Data Lake Solutions

Overview

Data lake solutions and IBM

A data lakehouse is an evolution in analytic data repositories that supports acquisition to refinement, delivery, and storage with open data and open table formats. This can help you 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.

A data lakehouse is an evolution in analytic data repository that supports acquisition to refinement, delivery, and storage with open table and format. IBM enables you to get more from your existing investment in data warehouses and data lakes, and supports the building of data lakehouses to a larger variety of data for increased flexibility. 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.

Read Forrester Total Economic Impact™ (TEI) of IBM Data Management

What is a data lake? (05:17)

Benefits

Improve customer experience

Understand and anticipate customer behaviors with complete, governed insights.

Streamline operations

Spot patterns and trends to reduce waste and overhead through diverse analytic and AI techniques.

Manage governance, risk, and compliance

Promote auditability and transparency with metadata-powered, native data access in a governed data lake.

Increase agility and productivity

Speed time to value with self-service data exploration and discovery for any user.

Unify users, tools, and repositories

Increase collaboration, and reduce the time and cost of managing disparate systems and tools in an integrated environment.

Harness the power of open source and existing skills

Turn your open-source and ecosystem investments into innovation opportunities with enterprise-ready secure data lakes.

Capabilities

Core technology for high-value use cases

Reuse the data lake for 360° customer and operational intelligence, governance, and risk and compliance reporting.

End-to-end data management

Ingest and integrate with transactional, operational, and analytical data to promote a complete insight.

Flexibility to handle analytic and AI needs

Extend a data fabric to provide right data at the right time on a common foundation for staging, storage and access.

Handle metadata, queries, and data curation

Build and maintain a data foundation that powers data cataloging, curation, exploration, and discovery needs.

Scale with access to virtually any data

Take a hybrid, multicloud approach to access any data from any locations from years of records to real-time data.

Ease of extending your data warehouse

Integrate and expand analytics across multiple data repositories to drive innovation and optimization at scale.

Why IBM

Enterprise-ready from day one

Rely on scale, security, resiliency, and flexibility of IBM data lakes that helps run the world’s most mission-critical environments.

Simplify procurement deployment

Enjoy a one-stop shop at IBM including support, IBM ecosystem, and open-source tooling.

World-class data and AI innovation and experience

Partner with IBM industry experts who have in-depth experience and know-hows in successful deployments.

Foundation

Embedded governance

Secure data sharing is crucial when multiple teams access enterprise data. You can rely on a data lake governance that houses raw structured and unstructured data — trusted, secured, and governed — with automated privacy and security anywhere.

Automated integration

Data integration tools that combine data from disparate sources into valuable data sets. Tools such as ETL, data replication, and data virtualization can extract large volumes of data from source systems and load it to a data warehouse or cloud source.

Virtualization

Traditional integrations struggle to connect app to object stores. Data is often moved from the data lake to a costly data warehouse, but with the data virtualization of Watson Query, you can query data directly in the data lake without duplication or movement.

Data lake solutions

IBM Db2 BigSQL

Powerful data query across Hadoop, object storage, and data warehouses with a hybrid SQL-on-Hadoop engine.

IBM Db2

Harness the power of transactional, operational, and analytic data for mission-critical environments.

IBM Netezza

Achieve simplicity, scalability, speed, and sophistication — all deployable as a service, on cloud and on premises.

IBM Watson Query

Simplify your data landscape with a universal query engine that accesses your disparate data sources.

IBM Watson Knowledge Catalog

Activate business-ready data for AI and analytics with intelligent cataloging, backed by active metadata and policy management.

IBM Cloud Pak for Data

Connect the right data to the right people at the right time with IBM and third-party services spanning the data lifecycle.

Case study

Partner spotlight

Data lake use cases

Financial services

Two office workers in discussion at a desk

Improve customer targeting, make better informed underwriting decisions and provide better claims management while mitigating risk and fraud.

Read the brief (492 KB)

Healthcare

Improve direct patient care, the customer experience, and administrative, insurance and payment processing while responding quicker to emerging diseases.

Read the brief (1.3 MB)