by quick learning curve of the engineering team to support the analytics product. Overall, implementation time was 50% shorter with GoodData than with other traditional BI tools
The source datasets are often complex, semi-structured and un-linked to key entities. With GoodData, all of these datasets are unified to serve as a central semantic data model layer, building into a galaxy schema with dimensions, bridge, and facts, which then forms the backbone that powers the data intelligence. Building insights and dashboards become a much easier task once the underlying data model is designed. The Analyzer on the GoodData Platform gives a simple, drag-drop option for analyst and engineers alike to build visuals and the dashboarding canvas is also simple to use. The LDM modelling layer is simple and intuitive for BI and data engineers to design.
Embedding flexibility was the main reason we chose GoodData. Interactivity, customization options, and programmatic ability were all very important to us and GoodData's embedding via React SDK offers exactly that. Implementation time was 50% shorter with GoodData than with other traditional BI tools. GoodData’s semantic layer and logical data model allow [...] to process large amounts of data and generate real-time views.

Do you think GoodData delivers good value for the price?

Yes

Are you happy with GoodData's feature set?

Yes

Did GoodData live up to sales and marketing promises?

I wasn't involved with the selection/purchase process

Did implementation of GoodData go as expected?

Yes

Would you buy GoodData again?

Yes

GoodData is well suited for classic business intelligence and data analytics solution involving visually driven content using charts and graphs. It's rich collection and drillable interactions make it perfect for embedded analytics where application workflow is tied to analytics. However, GoodData may not be ideal or appropriate for such solutions that require lot of textual content to be displayed with the help of tabular visuals, particularly in regulated industries where the key is in the details. This is all tied to the platform limits that force the default layout to pre-filter.

GoodData Feature Ratings

Drill-down analysis
8
Formatting capabilities
4
Report sharing and collaboration
8
Pre-built visualization formats (heatmaps, scatter plots etc.)
6
Location Analytics / Geographic Visualization
6
Predictive Analytics
4
Multi-User Support (named login)
Not Rated
Role-Based Security Model
7
Multiple Access Permission Levels (Create, Read, Delete)
7
Single Sign-On (SSO)
Not Rated
REST API
8
Javascript API
Not Rated
iFrames
Not Rated

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