Onboarding
Qualytics is a comprehensive data quality management solution, designed to help enterprises proactively manage their full data quality lifecycle at scale through automated profiling, contextual data quality checks, quality rule inference, anomaly detection, remediation, tailored notifications, and more.
This comprehensive document is designed to help enterprises get started with Qualytics, ensuring a smooth and efficient onboarding process.
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Onboarding Process
Qualytics onboarding begins with understanding your enterprise's requirements. Based on your data records, it offers a tailored approach to smoothly onboard you to the platform.
1. Screening & Criteria Gathering
Schedule a demo with us to help our team understand your enterprise data. During this session, the Qualytics team will create the plan to identify key success criteria and tailor the deployment to meet your specific needs, exploring relevant use cases.
2. User Invitations
Once the deployment setup is complete, Qualytics sends invitations to the provided email addresses. These invitations include instructions for accessing the platform and assigning admin or member roles based on your preferences. Admins have full access to configure and manage the platform, while members have access according to the permissions set by the admins.
Deployment Options
Qualytics offers flexible deployment options to seamlessly plug and acknowledge your data infrastructure requirements.
1. SaaS Deployment (Default)
The Software as a Service (SaaS) deployment is a fully managed service hosted by Qualytics. This option provides ease of use and minimal maintenance, allowing your team to focus on data quality management without worrying about infrastructure upkeep. SaaS deployment offers rapid scalability and seamless updates, ensuring you always have access to the latest features and improvements.
2. On-Premise Deployment
This option is ideal for organizations that prefer to keep their data within their own data centers. By deploying Qualytics on-premise, you maintain complete control over your data and its security, ensuring compliance with internal policies and regulations.
Tip
This deployment option is recommended for customers with sensitive data
Frequent Asked Questions (FAQs)
Q 1: What type of support is provided during a POC?
A 1: A dedicated Customer Success Manager, with mandatory weekly check-ins.
Q 2: What are the deployment options for POC?
A 2: Qualytics offers deployment options for Proof of Concept (POC) primarily as a Software as a Service (SaaS) solution.
Q 3: What type of data should we use for a POC?
A 3: In most cases, potential customers use their actual data during a POC. This provides the best representation of a live instance of Qualytics. Some customers use cleaned data to remove PII or sample test data.
Q 4: Are there limitations to data size for POC?
A 4: There are no limitations to data size for a Proof of Concept (POC)
Q 5: What type of support is provided during the Onboarding process?
A 5: A dedicated Customer Success Manager, with mandatory weekly check-ins.
Q 6: What types of data stacks does Qualytics support?
A 6: Qualytics supports two types of data stacks: modern solutions and legacy systems.
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Modern Solutions
Qualytics supports modern data platforms to ensure robust data quality management across infrastructures. This includes solutions like Snowflake, Amazon S3, BigQuery, etc.
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Legacy Systems
Qualytics also integrates with legacy systems to maintain high standards of data quality across all data sources. This includes reliable and scalable relational database management systems MySQL, Microsoft SQL Server, etc.
To integrate these data stacks refer to the quick start guide.
Q 7: What types of database technology can you connect in Qualytics?
A 7: Qualytics supports connecting to any Apache Spark-compatible datastore, including relational databases (RDBMS) and raw file formats such as CSV, XLSX, JSON, Avro, and Parquet.
Q 8: What is an enrichment datastore?
A 8: An Enrichment Datastore is a user-managed storage location where the Qualytics platform records and accesses metadata through a set of system-defined tables. It is purpose-built to capture metadata generated by the platform's profiling and scanning operations.
Q 9: Can I download my metadata and data quality checks?
A 9: Yes, Qualytics's metadata export feature is specifically designed to capture the mutable states of various data entities. This functionality enables the export of Quality Checks, Field Profiles, and Anomalies metadata from selected profiles into a designated enrichment datastore.
Q 10: How is the Quality Score calculated?
A 10: Quality Scores are measures of data quality calculated at the field, container, and datastore level and recorded as a time series enabling you to track movement over time. A quality score ranges from 0-100, with higher scores indicating higher quality.
Q 11: What is a catalog operation?
A 11: The Catalog Operation is run on a datastore to import the named collections (e.g., tables, views and files) of data available within it. The operation will also attempt to automatically identify the best way to support:
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Incremental scanning
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Data partitioning
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Record identification
Q 12: What is a profiling operation?
A 12: A Profile Operation will analyze every available record in all available containers in a datastore. Full Profiles provide the benefit of generating metadata with 100% fidelity at the cost of maximum compute time.
Q 13: What is a scan operation?
A 13: The Scan Operation is executed on a datastore to assert the data quality checks defined for the named collections of data (e.g., tables, views and files) within it. The operation will:
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Produce a record anomaly for any record where anomalous values are
detected.
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Produce a shape anomaly for anomalous values that span multiple
records.
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Record the anomaly data along with related analysis in the associated
Enrichment Datastore.