Alternatives to IBM InfoSphere Information Server

The most accurate, complete, and timely data provides the best insight. Minitab Connect empowers data users across the enterprise with self service tools to transform diverse data into a network of data pipelines that feed analytics initiatives, foster collaboration and foster organizational-wide collaboration. Users can seamlessly combine and explore data from various sources, including databases, on-premise and cloud apps, unstructured data and spreadsheets. Automated workflows make data integration faster and provide powerful data preparation tools that allow for transformative insights. Data integration tools that are intuitive and flexible allow users to connect and blend data from multiple sources such as data warehouses, IoT devices and cloud storage.

Manta is a unified data lineage platform that serves as the central hub of all enterprise data flows. Manta can construct lineage from report definitions, custom SQL code, and ETL workflows. Lineage is analyzed based on actual code, and both direct and indirect flows can be visualized on the map. Data paths between files, report fields, database tables, and individual columns are displayed to users in an intuitive user interface, enabling teams to understand data flows in context.

AWS Glue is a fully managed data integration solution that simplifies the process of discovering, preparing, and merging data for purposes such as analytics, machine learning, and application development. By offering all the necessary tools for data integration, AWS Glue enables users to begin analyzing their data and leveraging it for insights within minutes rather than taking months. The concept of data integration encompasses various activities like identifying and extracting data from multiple sources, enhancing, cleaning, normalizing, and consolidating that data, as well as organizing and loading it into databases, data warehouses, and data lakes. Different users, each utilizing various tools, often manage these tasks. Operating within a serverless environment, AWS Glue eliminates the need for infrastructure management, automatically provisioning, configuring, and scaling the resources essential for executing data integration jobs. This efficiency allows organizations to focus more on data-driven decision-making without the overhead of manual resource management.

IRI Voracity is an end-to-end software platform for fast, affordable, and ergonomic data lifecycle management. Voracity speeds, consolidates, and often combines the key activities of data discovery, integration, migration, governance, and analytics in a single pane of glass, built on Eclipse™. Through its revolutionary convergence of capability and its wide range of job design and runtime options, Voracity bends the multi-tool cost, difficulty, and risk curves away from megavendor ETL packages, disjointed Apache projects, and specialized software. Voracity uniquely delivers the ability to perform data: * profiling and classification * searching and risk-scoring * integration and federation * migration and replication * cleansing and enrichment * validation and unification * masking and encryption * reporting and wrangling * subsetting and testing Voracity runs on-premise, or in the cloud, on physical or virtual machines, and its runtimes can also be containerized or called from real-time applications or batch jobs.

Tokern offers an open-source suite designed for data governance, specifically tailored for databases and data lakes. This user-friendly toolkit facilitates the collection, organization, and analysis of metadata from data lakes, allowing users to execute quick tasks via a command-line application or run it as a service for ongoing metadata collection. Users can delve into aspects like data lineage, access controls, and personally identifiable information (PII) datasets, utilizing reporting dashboards or Jupyter notebooks for programmatic analysis. As a comprehensive solution, Tokern aims to enhance your data's return on investment, ensure compliance with regulations such as HIPAA, CCPA, and GDPR, and safeguard sensitive information against insider threats seamlessly. It provides centralized management for metadata related to users, datasets, and jobs, which supports various other data governance functionalities. With the capability to track Column Level Data Lineage for platforms like Snowflake, AWS Redshift, and BigQuery, users can construct lineage from query histories or ETL scripts. Additionally, lineage exploration can be achieved through interactive graphs or programmatically via APIs or SDKs, offering a versatile approach to understanding data flow. Overall, Tokern empowers organizations to maintain robust data governance while navigating complex regulatory landscapes.

The Alation Agentic Data Intelligence Platform is designed to transform how enterprises manage, govern, and use data for AI and analytics. It combines search, cataloging, governance, lineage, and analytics into one unified solution, turning metadata into actionable insights. AI-powered agents automate critical tasks like documentation, data quality monitoring, and product creation, freeing teams from repetitive manual work. Its Active Metadata Graph and workflow automation capabilities ensure that data remains accurate, consistent, and trustworthy across systems. With 120+ pre-built connectors, including integrations with AWS, Snowflake, Salesforce, and Databricks, Alation integrates seamlessly into enterprise ecosystems. The platform enables organizations to govern AI responsibly, ensuring compliance, transparency, and ethical use of data. Enterprises benefit from improved self-service analytics, faster data-driven decisions, and a stronger data culture. With industry leaders like Salesforce and 40% of the Fortune 100 relying on it, Alation is proven to help businesses unlock the value of their data.

Examine the usage of your data assets, focusing on aspects like popularity, utilization, and schema coverage. Gain vital insights into your data assets, including their quality and usage metrics. You can easily locate and filter the necessary data by leveraging metadata tags and descriptions. Additionally, these insights will help you drive data governance and establish clear ownership within your organization. By implementing a streamlined lineage from data lakes to warehouses, you can enhance collaboration and accountability. An automatically generated field-level lineage map provides a comprehensive view of your entire data ecosystem. Moreover, anomaly detection systems adapt by learning from your data trends and seasonal variations, ensuring automatic backfilling with historical data. Thresholds driven by machine learning are specifically tailored for each data segment, relying on actual data rather than just metadata to ensure accuracy and relevance. This holistic approach empowers organizations to better manage their data landscape effectively.

Kylo serves as an open-source platform designed for effective management of enterprise-level data lakes, facilitating self-service data ingestion and preparation while also incorporating robust metadata management, governance, security, and best practices derived from Think Big's extensive experience with over 150 big data implementation projects. It allows users to perform self-service data ingestion complemented by features for data cleansing, validation, and automatic profiling. Users can manipulate data effortlessly using visual SQL and an interactive transformation interface that is easy to navigate. The platform enables users to search and explore both data and metadata, examine data lineage, and access profiling statistics. Additionally, it provides tools to monitor the health of data feeds and services within the data lake, allowing users to track service level agreements (SLAs) and address performance issues effectively. Users can also create batch or streaming pipeline templates using Apache NiFi and register them with Kylo, thereby empowering self-service capabilities. Despite organizations investing substantial engineering resources to transfer data into Hadoop, they often face challenges in maintaining governance and ensuring data quality, but Kylo significantly eases the data ingestion process by allowing data owners to take control through its intuitive guided user interface. This innovative approach not only enhances operational efficiency but also fosters a culture of data ownership within organizations.

The contemporary data workspace transforms the accessibility of your data assets, making everything from data tables to BI reports easily discoverable. With our robust search algorithms and user-friendly browsing experience, locating the right asset becomes effortless. Atlan simplifies the identification of poor-quality data through the automatic generation of data quality profiles. This includes features like variable type detection, frequency distribution analysis, missing value identification, and outlier detection, ensuring you have comprehensive support. By alleviating the challenges associated with governing and managing your data ecosystem, Atlan streamlines the entire process. Additionally, Atlan’s intelligent bots analyze SQL query history to automatically construct data lineage and identify PII data, enabling you to establish dynamic access policies and implement top-notch governance. Even those without technical expertise can easily perform queries across various data lakes, warehouses, and databases using our intuitive query builder that resembles Excel. Furthermore, seamless integrations with platforms such as Tableau and Jupyter enhance collaborative efforts around data, fostering a more connected analytical environment. Thus, Atlan not only simplifies data management but also empowers users to leverage data effectively in their decision-making processes.

Hybrid data estates create silos, duplicate datasets, and “unknown” data flows. Teams lose time finding the right data, can’t trace lineage for audits, and take on risk when changes break downstream reports and apps. Rocket® DataEdge™ is a metadata-driven data intelligence, integration, and virtualization platform. It connects and delivers data across heterogeneous systems while adding business and technical context, lineage, and end-to-end visibility so teams can understand what data exists, where it’s used, and how it moves. Key capabilities: • Metadata capture and cataloging with glossary/tags/ownership • Lineage and impact visibility to troubleshoot and govern change • Seamless hybrid data integration plus virtual/federated access • Connectors/APIs for mainframe, distributed, and cloud sources/targets • Policy-driven security/governance controls across environments Outcome: faster time-to-data with fewer brittle pipelines, audit-ready visibility, and more trusted analytics/AI inputs.

This is the essential tool for metadata management. In just 5 minutes, automatically populate your entire catalogue! Data Discovery. Data Discovery. Find the data you need from any part of your data ecosystem, starting with the database and ending with the specific values for each field. Automated documentation of your data from existing data storage. First-class support for unstructured and tabular data. Automated data governance actions. Data Lineage. Data Lineage. Explore your data lineage to understand where your data is coming from and where it is headed. View the impact analysis of changes. See all up- and downstream impacts. Visualize connections and relationships. API AccessNew. Tree Schema API allows you to manage your data lineage in code and keep your catalog current. Integrate Data Lineage in CICD pipelines Capture values & description within your code Analyze the impact of breaking changes. Data Dictionary. Know the key terms and lingo which drive your business. Define the context and scope of keywords

Collate is a metadata platform powered by AI that equips data teams with automated tools for discovery, observability, quality, and governance, utilizing agent-based workflows for efficiency. It is constructed on the foundation of OpenMetadata and features a cohesive metadata graph, providing over 90 seamless connectors for gathering metadata from various sources like databases, data warehouses, BI tools, and data pipelines. This platform not only offers detailed column-level lineage and data profiling but also implements no-code quality tests to ensure data integrity. The AI agents play a crucial role in streamlining processes such as data discovery, permission-sensitive querying, alert notifications, and incident management workflows on a large scale. Furthermore, the platform includes real-time dashboards, interactive analyses, and a shared business glossary that cater to both technical and non-technical users, facilitating the management of high-quality data assets. Additionally, its continuous monitoring and governance automation help uphold compliance with regulations such as GDPR and CCPA, which significantly minimizes the time taken to resolve data-related issues and reduces the overall cost of ownership. This comprehensive approach to data management not only enhances operational efficiency but also fosters a culture of data stewardship across the organization.

Transform your big data processes and create intelligent knowledge repositories with the Data Lake Governance Center (DGC), a comprehensive platform for managing all facets of data lake operations, including design, development, integration, quality, and asset management. With its intuitive visual interface, you can establish a robust data lake governance framework that enhances the efficiency of your data lifecycle management. Leverage analytics and metrics to uphold strong governance throughout your organization, while also defining and tracking data standards with the ability to receive real-time alerts. Accelerate the development of data lakes by easily configuring data integrations, models, and cleansing protocols to facilitate the identification of trustworthy data sources. Enhance the overall business value derived from your data assets. DGC enables the creation of tailored solutions for various applications, such as smart government, smart taxation, and smart campuses, while providing valuable insights into sensitive information across your organization. Additionally, DGC empowers businesses to establish comprehensive catalogs, classifications, and terminologies for their data. This holistic approach ensures that data governance is not just a task, but a core aspect of your enterprise's strategy.

If you're looking to establish a governed delta lake, create a data warehouse, or transition from a conventional database to a contemporary cloud data solution, Lyftrondata has you covered. You can effortlessly create and oversee all your data workloads within a single platform, automating the construction of your pipeline and warehouse. Instantly analyze your data using ANSI SQL and business intelligence or machine learning tools, and easily share your findings without the need for custom coding. This functionality enhances the efficiency of your data teams and accelerates the realization of value. You can define, categorize, and locate all data sets in one centralized location, enabling seamless sharing with peers without the complexity of coding, thus fostering insightful data-driven decisions. This capability is particularly advantageous for organizations wishing to store their data once, share it with various experts, and leverage it repeatedly for both current and future needs. In addition, you can define datasets, execute SQL transformations, or migrate your existing SQL data processing workflows to any cloud data warehouse of your choice, ensuring flexibility and scalability in your data management strategy.

Microsoft Purview serves as a comprehensive data governance platform that facilitates the management and oversight of your data across on-premises, multicloud, and software-as-a-service (SaaS) environments. With its capabilities in automated data discovery, sensitive data classification, and complete data lineage tracking, you can effortlessly develop a thorough and current representation of your data ecosystem. This empowers data users to access reliable and valuable data easily. The service provides automated identification of data lineage and classification across various sources, ensuring a cohesive view of your data assets and their interconnections for enhanced governance. Through semantic search, users can discover data using both business and technical terminology, providing insights into the location and flow of sensitive information within a hybrid data environment. By leveraging the Purview Data Map, you can lay the groundwork for effective data utilization and governance, while also automating and managing metadata from diverse sources. Additionally, it supports the classification of data using both predefined and custom classifiers, along with Microsoft Information Protection sensitivity labels, ensuring that your data governance framework is robust and adaptable. This combination of features positions Microsoft Purview as an essential tool for organizations seeking to optimize their data management strategies.

Blindata encompasses all the essential components of a comprehensive Data Governance program. Its features, including the Business Glossary, Data Catalog, and Data Lineage, work together to provide a cohesive and thorough perspective on your data. The Data Classification module assigns semantic significance to the data, while the Data Quality, Issue Management, and Data Stewardship modules enhance data reliability and foster trust. Additionally, specific functionalities for privacy compliance are available, such as a registry for processing activities, centralized management of privacy notes, and a consent registry that incorporates Blockchain for notarization. The Blindata Agent facilitates connections to various data sources, enabling the collection of metadata, including data structures like Tables, Views, and Fields, as well as data quality metrics and reverse lineage. With a modular design and fully API-driven architecture, Blindata supports seamless integration with vital business systems, including DBMS, Active Directory, e-commerce platforms, and various Data Platforms. This versatile solution can be deployed as a Software as a Service (SaaS), installed on-premises, or acquired through the AWS Marketplace, making it accessible for a wide range of organizational needs. Its flexibility ensures that businesses can tailor their Data Governance approach to meet specific requirements effectively.

Dremio provides lightning-fast queries as well as a self-service semantic layer directly to your data lake storage. No data moving to proprietary data warehouses, and no cubes, aggregation tables, or extracts. Data architects have flexibility and control, while data consumers have self-service. Apache Arrow and Dremio technologies such as Data Reflections, Columnar Cloud Cache(C3), and Predictive Pipelining combine to make it easy to query your data lake storage. An abstraction layer allows IT to apply security and business meaning while allowing analysts and data scientists access data to explore it and create new virtual datasets. Dremio's semantic layers is an integrated searchable catalog that indexes all your metadata so business users can make sense of your data. The semantic layer is made up of virtual datasets and spaces, which are all searchable and indexed.

Varada offers a cutting-edge big data indexing solution that adeptly balances performance and cost while eliminating the need for data operations. This distinct technology acts as an intelligent acceleration layer within your data lake, which remains the central source of truth and operates within the customer's cloud infrastructure (VPC). By empowering data teams to operationalize their entire data lake, Varada facilitates data democratization while ensuring fast, interactive performance, all without requiring data relocation, modeling, or manual optimization. The key advantage lies in Varada's capability to automatically and dynamically index pertinent data, maintaining the structure and granularity of the original source. Additionally, Varada ensures that any query can keep pace with the constantly changing performance and concurrency demands of users and analytics APIs, while also maintaining predictable cost management. The platform intelligently determines which queries to accelerate and which datasets to index, while also flexibly adjusting the cluster to match demand, thereby optimizing both performance and expenses. This holistic approach to data management not only enhances operational efficiency but also allows organizations to remain agile in an ever-evolving data landscape.

Acceldata stands out as the sole Data Observability platform that offers total oversight of enterprise data systems, delivering extensive visibility into intricate and interconnected data architectures. It integrates signals from various workloads, as well as data quality, infrastructure, and security aspects, thereby enhancing both data processing and operational efficiency. With its automated end-to-end data quality monitoring, it effectively manages the challenges posed by rapidly changing datasets. Acceldata also provides a unified view to anticipate, detect, and resolve data-related issues in real-time. Users can monitor the flow of business data seamlessly and reveal anomalies within interconnected data pipelines, ensuring a more reliable data ecosystem. This holistic approach not only streamlines data management but also empowers organizations to make informed decisions based on accurate insights.

IBM InfoSphere® Information Governance Catalog is an online platform designed to help users investigate, comprehend, and evaluate their data. It facilitates the creation and management of a shared business lexicon, enables the documentation and implementation of policies and rules, and allows for the monitoring of data lineage. By integrating with IBM Watson® Knowledge Catalog, users can utilize existing curated datasets and enhance their on-premises Information Governance Catalog investment by extending it to the cloud. This knowledge catalog empowers data professionals by providing easy access to valuable metadata, ensuring that data science and analytics teams can find the optimal resources for their needs while maintaining alignment with enterprise governance standards. It establishes a unified business language and terminology that fosters a more profound understanding of all data assets, whether they are structured, semi-structured, or unstructured. Additionally, it records governance policies and implements rules, guiding how information should be organized, stored, transformed, and transferred, thus promoting efficiency and compliance within an organization. Overall, the platform not only supports effective data management but also enhances collaboration among teams by ensuring that everyone has access to the same foundational data understanding.

Delphix is the industry leader for DataOps. It provides an intelligent data platform that accelerates digital change for leading companies around world. The Delphix DataOps Platform supports many systems, including mainframes, Oracle databases, ERP apps, and Kubernetes container. Delphix supports a wide range of data operations that enable modern CI/CD workflows. It also automates data compliance with privacy regulations such as GDPR, CCPA and the New York Privacy Act. Delphix also helps companies to sync data between private and public clouds, accelerating cloud migrations and customer experience transformations, as well as the adoption of disruptive AI technologies.

Knowledge Catalog is a modern, AI-powered data catalog developed by Google Cloud to provide comprehensive governance and context for enterprise data. It works by automatically extracting meaning from structured and unstructured data, building a dynamic context graph that connects data assets. This allows organizations to discover, understand, and manage their data more effectively. The platform plays a critical role in improving AI accuracy by grounding models in reliable enterprise data, reducing hallucinations. It offers features such as data lineage tracking, data profiling, and quality measurement to ensure data reliability. Users can also create business glossaries and capture metadata to enhance data organization and accessibility. Knowledge Catalog supports integration with custom data sources and Google Cloud services, making it highly flexible. It enables both traditional analytics and advanced AI applications, including agent-based workflows. The platform also provides powerful search capabilities for locating data resources quickly. By centralizing data context and governance, it reduces operational complexity for data teams. Overall, Knowledge Catalog empowers organizations to build trusted, well-governed data environments.

Decube is a comprehensive data management platform designed to help organizations manage their data observability, data catalog, and data governance needs. Our platform is designed to provide accurate, reliable, and timely data, enabling organizations to make better-informed decisions. Our data observability tools provide end-to-end visibility into data, making it easier for organizations to track data origin and flow across different systems and departments. With our real-time monitoring capabilities, organizations can detect data incidents quickly and reduce their impact on business operations. The data catalog component of our platform provides a centralized repository for all data assets, making it easier for organizations to manage and govern data usage and access. With our data classification tools, organizations can identify and manage sensitive data more effectively, ensuring compliance with data privacy regulations and policies. The data governance component of our platform provides robust access controls, enabling organizations to manage data access and usage effectively. Our tools also allow organizations to generate audit reports, track user activity, and demonstrate compliance with regulatory requirements.

OvalEdge, a cost-effective data catalogue, is designed to provide end-to-end data governance and privacy compliance. It also provides fast, reliable analytics. OvalEdge crawls the databases, BI platforms and data lakes of your organization to create an easy-to use, smart inventory. Analysts can quickly discover data and provide powerful insights using OvalEdge. OvalEdge's extensive functionality allows users to improve data access, data literacy and data quality.

Connect and centralize data. Transform your data landscape into a flexible powerhouse. Data Virtuality is a data integration platform that allows for instant data access, data centralization, and data governance. Logical Data Warehouse combines materialization and virtualization to provide the best performance. For high data quality, governance, and speed-to-market, create your single source data truth by adding a virtual layer to your existing data environment. Hosted on-premises or in the cloud. Data Virtuality offers three modules: Pipes Professional, Pipes Professional, or Logical Data Warehouse. You can cut down on development time up to 80% Access any data in seconds and automate data workflows with SQL. Rapid BI Prototyping allows for a significantly faster time to market. Data quality is essential for consistent, accurate, and complete data. Metadata repositories can be used to improve master data management.

K2View believes that every enterprise should be able to leverage its data to become as disruptive and agile as possible. We enable this through our Data Product Platform, which creates and manages a trusted dataset for every business entity – on demand, in real time. The dataset is always in sync with its sources, adapts to changes on the fly, and is instantly accessible to any authorized data consumer. We fuel operational use cases, including customer 360, data masking, test data management, data migration, and legacy application modernization – to deliver business outcomes at half the time and cost of other alternatives.

A metadata management and data lineage platform for hybrid enterprises whose data spans mainframe, distributed, and cloud. It automatically discovers datasets, pipelines, dependencies, and transformations, then provides end-to-end lineage and impact analysis so teams can trace a KPI to its source, predict what will break before changing a job/table, and prove where sensitive fields (PII) flowed. Key capabilities: • Automated metadata collection across heterogeneous platforms. • Lineage mapping from source through ETL/ELT, warehouse/lakehouse, and BI. • Impact analysis and change visibility. • Field/column-level tracing (where supported) for audits, root-cause analysis, and compliance. • Glossary/tagging to connect technical assets to business definitions and ownership. Outcome: fewer production surprises, faster modernization, and more trusted analytics/AI backed by audit-ready evidence. Partner with us to unlock actionable insights and modernize your data strategy today.

Detect and address code and optimization challenges in real-time, mitigate data incidents before deployment, and oversee data-affecting code modifications comprehensively—from the operational database to the user interface dashboard. With automated, column-level data lineage tracing the journey from the operational database to the reporting layer, every dependency is meticulously examined. Foundational automates the enforcement of data contracts by scrutinizing each repository in both upstream and downstream directions, directly from the source code. Leverage Foundational to proactively uncover code and data-related issues, prevent potential problems, and establish necessary controls and guardrails. Moreover, implementing Foundational can be achieved in mere minutes without necessitating any alterations to the existing codebase, making it an efficient solution for organizations. This streamlined setup promotes quicker response times to data governance challenges.

The Collibra Data Intelligence Cloud serves as your comprehensive platform for engaging with data, featuring an exceptional catalog, adaptable governance, ongoing quality assurance, and integrated privacy measures. Empower your teams with a premier data catalog that seamlessly merges governance, privacy, and quality controls. Elevate efficiency by enabling teams to swiftly discover, comprehend, and access data from various sources, business applications, BI, and data science tools all within a unified hub. Protect your data's privacy by centralizing, automating, and streamlining workflows that foster collaboration, implement privacy measures, and comply with international regulations. Explore the complete narrative of your data with Collibra Data Lineage, which automatically delineates the connections between systems, applications, and reports, providing a contextually rich perspective throughout the organization. Focus on the most critical data while maintaining confidence in its relevance, completeness, and reliability, ensuring that your organization thrives in a data-driven world. By leveraging these capabilities, you can transform your data management practices and drive better decision-making across the board.

Kensu provides real-time monitoring of the complete data usage quality, empowering your team to proactively avert data-related issues. Grasping the significance of data application is more crucial than merely focusing on the data itself. With a unified and comprehensive perspective, you can evaluate data quality and lineage effectively. Obtain immediate insights regarding data utilization across various systems, projects, and applications. Instead of getting lost in the growing number of repositories, concentrate on overseeing the data flow. Facilitate the sharing of lineages, schemas, and quality details with catalogs, glossaries, and incident management frameworks. Instantly identify the underlying causes of intricate data problems to stop any potential "datastrophes" from spreading. Set up alerts for specific data events along with their context to stay informed. Gain clarity on how data has been gathered, replicated, and altered by different applications. Identify anomalies by analyzing historical data patterns. Utilize lineage and past data insights to trace back to the original cause, ensuring a comprehensive understanding of your data landscape. This proactive approach not only preserves data integrity but also enhances overall operational efficiency.

Numerous products are available that assist businesses in this endeavor, but if your main goals are to build a data-driven organization while maximizing efficiency and minimizing costs, the only option worth considering is Fraxses, the leading distributed data platform in the world. Fraxses gives clients on-demand access to data, providing impactful insights through a solution that supports either a data mesh or data fabric architecture. Imagine a data mesh as a framework that overlays various data sources, linking them together and allowing them to operate as a cohesive unit. In contrast to other platforms focused on data integration and virtualization, Fraxses boasts a decentralized architecture that sets it apart. Although Fraxses is fully capable of accommodating traditional data integration methods, the future is leaning towards a novel approach where data is delivered directly to users, eliminating the necessity for a centrally managed data lake or platform. This innovative perspective not only enhances user autonomy but also streamlines data accessibility across the organization.

DataWise is a specialized solution designed specifically for the modernization of SAP data. It effectively connects SAP systems, whether ECC or S/4HANA, with the Databricks Lakehouse, facilitating the conversion of isolated operational data into a reliable and analytics-ready platform that supports real-time decision-making and fosters AI advancements. By utilizing SAP-native connectors and offering prebuilt models for various modules such as SD, MM, PM, Finance, Ariba, and SuccessFactors, DataWise significantly enhances value. It employs automated ELT pipelines to transfer data into Delta Lake, while its MatchX AI-driven data quality engine ensures data cleansing, standardization, deduplication, and entity matching, thereby improving data accuracy and completeness on a large scale. Comprehensive governance is maintained throughout the process via Unity Catalog, which implements fine-grained access controls and tracks data lineage. After the data has been standardized and governed, DataWise enables seamless activation of your SAP data across business intelligence dashboards, machine learning functionalities, and event-driven workflows, all without interfering with your core ERP operations. This innovative approach not only streamlines data accessibility but also empowers organizations to leverage their SAP data for enhanced insights and decision-making.

Explore the exceptional features offered by Global IDs, which provide a comprehensive range of Enterprise Data Solutions including data governance, compliance, cloud migration, rationalization, privacy, analytics, and more. The Global IDs EDA Platform includes essential functionalities such as automated discovery and profiling, data classification, data lineage, and data quality, all aimed at ensuring that data is transparent, reliable, and understandable throughout the ecosystem. Additionally, the architecture of the Global IDs EDA platform is built for seamless integration, enabling access to all its functionalities through APIs. This platform effectively automates data management for organizations of varying sizes and diverse data environments. By utilizing Global IDs EDA, businesses can significantly enhance their data management practices and drive better decision-making.

The RecordPoint Data Trust platform helps highly regulated organizations manage data throughout its lifecycle, regardless of system. We work with organizations in highly regulated industries to ensure their data is right where it should be - safeguarded for privacy, security, and governance.

Aggua serves as an augmented AI platform for data fabric that empowers both data and business teams to access their information, fostering trust while providing actionable data insights, ultimately leading to more comprehensive, data-driven decision-making. Rather than being left in the dark about the intricacies of your organization's data stack, you can quickly gain clarity with just a few clicks. This platform offers insights into data costs, lineage, and documentation without disrupting your data engineer’s busy schedule. Instead of investing excessive time on identifying how a change in data type might impact your data pipelines, tables, and overall infrastructure, automated lineage allows data architects and engineers to focus on implementing changes rather than sifting through logs and DAGs. As a result, teams can work more efficiently and effectively, leading to faster project completions and improved operational outcomes.

Dawiso is a comprehensive platform designed to simplify data management by integrating governance with usability for the entire organization. Central to Dawiso is its AI-powered data catalog, which empowers teams to quickly discover and understand trusted data across various systems, reports, and business applications. The platform’s flexible governance capabilities, alongside intuitive documentation apps, make it easy for both technical and non-technical users to collaborate effectively. Dawiso increases confidence in data through visual data lineage that clearly maps connections and dependencies across sources and systems. It supports regulatory compliance with customizable workflows, role-based access controls, and detailed metadata capture. By providing business-friendly tools and structured governance, Dawiso bridges communication gaps and streamlines data-driven decision-making. The platform promotes transparency, security, and usability in data management. Overall, Dawiso is built to enhance collaboration and trust in organizational data assets.

Velox Software Suite allows data migration and system integration throughout an entire organization. The suite includes two applications: Migration Studio VXm -- which allows users to control data migrations; and Integration Server VXi -- which automates data processing and integration. Extract multiple sources and send to multiple destinations. A near real-time, unified view of all data without having to move between sources. Physically combine data from multiple sources, reduce storage locations, and transform according to business rules.

Quest's erwin Data Catalog is a powerful tool for metadata management that assists organizations in understanding their data assets and their locations, encompassing both static and dynamic data. It provides insights into the available data and metadata related to specific topics, enabling users to swiftly locate relevant sources and resources for analysis and informed decision-making. By automating the tasks associated with harvesting, integrating, activating, and governing enterprise data in line with business needs, erwin Data Catalog enhances accuracy and accelerates the value derived from data governance initiatives and digital transformation projects, such as those involving data warehouses, data lakes, data vaults, and cloud migrations. Effective management of metadata is crucial for sustainable data governance and is essential for any organizational endeavor reliant on data for successful outcomes. The erwin Data Catalog streamlines various functions including enterprise metadata management, data mapping, cataloging, code generation, data profiling, and tracking data lineage, ultimately improving overall data management efficiency. As a result, organizations can better harness their data for strategic advantage and operational excellence.

Oracle Big Data SQL Cloud Service empowers companies to swiftly analyze information across various platforms such as Apache Hadoop, NoSQL, and Oracle Database, all while utilizing their existing SQL expertise, security frameworks, and applications, achieving remarkable performance levels. This solution streamlines data science initiatives and facilitates the unlocking of data lakes, making the advantages of Big Data accessible to a wider audience of end users. It provides a centralized platform for users to catalog and secure data across Hadoop, NoSQL systems, and Oracle Database. With seamless integration of metadata, users can execute queries that combine data from Oracle Database with that from Hadoop and NoSQL databases. Additionally, the service includes utilities and conversion routines that automate the mapping of metadata stored in HCatalog or the Hive Metastore to Oracle Tables. Enhanced access parameters offer administrators the ability to customize column mapping and govern data access behaviors effectively. Furthermore, the capability to support multiple clusters allows a single Oracle Database to query various Hadoop clusters and NoSQL systems simultaneously, thereby enhancing data accessibility and analytics efficiency. This comprehensive approach ensures that organizations can maximize their data insights without compromising on performance or security.

The primary obstacle in expanding AI-driven decision-making lies in the underutilization of data. IBM Cloud Pak® for Data provides a cohesive platform that integrates a data fabric, enabling seamless connection and access to isolated data, whether it resides on-premises or in various cloud environments, without necessitating data relocation. It streamlines data accessibility by automatically identifying and organizing data to present actionable knowledge assets to users, while simultaneously implementing automated policy enforcement to ensure secure usage. To further enhance the speed of insights, this platform incorporates a modern cloud data warehouse that works in harmony with existing systems. It universally enforces data privacy and usage policies across all datasets, ensuring compliance is maintained. By leveraging a high-performance cloud data warehouse, organizations can obtain insights more rapidly. Additionally, the platform empowers data scientists, developers, and analysts with a comprehensive interface to construct, deploy, and manage reliable AI models across any cloud infrastructure. Moreover, enhance your analytics capabilities with Netezza, a robust data warehouse designed for high performance and efficiency. This comprehensive approach not only accelerates decision-making but also fosters innovation across various sectors.

SAP AIW serves as a comprehensive platform for enterprise data governance, facilitating the oversight, tracking, and management of both structured and unstructured asset data across various systems-of-record, including ERP, engineering, PLM, and maintenance systems. Enhance the efficiency of your master data governance by executing intricate multi-object change requests or extensive master data modifications effortlessly in a single action. By ensuring consistent and synchronized data from all record systems, accessible through a unified view, you can significantly reduce environmental and health and safety risks. Maintain and supervise your maintenance tasks with standardized master data, leading to minimized downtime and heightened productivity on the shop floor. Utilize an advanced user interface designed for multi-change object requests, which allows for efficient management of a complete asset structure. Additionally, enrich your asset data by incorporating information from both external and internal sources, which can then be integrated into your internal systems of record. Elevate usability with user-friendly hierarchy processing features that enable searching, copying, and replacing data seamlessly, thereby streamlining the overall data management process. This approach not only simplifies governance but also fosters a more integrated and responsive data environment.

Bid farewell to abandoned data catalogs. Acryl Cloud accelerates time-to-value by implementing Shift Left methodologies for data producers and providing an easy-to-navigate interface for data consumers. It enables the continuous monitoring of data quality incidents in real-time, automating anomaly detection to avert disruptions and facilitating swift resolutions when issues arise. With support for both push-based and pull-based metadata ingestion, Acryl Cloud simplifies maintenance, ensuring that information remains reliable, current, and authoritative. Data should be actionable and operational. Move past mere visibility and leverage automated Metadata Tests to consistently reveal data insights and identify new opportunities for enhancement. Additionally, enhance clarity and speed up resolutions with defined asset ownership, automatic detection, streamlined notifications, and temporal lineage for tracing the origins of issues while fostering a culture of proactive data management.

In just 15 minutes, you can set up your automated data catalogue and receive column-level lines, Entity Relationship diagrams, and auto-populated documentation in 24 hours. You can easily tag, find, and add documentation to data so everyone can find the right one for them. Select Star automatically detects your column-level data lineage and displays it. Now you can trust the data by knowing where it came. Select Star automatically displays how your company uses data. This allows you to identify relevant data fields without having to ask anyone else. Select Star ensures that your data is protected with AICPA SOC2 Security, Confidentiality and Availability standards.

Establish federated source data identifiers to allow users to connect to various data sources seamlessly. Utilize a web-based administrative console to streamline the management of user access, privileges, and authorizations for easier oversight. Incorporate data quality enhancements such as match-code generation and parsing functions within the view to ensure high-quality data. Enhance performance through the use of in-memory data caches and efficient scheduling methods. Protect sensitive information with robust data masking and encryption techniques. This approach keeps application queries up-to-date and readily accessible to users while alleviating the burden on operational systems. You can set access permissions at multiple levels, including catalog, schema, table, column, and row, allowing for tailored security measures. The advanced capabilities for data masking and encryption provide the ability to control not just who can see your data but also the specific details they can access, thereby significantly reducing the risk of sensitive information being compromised. Ultimately, these features work together to create a secure and efficient data management environment.

Hybrid data stacks create duplication and delay: mainframe records, on prem apps, and cloud platforms often end up with mismatched copies, brittle ETL, and long lead times for “just one more feed.” Moving large datasets for every use case is slow, costly, and expands the security surface. Rocket® Data Virtualization™ is a data virtualization and federated query solution that enables a governed, virtual data model across mainframe, distributed, and cloud sources—so BI tools, analysts, and applications can query sensitive data in place. Key capabilities: • Federated SQL queries/joins across heterogeneous sources with pushdown • Standard connectivity (e.g., JDBC/ODBC/REST) for BI, analytics, and apps • Virtual views/semantic layer to simplify access and reuse logic • Centralized security controls, auditing, and masking (where supported) • Optional caching/materialization to balance performance and freshness Result: faster time to data with less ETL and lower migration risk.