DataOps platform solutions
Organize your data to be trusted and business-ready for your journey to AI
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DataOps platforms for better, faster data

Your data is everywhere, and that's part of the problem. Siloed data becomes an even bigger problem when your data and development teams also work in silos, causing a slow response to any incident. This lack of collaboration affects other areas of your business, too, from bug fixing to goal setting, making overall data use and operations inefficient.

With an IBM DataOps platform, you can eliminate the distinction between data- and development-focused teams through collaborative work to develop an overview of the data acquisition journey. As a result, incident responses will accelerate, bugs will be fixed faster and a cohesive team will be able to set and update performance goals in real-time. Your data will be agile, accurate and efficient from end to end.

 
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Scale AI workloads, for all your data, anywhere

DataOps capabilities

Data governance

Data integration
Introducing DataStage as a Service Anywhere - execute ETL and ELT Pipelines in any Cloud, Data Center or On-premises. 
DataOps platform benefits Solve inefficient data-generation and processing problems and improve poor data quality caused by errors and inconsistencies with IBM DataOps platforms. End-to-end efficient data

Access agile software to curate, govern, manage and provision data—connected and optimized at every stage of the data lifecycle—across the entire supply chain.

Secure and compliant data

Apply controls for automated, customizable data quality, masking, tokenization and more so data is protected and compliance-verified at every step of its journey.

 Lower data costs

Offer stakeholders self-service access. This quality will make data easily discovered, selected, and provisioned to any destination while reducing IT dependence, accelerating analytic outcomes and lowering data costs.

Data compliance and privacy Comply with complex regulations and protect sensitive data more effectively by automating and integrating data governance, data quality and policy management. Read: How to turn data compliance into a foundation for innovation
Drive business insights Discover DataOps solutions that can monetize your data and deliver up to 87% savings in development costs with automated design. Read: Three DataOps strategies to monetize your data
DataOps tools IBM Knowledge Catalog
A modern data catalog designed to help data scientists, data governance professionals and business analysts activate data for AI, business operations and analytics
 IBM® DataStage®
A highly scalable data integration tool for designing, developing and running jobs that move and transform data; can be deployed on IBM Cloud Pak for Data, IBM Cloud® or on premises
 IBM Cloud Pak® for Data
A flexible multicloud data platform that integrates all your data, whether on premises or on any cloud, while helping keep it more secure at its source
 IBM Databand
A cloud-native, data observability platform that helps data teams detect their data incidents earlier and resolve them faster so they can deliver more reliable data
Data governance
Catalog, protect and govern all data types, trace data lineage and manage data lakes.
 Data integration
Integrate, replicate and virtualize data in real time to meet data access and delivery needs accross multiple clouds.
 Master data management
Get a single, trusted, 360-degree view of data and enable users to know their data.
 Data quality
Cleanse and manage data while making it available accross your entire organization.
 Data preparation
Transform large amounts of raw data into quality, consumable information.
 Data replication
Provide real-time change data capture and synchronization to make data available fast.
 Data cataloging
Automate metadata and policy management, provide consistent definitions and enable self-service management of high-quality enterprise data.
IBM named a Leader in the 2022 Gartner® Magic Quadrant™ for Data Quality Solutions
DataOps case studies See and hear how IBM clients use our DataOps platform solutions to help themselves and their clients. Tailoring customer solutions at scale

Modernizing its information architecture allowed Flagstar Bank to provide faster and more accurate data to its customers through their customized solutions.

Watch Flagstar Bank's Data Quality Architect speak (1:47) Protecting customer privacy and beyond

While applying customer data privacy practices as part of data governance, Vanguard also became a digital transformation leader in its industry.

Watch Vanguard's Senior Solutions Architect speak (1:07) Serving Sonoma County residents

With a master data management platform, Sonoma County could connect four disparate data pools of 91,000 clients to serve their community better.

Watch Sonoma County's Department of Health Services Director speak (1:45)
DataOps resources DataOps interactive guide
Explore how IBM DataOps builds a scalable and agile data-driven culture through automation, data quality and governance through this interactive guide.
 IBM DataOps methodology and practice
Read how the IBM DataOps methodology and practice can help you deliver a business-ready data pipeline.
 Leaders embrace DataOps
Learn what defines a leader, how a leader embraces DataOps and how DataOps benefits AI and other business initiatives.
 An introduction to the DataOps discipline
Learn about DataOps dimensions, the team and the process. Then, learn how to organize data as part of the implementation of DataOps using IBM Cloud Pak® for Data; set up IBM Cloud Pak for Data on Red Hat® OpenShift®; set up governance artifacts for the data; and more.
 What is DataOps?
Read this blog article about DataOps, a different perspective of its definition and how it works.
Next steps

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