Data management software and solutions

Promote agility and efficiency with end-to-end data management

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Overview

Data management for agility and efficiency

Today, data is even more distributed than ever requiring supporting technologies to evolve and new solutions to address current data management issues in innovative and unprecedented ways.  Data management is designed to help you achieve consistent access to and delivery of data across all data structures and subject areas in your enterprise. Applying a comprehensive data management plan helps meet data consumption requirements of all applications and business processes.  

Additionally, a data fabric approach simplifies access and facilitates self-service data consumption that is independent of environment, process, utility and geography. A data fabric enables enterprises to automate data usage to maximize their value chain. 

IBM data management empowers businesses to improve outcomes using any data for analytics or applications across any cloud including on-premises, public and private. Gain resiliency, reliability, scalability and availability with security and quality with IBM, and get more from multimodal, multicloud data ecosystems to increase your enterprise readiness for data management.

Read Forrester’s “Total Economic Impact™ (TEI) of IBM Data Management”

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Benefits

Why IBM for data management IBM data management helps improve outcomes by using any data for analytics or applications across any cloud and helps you automate end-to-end data management. Promote agility and efficiency

Harness data for modern apps, analytics, and AI.  Spot new patterns and trends to improve operations and create new offerings.

Simplify and unify data tiers

Get value from any transactional, operational and analytical data. Access structured and unstructured data in real-time and batch.

Help ensure resiliency, reliability, and scalability

Promote business continuity and mitigate data-related outages. Start small and scale across use cases and deployments.

Meet governance, risk, compliance, and sustainability objectives

Take a data-driven approach to meeting regulatory, corporate and environment mandates. Protect data privacy and security end-to-end.

Automate and govern your data

Reduce complexity and speed time to value through automated data management. Improve decision-making and act on insights faster with AI-powered self-service.

Speed deployment and avoid lock-ins

Partner with IBM to manage data ecosystems. Implement business analytics and conversational AI faster in a data fabric architecture.

Use cases

Highly resilient transactional and operational data Maintain highly performant, transactional integrity at scale for online transactional processing (OLTP) and empower real-time decision making with updated patterns and conditions with intelligent operational data. Puma runs databases faster Norfolk Southern keeps shipments on track

Unified analytical data Make data and analytics simple, trustworthy and secure across deployments, workloads and use cases. Bic Camera reduces batch processing time

Multimodal, multicloud data ecosystems Speed mission-critical delivery by simplifying your data ecosystems with IBM. Active international grows client revenues

DataOps for AI engineering Make data ready for AI by integrating DevOps, DataOps and ModelOps. Vanguard puts DataOps to work

AI-powered self service Manage data built for AI and with AI by automated model development and built-in intelligence. The Health Collaborative navigates crises with data

Data-driven governance and security Improve governance, compliance and risk posture with data visibility, auditability and transparency. ING maintains governance without manual effort

Case studies

Data management case studies
Decreased costs and enhanced performance Owens-Illinois realized such benefits as a seven-figure total cost of ownership savings, faster query performance and reduced server footprint by migrating from Oracle Database to IBM Db2. Watch the Owens-Illinois video (2:53)

Break down data barriers knowis, a banking solutions provider, breaks down their customers' data barriers by deploying IBM Db2 on Cloud, allowing them to serve smaller banking and financial institutions. Watch the knowis video (1:34)

How it works

Data management: How it works

Data management has evolved since its inception in the 1980s. It’s comprised of a set of tools, methods and architectures for collecting, accessing, maintaining and driving value from data in an agile, secure and cost-effective manner. With hardware advancements and the rise of cloud-based solutions, it’s become easier for an organization to harness the power of insights for applications, analytics, and AI.

Data management spans across disciplines. Organizations need a unified approach to data with pre-integrated, open and complete data management technologies. Dig deeper into the building blocks of data management and take your steps toward becoming a data-driven business.

  • Database management – Access, store and maintain data to help organization drive value.
  • Master data management - Empower business and IT users to collaborate and innovate with a trusted 360-degree view of master data across the enterprise.
  • Data quality - Cleanse data, manage it and support better decision-making.
  • Data integration - Transform structured and unstructured data from different sources into a trusted, unified view available to any system.
  • Data governance - Understand and govern all enterprise data to mitigate risk and accelerate insights.
  • Data virtualization - Gain a single view of disparate data without data movement.
  • Data lake – Store and manage extremely large data volumes of structured, semi-structured and unstructured data in its native format.
  • Data warehousing – Support business intelligence and analytic initiatives with a cloud data warehouse.
  • Data migration - Accelerate your journey to hybrid cloud with simplified tools and expert services.
  • Data science - Build and scale AI with trust and transparency.

With IBM data management, you can choose and combine any of the integrated solutions including DataOps, trustworthy AI, business analytics and conversational AI with a data fabric. 

IBM also helps you bring together and govern IBM, IBM ecosystem and open-source frameworks for your teams of any skill level. You can improve productivity of application development with an automated, simplified approach to data management and ease of change management that is micro-service driven.

As practitioners interact with IBM data management framework, systems of engagement, interaction and data flows cut across transactional, operational and analytical data. This helps optimize delivery and improve business outcomes at scale with built-in governance, risk and compliance.


IBM named a Leader in 2021 Gartner® Magic Quadrant™ Cloud Database Management Systems

Next steps

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