Data lake solutions
Power your applications, analytics and AI with any data in an open data lakehouse
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Data lake and data lakehouse solutions and IBM

Data lakes and data lakehouses provide a centralized repository for managing large data volumes. They serve as a foundation for collecting and analyzing structured, semi-structured and unstructured data in its native format for long-term storage and to drive insights and predictions. Unlike traditional data warehouses, they can process video, audio, logs, texts, social media, sensor data and documents to power apps, analytics and AI. They can also be built as part of a data fabric architecture to provide the right data, at the right time, regardless of where it is resides.

Hadoop-based data lakes were an attempt to address these new workloads, but required hard-to-find skills for developing applications and managing the platforms. Data lakes are largely being supplanted by a new architectural approach called a data lakehouse.

How to resolve today’s data challenges with a lakehouse architecture

 

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IBM named a Leader in The Forrester Wave™: Data Management for Analytics, Q1 2023
Benefits of an open data lakehouse  Scale analytics and AI

Reduce cost and time to insight, and enhance confidence and trust in data used for applications, analytics and AI with a modern data architecture. Identify new patterns and trends to improve operations and deliver new offerings.

Simplify and make data accessible

Access existing data lakes and data warehouses on-premises or in the cloud, and integrate them with new data to unlock insights and opportunity with a modern data lakehouse and data fabric approach.

Be agile, efficient, and scalable

Deliver business value and reduce data management complexity. Start small and scale across use cases and deployments (cloud, hybrid and on-premises).

Accelerate time to trusted insights

Control data privacy and security with built-in governance and metadata management. Manage centrally and deploy globally with enterprise-wide governance solutions.

Accelerate deployment and avoid lock-in

Partner with IBM to accelerate deployments across hybrid and multi-cloud environments. Support all types of data and use cases with open source, open standards and interoperability with IBM and 3rd party services.

Drive down analytics cost

Take advantage of lower cost compute and storage, and fit-for-purpose analytics engines that dynamically scale up and down—pairing the right workload with the right analytic engine.

The IBM data lakehouse approach

Watsonx.data makes it possible for enterprises to scale analytics and AI with a fit-for-purpose data store, built on an open lakehouse architecture, supported by querying, governance and open data formats to access and share data. With watsonx.data, you can connect to data in minutes, quickly get trusted insights and reduce your data warehouse costs. Now available as a service on IBM Cloud and AWS and as containerized software.

Learn more about watsonx.data

Learn about a modern solution to distributed data landscapes: the data lakehouse.

Today’s data architecture challenges

The real-world challenges organizations are facing with big data today are multi-faceted.

New strategic approach to analytics

Today's data challenges require a new strategic approach to data management.

What is Presto?

Learn about the fast and flexible open-source query engine available with watsonx.data.

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Set up a no-cost, one-on-one call with IBM to explore data lakehouse solutions

Learn more What is a data lakehouse? What is a data lake? What is a data warehouse What is Hadoop? What is Apache Spark? What is a data mart? What is ETL? What is data management? What is a data fabric?