Quantexa’s capabilities for data ingestion provide a fast, simple, and scalable way of getting data into the Quantexa platform, reducing the need for cumbersome data wrangling and speeding up the time to value.
Our data ingestion enables data scientists and data-driven analysts to easily prepare, configure, and ingest billions of data points across multiple formats for use in AI-powered decision intelligence via our low-code data ingestion framework and UI.
Ingest all your data into Quantexa, from any data source, with minimal preparation required.
Quantexa’s multi-source data ingestion enables you to safely and speedily ingest and fuse all of your internal and external data sources at huge scale, whether structured, unstructured, or semi-structured:
Transactional, customer, and account data
Third-party licensed data
Quantexa’s data ingestion allows both technical and non-technical users to easily and quickly prepare data for use in entity resolution and graph analytics:
Standardized data ingestion framework for rapid onboarding
Out-of-the-box AI models to cleanse and enrich data
Scales to billions of data points in batch or real time
Benefits
Significantly reduce the ETL burden on your data engineering teams and ensure they focus on higher value tasks, by ingesting data via either our low-code or no-code data ingestion tools which automate a multitude of repetitive tasks.
If you are leaving some data out in order to fit a required data model, your data is incomplete, leading to potential for missed insights about risks and opportunities. This is why Quantexa is data model agnostic.
Faster data onboarding logically leads to faster time to value. But just as beneficial is the operational efficiency of having one data store, ingested once (with no duplication), for multiple use cases, reducing costs and realizing value faster.
By unifying your data with Quantexa's data ingestion and performing entity resolution, you will eliminate data model discrepancies and data quality issues, so that decisions can be made with confidence and transparency.
Split unstructured data such as names and addresses into their component parts, e.g., Forename=Michael and Surname=Greene.
Cleanse raw data to prepare it for optimal entity resolution, e.g., by removing punctuation, default values, and generic text (limited, organization).
Transliterate and standardize different presentations of the same data with a single version for consistent formatting formatting (e.g., changing USA, United States, or America to just US).
Raw data is mapped to a hierarchical model, structuring data in a way that enables the expression of relationships between different entities.
Import projects and data sources from existing configurations to speed up future data onboarding.
Quantexa offers both dynamic and batch ingestion to ensure you get the best of both worlds when it comes to data processing.
Data ingestion is made easy for data analysts and developers with an intuitive UI and low-code tools.
Our standardized data ingestion framework provides technical users with everything you need to quickly and easily ingest data into the Quantexa platform. Simply upload your data set and follow our best practice templates for every step of the data ingestion process.
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