DATA LAKE MANAGEMENT
Seamlessly Manage and Scale Your Data Lake With Qlik's Data Lake Management
Manage and scale your data lake efficiently. Automate ingestion, governance, and analytics-ready data delivery.
Power modern analytics with automated,
governed data lake management
Turn your data lake into a value generator. Automate the hard work of ingesting, refining, and provisioning data.
Streamline data ingestion from supported sources into your data lake
Eliminate scripting with a universal ingestion engine that loads data from databases, mainframes, and SaaS apps efficiently.
Automate lakehouse data processing for analytics at scale
Automatically transform raw lake data into structured, query-ready formats (like Parquet/Delta).
Ensure trusted, governed data across the lake environment
Apply consistent security and governance policies to prevent your data lake from becoming a data swamp.
How Qlik's data lake management platform works
Step 1: Ingest and consolidate data from cloud and on-prem sources
Step 2: Transform and organize data lake assets
Step 3: Generate predictive, visual, and AI-driven insights
Step 4: Provision accurate data to datamarts and analytics tools
Why choose Qlik for data lake management?
Governance built-in
Automatically catalog technical and business metadata to ensure data is findable, understandable, and compliant.
Future-proof architecture
Optimize performance for modern lakehouse architectures like Databricks and Snowflake without vendor lock-in.
Manage visually
Design and monitor complex lake pipelines using an intuitive visual interface that simplifies operations.
Key capabilities of Qlik's data lake management platform
Automated data lake workflows and pipelines
Orchestrate end-to-end data flows with dependency checking and error handling.
AI-assisted modeling and data quality enhancements
Use AI to optimize data structures and improve data quality within the lake automatically.
Natural language queries and AI-generated SQL
Interact with data lake assets using natural language to generate optimized SQL queries.
ACID transaction support
Ensure data consistency in the lake with support for modern table formats like Delta Lake and Iceberg.
Continuous refinement
Automatically merge near real-time updates (CDC) into the lake without complete reloads.
Cost control
Optimize storage tiers and compute usage to manage cloud costs effectively.
Trusted by leading enterprises worldwide
What our customers say
We needed to consolidate data in one place, from heterogeneous sources, updated in almost real-time. That’s what Qlik enables for us.
Connect to 500+ data sources with Qlik’s analytics integrations
SAP
Adobe
IBM
AWS
MySQL
Jira
Azure
MS SQL
Apache
Mongo DB
SAP
Adobe
IBM
AWS
MySQL
Jira
Azure
MS SQL
Apache
Mongo DB
SAP
Adobe
IBM
AWS
MySQL
Jira
Azure
MS SQL
Apache
Mongo DB
SAP
Adobe
IBM
AWS
MySQL
Jira
Azure
MS SQL
Apache
Mongo DB
SAP
Adobe
IBM
AWS
MySQL
Jira
Azure
MS SQL
Apache
Mongo DB
Oracle
Salesforce
Workday
Apache Iceberg
CircleCI
Zendesk
Snowflake
Databricks
OpenAI
Intuit
Oracle
Salesforce
Workday
Apache Iceberg
CircleCI
Zendesk
Snowflake
Databricks
OpenAI
Intuit
Oracle
Salesforce
Workday
Apache Iceberg
CircleCI
Zendesk
Snowflake
Databricks
OpenAI
Intuit
Oracle
Salesforce
Workday
Apache Iceberg
CircleCI
Zendesk
Snowflake
Databricks
OpenAI
Intuit
Oracle
Salesforce
Workday
Apache Iceberg
CircleCI
Zendesk
Snowflake
Databricks
OpenAI
Intuit
Resources
Data Lake Management Platform FAQs
Yes, Qlik fully supports modern open table formats to provide data warehouse-like reliability on data lakes.
Yes, the platform optimizes data for high-performance SQL querying via engines like Presto, Trino, or Spark SQL.
The platform automatically detects schema changes in source systems and propagates them to the data lake to prevent pipeline failures.