A data lake is a centralized repository for managing extremely large data volumes. It serves as a foundation for collecting and analyzing structured, semistructured, and unstructured data in its native format to drive new insights, better predictions, and improved optimization. Unlike traditional data warehouses, data lakes can process video, audio, logs, texts, social media, sensor data and documents to power apps, analytics, and AI. Data lakes can be built as part of a data fabric architecture to provide the right data, at the right time, regardless of where it is resides.
A data lakehouse is an evolution in analytic data repositories that supports data acquisition to refinement, delivery and storage with open data and open table formats. IBM enables you to get more from your existing investments in data warehouses and data lakes by building data lakehouse access to a larger variety of data for increased flexibility.
Read the most common misconceptions about cloud data warehouses that cause companies to hesitate to move to a hybrid-cloud strategy
Understand and anticipate customer behaviors with complete, governed insights.
Spot patterns and trends to reduce waste and overhead through diverse analytic and AI techniques.
Promote auditability and transparency with metadata-powered, native data access in a governed data lake.
Speed time to value with self-service data exploration and discovery for any user.
Increase collaboration, and reduce the time and cost of managing disparate systems and tools in an integrated environment.
Turn your open-source and ecosystem investments into innovation opportunities with enterprise-ready secure data lakes.
Reuse the data lake for 360° customer and operational intelligence, governance, and risk and compliance reporting.
Ingest and integrate with transactional, operational, and analytical data to promote a complete insight.
Extend a data fabric to provide right data at the right time on a common foundation for staging, storage and access.
Build and maintain a data foundation that powers data cataloging, curation, exploration, and discovery needs.
Take a hybrid, multicloud approach to access any data from any locations from years of records to real-time data.
Integrate and expand analytics across multiple data repositories to drive innovation and optimization at scale.
Rely on scale, security, resiliency and flexibility of IBM data lakes that helps run the world’s most mission-critical environments.
Enjoy a one-stop shop at IBM including support, IBM ecosystem, and open-source tooling.
Partner with IBM industry experts who have in-depth experience and know-hows in successful deployments.
Rely on a data lake governance that houses raw structured and unstructured data — trusted, secured, and governed — with automated privacy and security anywhere.
Use data integration tools such as ETL, data replication, and data virtualization combine data from disparate sources into valuable data sets.
Query data directly in the data lake without duplication or movement with the data virtualization of IBM Watson® Query.
Query across Hadoop, object storage, and data warehouses with a hybrid SQL-on-Hadoop engine.
Harness the power of transactional, operational, and analytic data for mission-critical environments.
Achieve simplicity, scalability, speed and sophistication — all deployable as a service, on the cloud and on premises.
Simplify your data landscape with a universal query engine that accesses your disparate data sources.
Activate business-ready data for AI and analytics with intelligent cataloging, backed by active metadata and policy management.
Connect the right data to the right people at the right time with IBM and third-party services spanning the data lifecycle.
ING’s centralized governed data lake seemed to serve its organizational and regulatory needs — but their chief AI architect wanted more out of this business-critical environment. The amount of manual work, the number of subject matter experts, and the associated maintenance costs became inhibitors to getting more data into the data lake.
Cloudera and IBM work together to help you build a data lake for analytics and AI. You can collect, store, govern and secure raw data from across your business anywhere on premises or on any cloud. Cloudera Data Platform is available through a one-stop shop at IBM to help you simplify licensing, procurement, support and deployment.
Integrate a data lake into your data management strategy to generate new insights from more data types and sources.
Accelerate your research by exploring five myths about data lakes, such as "Hadoop is the only data lake."