Elevating Data Management: Unveiling the Pillars of a Trusted Data Foundation with Quantexa

Milda_Klimasauskaite · March 4

Hi Community!

We are all well aware that data teams are faced with increasingly complex business challenges and not being able to make the most of their data makes it very hard to reach strategic, tactical and operational goals set by their organizations.

The solution to that is building a truly trusted data foundation.

As part of Quantexa’s ongoing commitment to providing best-in-class Data Management solutions to address the latter, the team at Quantexa has had a brainstorm of what aspects are crucial when choosing one, and what we – as a team – are focusing on when building our solutions.

Let’s go through some of the main components.

1. Quick multi-source data ingestion:

A common challenge is the complexity and time required to get data in the platform. To address that, we apply intelligent data cleansing and enrichment processes and accelerate data onboarding with low-code, schema-agnostic, scalable, high-performance data preparation and ingestion for both internal and external data sources.

2. Truly accurate data matching through Entity Resolution:

Without a holistic view of your data, it’s impossible to make informed decisions. Our AI-powered Entity Resolution uses transparent and tunable models that are designed to address common problems associated with traditional matching methods such as data availability and quality issues with proven 99% accuracy.

3. Quality scoring and corrections:

Even with the best matching engines, there is always going to be a need for a Data steward’s input: monitoring and continuous data quality enhancement. We provide tools to review the quality score of each entity down to understanding exactly what contributed to a score, quickly identifying source system issues to address. There is also an easy way to correct the data, e.g. merge entities, without needing to adjust the source data, which is incredibly valuable both for immediate use in your analytics and also for any consuming system.

4. The use of Graph Analytics:

Connecting data in a meaningful way is a crucial, but the next step is to really uncover the relationships you need for the business problem you are solving. For that our users are able to use advanced Graph Analytics technology to uncover the intricate networks of real-world connections and relationships between entities – building even complex corporate hierarchies or family relationships.

Take a look at our video, where @Zayd_Sukhun, Solutions Lead, shows examples of these capabilities in the Quantexa platform.

https://www.youtube.com/watch?v=PBjyv4r6D3s&t=11s

Find this article interesting? Check out these related posts:

https://community.quantexa.com/discussion/2051/entity-resolution-tooling-and-best-practices-on-the-docs-site

https://community.quantexa.com/discussion/27/why-your-data-integration-graph-needs-entity-resolution