DATA LAKE ANALYTICS
Power Insights with Qlik's Data Lake Analytics Platform
Transform your data lake into a powerful decision engine. Unlock insights by streaming, processing, and analyzing live data to drive smarter decisions across your business.
Transform your data lake into a decision engine
Move beyond batch processing. Continuously stream and analyze data to capture value the moment it is generated.
Stream data continuously
Ingest live data streams from IoT, applications, and databases directly into your lake for immediate availability.
Reduce analysis latency
Process and query data in motion, eliminating the lag between data capture and actionable insight.
Scale intelligence globally
Deliver dashboards and predictive models across your enterprise without compromising performance.
How Qlik's data lake analytics works
Step 1: Ingest and stream data continuously
Step 2: Process and enhance data
Step 3: Generate visual, predictive, and actionable insights
Step 4: Deliver live analytics across applications and teams
Why choose Qlik for data lake analytics?
One platform for all data velocities
Seamlessly handle both data streams and historical batch data in a single environment to simplify architecture and ensure consistency.
Deploy on any cloud or object store
Run analytics on AWS, Azure, Google Cloud, or hybrid lakes without vendor lock-in or proprietary format constraints.
Zero-code orchestration for flows
Automate the ingestion, transformation, and delivery of streaming data using visual workflows that reduce engineering overhead.
Key capabilities of Qlik's data lake analytics
High-throughput streaming ingestion
Capture data from thousands of sources simultaneously with minimal latency.
In-flight data transformation
Cleanse, filter, and aggregate streaming data before it hits disk to optimize storage and query speed.
Change Data Capture (CDC)
Automatically detect and replicate source changes to the data lake.
Live visualization connectivity
Connect analytics tools directly to live data streams for up-to-the-second reporting.
Automated schema evolution
Handle changes in source data structures automatically without breaking downstream analytics.
Governed data delivery
Ensure all data is validated, cataloged, and secured before it reaches business users.
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 analytics FAQs
Data lake analytics allows you to process and analyze vast amounts of raw, unstructured, or semi-structured data directly in its native format, whereas warehousing typically requires structured, pre-processed data.
Yes, Qlik provides a unified platform that ingests, processes, and analyzes both real-time streaming data and historical batch data using consistent logic and governance.
Qlik applies automated validation, cleansing, and standardization rules as data is ingested and transformed, ensuring the lake contains trusted, analytics-ready information.