dataZap, your all-in-one solution for lightning-fast data migrations, impeccable reconciliation, and seamless integrations. Unleash the true potential of your data with a platform designed for agility, precision, and unmatched efficiency.
Seamlessly connect and interact with data across diverse platforms. Our dataZap ensures compatibility with various databases, applications, and systems, providing a unified experience for your data management needs.
Consolidate your data reconciliation tools, setup migrations, integrations, big data ingestions, and archival processes on a single platform.
With 9000+ pre-built templates, dataZap ensures coverage for over 200 applications, simplifying your data transformation across various systems.
Our data quality engine comes with pre-configured rules for profiling, cleaning, enriching, and correcting data, ensuring your data is accurate and reliable.
dataZap is a configurable, agile, and low code/no code integration platform, allowing you to adapt quickly to changing business requirements.
Our fully cloud-enabled ETL software enables immediate usage, allowing you to harness the power of the cloud effortlessly.
Pay only for the data you move, making dataZap a cost-effective solution for your organization.
In a world where data is the driving force, we stand as your trusted partner and help to transform your data challenges into opportunities. Take a glance at how the magic happens in no time.
Our platform is meticulously designed to provide a seamless integration experience, ensuring your data flows effortlessly across a diverse array of applications. Experience the unparalleled ease of connecting with over 200 applications effortlessly.
The key to success was the ability to clean and enrich master data before implementation, stay clean of master data across all systems.
The Client’s master data quality in salesforce is in bad shape with major problems like duplicates and non-standardized data for its major operational objects.
The 105 applications across the 78 entities had discrete data models, and there was no uniformity or clarity on the way the entities functioned. In order to successfully manage all applications, a common integration data model had to be created, along with enterprise-wide data quality standards & governance policies.
